diff --git a/README.md b/README.md index 51f7dbb9f..c781a44b9 100644 --- a/README.md +++ b/README.md @@ -17,6 +17,10 @@ Qibocal key features: Qibocal documentation is available [here](https://qibo.science/qibocal/stable/). +>[!NOTE] +> Qibocal `main` contains some breaking changes compared to `0.1` versions. +> A small guide to make the transition as smooth as possible can be found [`here`](changes.md). + ## Installation The package can be installed by source: diff --git a/calibration_scripts/rx_calibration.py b/calibration_scripts/rx_calibration.py index f71fd20f5..8ae09d17e 100644 --- a/calibration_scripts/rx_calibration.py +++ b/calibration_scripts/rx_calibration.py @@ -13,10 +13,10 @@ e.platform.settings.nshots = 2000 rabi_output = e.rabi_amplitude( - min_amp_factor=0.5, - max_amp_factor=1.5, - step_amp_factor=0.01, - pulse_length=e.platform.qubits[target].native_gates.RX.duration, + min_amp=0.0, + max_amp=2, + step_amp=0.01, + pulse_length=e.platform.natives.single_qubit[target].RX[0][1].duration, ) # update only if chi2 is satisfied if rabi_output.results.chi2[target][0] > 2: @@ -43,10 +43,10 @@ ramsey_output.update_platform(e.platform) rabi_output_2 = e.rabi_amplitude( - min_amp_factor=0.5, - max_amp_factor=1.5, - step_amp_factor=0.01, - pulse_length=e.platform.qubits[target].native_gates.RX.duration, + min_amp=0, + max_amp=0.2, + step_amp=0.01, + pulse_length=e.platform.natives.single_qubit[target].RX[0][1].duration, ) # update only if chi2 is satisfied if rabi_output_2.results.chi2[target][0] > 2: @@ -61,10 +61,10 @@ ) rabi_output_3 = e.rabi_amplitude( - min_amp_factor=0.5, - max_amp_factor=1.5, - step_amp_factor=0.01, - pulse_length=e.platform.qubits[target].native_gates.RX.duration, + min_amp=0, + max_amp=0.2, + step_amp=0.01, + pulse_length=e.platform.natives.single_qubit[target].RX[0][1].duration, ) # update only if chi2 is satisfied if rabi_output_3.results.chi2[target][0] > 2: diff --git a/changes.md b/changes.md new file mode 100644 index 000000000..cb90d7e36 --- /dev/null +++ b/changes.md @@ -0,0 +1,14 @@ +## Changes in `main` +After merging [#990](https://github.com/qiboteam/qibocal/pull/990), Qibocal is now compatible with Qibolab 0.2.1. +For this reason, a small internal refactoring and some breaking changes were required. +The main differences concern the acquisition functions and the protocol parameters: +- The amplitudes are no longer relative to the values defined in the platform, but to +the maximum value the instruments reach (internally stored in `Qibolab`). +It implies renaming the amplitude parameters and converting the new amplitude level accordingly. +- The platform parameters that were previously in the `parameters.json` +but required by `Qibolab` to execute circuits and pulse sequences (like $E_J$, $T_1$ and $T_2$), +are moved to the `calibration.json` stored inside each platform folder. +- In the Rabi and flipping experiment, Qibocal provides the possibility to calibrate the $RX(\pi/2)$. +- Small changes in the report template. +- Some protocols are not supported anymore(https://github.com/qiboteam/qibocal/pull/990#issue-2559341729 + for a list of them). diff --git a/doc/source/getting-started/interface.rst b/doc/source/getting-started/interface.rst index 2350dcc84..f88fc2430 100644 --- a/doc/source/getting-started/interface.rst +++ b/doc/source/getting-started/interface.rst @@ -105,7 +105,7 @@ This program will upload your report to the server and generate an unique URL. ``qq compare`` -^^^^^^^^^^^^^ +^^^^^^^^^^^^^^ Using ``qq compare`` it is possible to compare together two ``Qibocal`` reports. diff --git a/doc/source/protocols/avoided_crossing.png b/doc/source/protocols/avoided_crossing.png deleted file mode 100644 index 94b1b9196..000000000 Binary files a/doc/source/protocols/avoided_crossing.png and /dev/null differ diff --git a/doc/source/protocols/avoided_crossing.rst b/doc/source/protocols/avoided_crossing.rst deleted file mode 100644 index 5ee12050d..000000000 --- a/doc/source/protocols/avoided_crossing.rst +++ /dev/null @@ -1,55 +0,0 @@ -Avoided crossing -================ - -In the avoided crossing experiment the goal is to study the qubit-flux dependency -of a couple of qubits to precisely tune the interaction between them at specific -frequencies in order to calibrate the CZ and the iSWAP gates. - -In the avoided crossing experiment for CZ qubit gates, the interaction between -two qubits is controlled by tuning their energy levels such that the :math:`\ket{11}` -(both qubits in the excited state) and :math:`\ket{02}` (one qubit in the ground state and -the other in the second excited state) states come into resonance. -At this resonance point, the energy levels of these states experience an avoided -crossing, a key phenomenon that enables the controlled-Z (CZ) gate operation. -By observing the avoided crossing, one can confirm that the coupling between the -qubits is strong enough to facilitate the necessary interaction for the CZ gate. -Hence, precise tuning of these states is essential for achieving the correct gate -operation. - -In the avoided crossing experiment for iSWAP qubit gates, the key focus is on -the interaction between the :math:`\ket{10}` and :math:`\ket{01}` states. -When tuning the qubits' energy levels, these two states come into resonance, -creating an avoided crossing, which is the fundamental operation of -the iSWAP gate. - -In this protocol, for each qubit pair we execute a qubit flux dependency of the -01 and 02 transitions on the qubit with higher frequency and we fit the data to -find the flux-frequency relationship that we use to estimate the bias needed to -reach the CZ and iSWAP interaction points. - -Parameters -^^^^^^^^^^ - -.. autoclass:: - qibocal.protocols.flux_dependence.avoided_crossing.AvoidedCrossingParameters - :noindex: - -Example -^^^^^^^ - -It follows a runcard example of this experiment. - -.. code-block:: yaml - - - id: avoided crossing - operation: avoided_crossing - parameters: - bias_step: 0.01 - bias_width: 0.2 - drive_amplitude: 0.5 - freq_step: 500000 - freq_width: 100000000 - -The expected output is the following: - -.. image:: avoided_crossing.png diff --git a/doc/source/protocols/chevron.rst b/doc/source/protocols/chevron.rst index 9565cad43..d4a95cff3 100644 --- a/doc/source/protocols/chevron.rst +++ b/doc/source/protocols/chevron.rst @@ -1,6 +1,20 @@ Chevron ======= +In order to implement a two-qubit gate in superconducting quantum computing, it is necessary to bring the two qubits near resonance using specific pulse sequences. +The Chevron protocol implemented in Qibocal can be used to calibrate both CZ and iSWAP gates. + +The pulse sequence used to calibrate the iSWAP gate consists of a :math:`\pi` pulse followed by a flux pulse of varying amplitude and duration, applied to the qubit with the highest frequency in the pair. +The initial :math:`pi` pulse brings the qubit into the state :math:`\ket{1}` while the flux pulse detunes its frequency near resonance with the second qubit. The implementation of the iSWAP gate leverages the avoided crossing between the states :math:`\ket{10}` and :math:`\ket{01}`. + +The expected population oscillation pattern follows: +.. math:: + p_e(t, \delta) = \frac{\Delta^2}{\Delta^2 + 4g^2} + {4g^2}{\Delta^2 + 4g^2}\cos^2\left(\frac{\sqrt{\Delta^2 + 4g^2}}{2}t\right) + +where :math:`\Delta=\omega_1 - \omega_2`, and :math:`g` is the coupling constant for the two qubits. + +The pulse sequence used to calibrate the CZ gate is the same as the one for the iSWAP gate, with the addition of an initial :math:`\pi` pulse applied to the qubit with the lower frequency so that both qubits are initially prepared in the :math:`\ket{1}`. With this sequence the CZ gate is implemented leveraging the avoided crossing between the states :math:`\ket{11}` and :math:`\ket{20}`. + Parameters ^^^^^^^^^^ @@ -18,9 +32,9 @@ Below is an example runcard for this experiment. - id: chevron operation: chevron parameters: - amplitude_max_factor: 1.1 - amplitude_min_factor: 0.9 - amplitude_step_factor: 0.01 + amplitude_max: 1.1 + amplitude_min: 0.9 + amplitude_step: 0.01 duration_max: 51 duration_min: 4 duration_step: 2 @@ -28,3 +42,8 @@ Below is an example runcard for this experiment. The expected output is the following: .. image:: chevron.png + +The plot represents the probability of measuring qubit 1 in the excited state as a function of the flux pulse parameters. +The characteristic shape of the plot, known as a Chevron pattern, appears as a consequence of the interaction of the two qubits through their coupling, leading to population exchange. + +Before running the Chevron routine it may be useful to run a Cryoscope experiment in order to correct possible distortions in the flux pulse. diff --git a/doc/source/protocols/coupler/chevron.png b/doc/source/protocols/coupler/chevron.png deleted file mode 100644 index 8cd3900e3..000000000 Binary files a/doc/source/protocols/coupler/chevron.png and /dev/null differ diff --git a/doc/source/protocols/coupler/chevron.rst b/doc/source/protocols/coupler/chevron.rst deleted file mode 100644 index 9c2579200..000000000 --- a/doc/source/protocols/coupler/chevron.rst +++ /dev/null @@ -1,35 +0,0 @@ -Coupler Chevron -=============== - -Parameters -^^^^^^^^^^ - -.. autoclass:: - qibocal.protocols.two_qubit_interaction.chevron.chevron.ChevronParameters - :noindex: - - -Example -^^^^^^^ - -Below is an example runcard for this experiment. - -.. code-block:: yaml - - - id: coupler chevron - operation: coupler_chevron - parameters: - amplitude_max_factor: 1.5 - amplitude_min_factor: 0.4 - amplitude_step_factor: 0.005 - duration_max: 100 - duration_min: 10 - duration_step: 2 - native: CZ - nshots: 256 - relaxation_time: 100000 - - -The expected output is the following: - -.. image:: chevron.png diff --git a/doc/source/protocols/cpmg/cpmg.png b/doc/source/protocols/cpmg/cpmg.png new file mode 100644 index 000000000..eaf7c175a Binary files /dev/null and b/doc/source/protocols/cpmg/cpmg.png differ diff --git a/doc/source/protocols/cpmg/cpmg.rst b/doc/source/protocols/cpmg/cpmg.rst new file mode 100644 index 000000000..bde28739c --- /dev/null +++ b/doc/source/protocols/cpmg/cpmg.rst @@ -0,0 +1,51 @@ +CPMG sequence +============= + +In this section we show how to run the dynamical decoupling sequence CPMG. + +The CPMG sequence consists in applying N equally spaced :math:`\pi` pulses +within two :math:`\pi / 2` pulses. By increasing the number of :math:`\pi` pulses :math:`T_2` +should increase since the estimation is less sensitive to noises of the type :math:`1/f` +eventually reaching the :math:`2 T_1` limit. + + +The fit is again a dumped exponential of the following form: + +.. math:: + + p_e(t) = A + B e^{ - t / T^{(N)}_2} + + +Parameters +^^^^^^^^^^ + +.. autoclass:: qibocal.protocols.coherence.cpmg.CpmgParameters + :noindex: + +Example +^^^^^^^ + +A possible runcard to launch a CPMG experiment could be the following: + +.. code-block:: yaml + + - id: CPMG + operation: cpmg + parameters: + delay_between_pulses_end: 100000 + delay_between_pulses_start: 4 + delay_between_pulses_step: 1000 + n: 10 + nshots: 1000 + +The expected output is the following: + +.. image:: cpmg.png + +:math:`T_2` is determined by fitting the output signal using +the formula presented above. + +Requirements +^^^^^^^^^^^^ + +- :ref:`single-shot` diff --git a/doc/source/protocols/drag/drag.rst b/doc/source/protocols/drag/drag.rst new file mode 100644 index 000000000..f05fdb6ba --- /dev/null +++ b/doc/source/protocols/drag/drag.rst @@ -0,0 +1,94 @@ +DRAG experiments +================ + +In this section we show how to run DRAG experiments using Qibocal + +.. _drag: + + +DRAG :cite:p:`Motzoi_2009, Gambetta_2011`: pulses can be used to lower both phase and leakage errors. +It consists of adding a quadrature component to the pulse which is proportional +to the time derivative of the in-phase component. Given a pulse with an in-phase component :math:`\Omega_x` +the quadrature component :math:`\Omega_y` is evaluated as + +.. math:: + + \Omega_y (t) = \beta \frac{d\Omega_x}{dt} , + +where :math:`\beta` is a scaling parameter. + +Qibocal provides two separate protocols to calibrate :math:`\beta`. + + +Method 1 +-------- + +:math:`\beta` can be extracted by playing the pulse sequence composed of +:math:`[R_X(\pi) - R_X(-\pi)]^N` for different values of :math:`\beta` as shown in :cite:p:`Sheldon_2016`. +The post-processing consists of measuring the probability of :math:`\ket{0}` for every :math:`\beta` +and fitting the curve with a cosine. The correct :math:`\beta` value is the one which maximizes +the curve. + +Parameters +^^^^^^^^^^ + +.. autoclass:: qibocal.protocols.drag.DragTuningParameters + :noindex: + +Example +^^^^^^^ + +.. code-block:: yaml + + - id: drag tuning + operation: drag_tuning + parameters: + beta_start: -1 + beta_end: 1 + beta_step: 0.1 + nflips: 5 + unrolling: true + + +Running this protocol you should get something like this: + +.. image:: drag_tuning.png + + +Method 2 +-------- + +The second method consists of playing two different sequences +:math:`R_Y(\pi) R_X(\pi/2)` and :math:`R_X(\pi) R_Y(\pi/2)`. These are two +of the AllXY sequences which exhibit opposite sign of phase error as highlighted +in :cite:p:`reed2013entanglementquantumerrorcorrection`. +The post-processing consists of measuring the probability of :math:`\ket{1}` for every :math:`\beta` +and performing a linear fit for both sequences. The correct :math:`\beta` value is the one where the two lines +cross. + +Parameters +^^^^^^^^^^ + +.. autoclass:: qibocal.protocols.drag_simple.DragTuningSimpleParameters + :noindex: + +Example +^^^^^^^ + +.. code-block:: yaml + + - id: drag simple + operation: drag_simple + parameters: + beta_start: -1 + beta_end: 1 + beta_step: 0.1 + unrolling: true + +.. image:: drag_simple.png + + +Requirements +^^^^^^^^^^^^ + +- :ref:`single-shot` diff --git a/doc/source/protocols/drag/drag_simple.png b/doc/source/protocols/drag/drag_simple.png new file mode 100644 index 000000000..8cdb0c3df Binary files /dev/null and b/doc/source/protocols/drag/drag_simple.png differ diff --git a/doc/source/protocols/drag/drag_tuning.png b/doc/source/protocols/drag/drag_tuning.png new file mode 100644 index 000000000..5077f1cf4 Binary files /dev/null and b/doc/source/protocols/drag/drag_tuning.png differ diff --git a/doc/source/protocols/flipping.rst b/doc/source/protocols/flipping.rst index a83a7ea5e..0ac31d154 100644 --- a/doc/source/protocols/flipping.rst +++ b/doc/source/protocols/flipping.rst @@ -1,8 +1,8 @@ Flipping ======== -The flipping experiment corrects the amplitude in the qubit drive pulse. In this experiment, -we applying an :math:`R_x(\pi/2)` rotation followed by :math:`N` flips (two :math:`R_x(\pi)` rotations) +The flipping experiment corrects the amplitude in the qubit drive pulse for :math:`R_x(\pi)` rotations. In this experiment, +we apply an :math:`R_x(\pi/2)` rotation followed by :math:`N` flips (two :math:`R_x(\pi)` rotations) and we measure the qubit state. The first :math:`R_x(\pi/2)` is necessary to discriminate the over rotations and under rotations of the :math:`R_x(\pi)` pulse: without it the difference between the two cases is just a global phase, i.e., the @@ -10,7 +10,11 @@ probabilities are the same. With the :math:`R_x(\pi/2)` pulse, in case of under after the initial flip, in the over rotations one the final state will be closer to :math:`\ket{1}`. By fitting the resulting data with a sinusoidal function, we can determine the delta amplitude, which allows us to refine the -:math:`\pi` pulse amplitue. +:math:`\pi` pulse amplitude. + +We implemented also a version of the flipping protocol to calibrate the drive pulse amplitude of the :math:`R_x(\pi/2)` rotations, +in this case each :math:`R_x(\pi)` rotation is replaced by two :math:`R_x(\pi/2)` rotations. +The main reasons for implementing protocols to fine tune the `R_x(\pi/2)` rotations are explained in :ref:`rabi`. Parameters ^^^^^^^^^^ @@ -24,30 +28,28 @@ It follows a runcard example of this experiment. .. code-block:: yaml - - id: flipping - operation: flipping - parameters: - detuning: 0.05 - nflips_max: 30 - nflips_step: 1 + - id: flipping + operation: flipping + parameters: + delta_amplitude: 0.05 + nflips_max: 30 + nflips_step: 1 The expected output is the following: .. image:: flipping.png -Qibocal provides also a "signal" version of this routine, it follows a possible runcard -with its report. +If the same experiment is run setting the `rx90: True` the flipping is performed to calibrate the amplitude of the :math:`R_x(\pi/2)` rotation .. code-block:: yaml - id: flipping - operation: flipping_signal + operation: flipping parameters: - detuning: -0.5 - nflips_max: 20 + delta_amplitude: 0.05 + nflips_max: 30 nflips_step: 1 - -.. image:: flipping_signal.png + rx90: True Requirements ^^^^^^^^^^^^ diff --git a/doc/source/protocols/flipping_signal.png b/doc/source/protocols/flipping_signal.png deleted file mode 100644 index 9427aa7fa..000000000 Binary files a/doc/source/protocols/flipping_signal.png and /dev/null differ diff --git a/doc/source/protocols/flux/crosstalk.rst b/doc/source/protocols/flux/crosstalk.rst index dc5226c58..32a1bbd6c 100644 --- a/doc/source/protocols/flux/crosstalk.rst +++ b/doc/source/protocols/flux/crosstalk.rst @@ -62,50 +62,3 @@ Requirements ^^^^^^^^^^^^ - :ref:`qubit_flux` - -.. _resonator_crosstalk: - -Resonator crosstalk -------------------- - -In a similar fashion it is possible to repeat the previous experiment -by sweeping the readout frequency. Note that in this case it will be -necessary to bias the qubit away from its sweetspot more to observe -significant variations. - -Parameters -^^^^^^^^^^ - -.. autoclass:: qibocal.protocols.flux_dependence.resonator_crosstalk.ResCrosstalkParameters - :noindex: - -Example -^^^^^^^ - -.. code-block:: yaml - - - id: resonator crosstalk - operation: resonator_crosstalk - targets: [2] - parameters: - bias_point: - 2: 0.5 - bias_step: 0.01 - bias_width: 0.4 - flux_qubits: [0, 3] - freq_step: 100000 - freq_width: 6000000 - nshots: 2000 - -.. image:: resonator_crosstalk.png - -As we can see, even by biasing the qubit away from its sweetspot we are not able to see -a dependence ( a deviation from the straight line) but only a shift. - -The protocols aims at extracting the crosstalk coefficients -:math:`C_{20}` and :math:`C_{23}`. - -Requirements -^^^^^^^^^^^^ - -- :ref:`resonator_flux` diff --git a/doc/source/protocols/flux/resonator_crosstalk.png b/doc/source/protocols/flux/resonator_crosstalk.png deleted file mode 100644 index 1024aaa93..000000000 Binary files a/doc/source/protocols/flux/resonator_crosstalk.png and /dev/null differ diff --git a/doc/source/protocols/flux/single.rst b/doc/source/protocols/flux/single.rst index 9e1746722..ce77c4219 100644 --- a/doc/source/protocols/flux/single.rst +++ b/doc/source/protocols/flux/single.rst @@ -127,12 +127,6 @@ A possible runcard to assess how the resonator frequency changes by varying flux relaxation_time: 1000 -From this protocol it is possible to extract both the bare and the dressed resonator frequency -as well as an estimate for the coupling :math:`g_0`. -It is suggested to run this protocol only after executing the qubit flux dependence experiment -since some of the coefficients required can be computed with that experiment. - - .. image:: resonator_flux.png Requirements @@ -140,41 +134,3 @@ Requirements - :ref:`resonator_punchout` - :ref:`qubit_flux` - -Qubit flux dependence (tracking) --------------------------------- - -As we saw above both the resonator and the qubit are affected by an external flux. -In the qubit flux dependence the measurement is performed at fixed readout frequency. -To take into account how the transmon shifts in frequency when probing the qubit we have -another experiment `qubit_flux_tracking`. - -Parameters -^^^^^^^^^^ - -.. autoclass:: qibocal.protocols.flux_dependence.qubit_flux_tracking.QubitFluxTrackParameters - :noindex: - -Example -^^^^^^^ - -Here is a possible runcard: - -.. code-block:: yaml - - - id: qubit flux dependence - operation: qubit_flux_tracking - parameters: - bias_step: 0.001 - bias_width: 0.05 - drive_amplitude: 0.002 - drive_duration: 4000 - freq_step: 200000 - freq_width: 10000000 - nshots: 1024 - relaxation_time: 20000 - -Requirements -^^^^^^^^^^^^ - -- :ref:`resonator_flux` diff --git a/doc/source/protocols/index.rst b/doc/source/protocols/index.rst index 565dc8293..6705a7215 100644 --- a/doc/source/protocols/index.rst +++ b/doc/source/protocols/index.rst @@ -1,3 +1,4 @@ +.. _calibration_routines: Protocols ========= @@ -21,18 +22,18 @@ In this section we introduce the basics of all protocols supported by ``qibocal` t1/t1 t2/t2 t2_echo/t2_echo + cpmg/cpmg flux/single flux/crosstalk singleshot dispersive_shift allxy flipping + drag/drag readout_mitigation_matrix - avoided_crossing readout_optimization standard_rb chevron virtual_z state_tomographies - coupler/chevron references diff --git a/doc/source/protocols/qubit_spectroscopy/qubit_spectroscopy.rst b/doc/source/protocols/qubit_spectroscopy/qubit_spectroscopy.rst index b891ed095..e81cb81ee 100644 --- a/doc/source/protocols/qubit_spectroscopy/qubit_spectroscopy.rst +++ b/doc/source/protocols/qubit_spectroscopy/qubit_spectroscopy.rst @@ -53,10 +53,6 @@ Here is the corresponding plot: To extract the qubit frequency a Lorentzian fit is performed. -After the post-processing the following parameters will be updated: - -* qubit.drive_frequency -* qubit.native_gates.RX.frequency Requirements ^^^^^^^^^^^^ diff --git a/doc/source/protocols/rabi/rabi.rst b/doc/source/protocols/rabi/rabi.rst index 5a3de5c1e..a1b096675 100644 --- a/doc/source/protocols/rabi/rabi.rst +++ b/doc/source/protocols/rabi/rabi.rst @@ -29,6 +29,17 @@ Rabi rate is larger than the decay and the pure dephasing rate, where :math:`\Omega_R` is the Rabi frequency and :math:`\tau` the decay time. + +Since many routines and protocols in quantum computing are based on `R_x(\pi/2)` rotations, in qibocal we implemented +also another version of the Rabi experiment which can be used to tune the amplitude (duration) of the drive pulse in order +to excite the qubit from the ground state up to state :math:`\frac{\ket{0}-i\ket{1}}{\sqrt{2}}`. + +The possibility to calibrate an `R_x(\pi/2)` rotation as native gate allows us to remove the errors that could arise from assuming that the `R_x(\pi/2)` amplitude (duration) +is exactly half that of the `R_x(\pi)` amplitude (duration). This assumption presumes a perfectly linear response of the qubit to the drive pulse, which is +often not the case due to nonlinearities in the qubit's response or imperfections in the pulse shaping :cite:p:`Chen2018MetrologyOQ`. + +In this case the pulse sequence is the same as before with the only difference that instead of a single `R_x(\pi)` pulse we use two concatenated `R_x(\pi/2)` pulses. + Parameters ^^^^^^^^^^ @@ -49,9 +60,9 @@ It follows an example of the experiment parameters. - id: Rabi amplitude operation: rabi_amplitude parameters: - min_amp_factor: 0.1 - max_amp_factor: 1. - step_amp_factor: 0.01 + min_amp: 0.1 + max_amp: 1. + step_amp: 0.01 pulse_length: 40 nshots: 3000 relaxation_time: 50000 @@ -94,15 +105,38 @@ It follows an example runcard and plot for the signal exepriment - id: Rabi signal operation: rabi_amplitude_signal parameters: - min_amp_factor: 0.2 - max_amp_factor: 1. - step_amp_factor: 0.01 + min_amp: 0.2 + max_amp: 1. + step_amp: 0.01 pulse_length: 40 nshots: 3000 relaxation_time: 50000 .. image:: rabi_signal.png +In all the previous examples we run Rabi experiments for calibrating the amplitude (duration) of the drive pulse +to excite the qubit from the ground state up to state :math:`\ket{1}`. +All these example runcards can be modified to calibrate the amplitude (duration) of the drive pulse +to excite the qubit from the ground state up to state :math:`\frac{\ket{0}-i\ket{1}}{\sqrt{2}}` by simply setting the `rx90` parameter to `True`. + +In the following we show an example runcard for the amplitude calibration of the `R_x(\pi/2)`. + +.. code-block:: yaml + + + - id: Rabi signal + operation: rabi_amplitude_signal + parameters: + min_amp: 0.01 + max_amp: 0.16 + step_amp: 0.002 + pulse_length: 40 + nshots: 1024 + relaxation_time: 50000 + rx90: True + +.. image:: rabi_amplitude_rx90 + Requirements ^^^^^^^^^^^^ - :ref:`qubit-spectroscopy` @@ -125,9 +159,9 @@ It follows an example of runcard and a generated report. - id: Rabi ef operation: rabi_amplitude_ef parameters: - min_amp_factor: 0.2 - max_amp_factor: 1. - step_amp_factor: 0.01 + min_amp: 0.2 + max_amp: 1. + step_amp: 0.01 pulse_length: 400 nshots: 3000 relaxation_time: 50000 diff --git a/doc/source/protocols/rabi/rabi_amplitude_rx90.png b/doc/source/protocols/rabi/rabi_amplitude_rx90.png new file mode 100644 index 000000000..ac6c53ebd Binary files /dev/null and b/doc/source/protocols/rabi/rabi_amplitude_rx90.png differ diff --git a/doc/source/protocols/resonator_punchout.rst b/doc/source/protocols/resonator_punchout.rst index f910667e3..9c6bc1c76 100644 --- a/doc/source/protocols/resonator_punchout.rst +++ b/doc/source/protocols/resonator_punchout.rst @@ -36,10 +36,9 @@ Example parameters: freq_width: 40_000_000 freq_step: 500_000 - amplitude: 0.03 - min_amp_factor: 0.1 - max_amp_factor: 2.4 - step_amp_factor: 0.3 + min_amp: 0.1 + max_amp: 2.4 + step_amp: 0.3 nshots: 2048 relaxation_time: 5000 @@ -106,35 +105,6 @@ approximate value, that can later be used to check, in other experiments, that w not exciting the qubit by error (if we see a change in amplitude, then maybe the qubit state has changed). -It is also possible to run the punchout experiment with attenuation: - -Parameters -^^^^^^^^^^ - -.. autoclass:: qibocal.protocols.resonator_punchout_attenuation.ResonatorPunchoutAttenuationParameters - :noindex: - -Example -^^^^^^^ - -.. code-block:: yaml - - - id: resonator_punchout_attenuation - - operation: resonator_punchout_attenuation - parameters: - freq_width: 10_000_000 - freq_step: 500_000 - max_att: 60 - min_att: 4 - nshots: 1000 - step_att: 4 - nshots: 2048 - -.. image:: resonator_punchout_attenuation.png - -Requirements -^^^^^^^^^^^^ - :ref:`Time Of Flight` - :ref:`resonator_spectroscopy` (high power) diff --git a/doc/source/protocols/resonator_punchout_attenuation.png b/doc/source/protocols/resonator_punchout_attenuation.png deleted file mode 100644 index 6a0579599..000000000 Binary files a/doc/source/protocols/resonator_punchout_attenuation.png and /dev/null differ diff --git a/doc/source/protocols/signal/time_of_flight.rst b/doc/source/protocols/signal/time_of_flight.rst index 0d2561b60..8fc93c626 100644 --- a/doc/source/protocols/signal/time_of_flight.rst +++ b/doc/source/protocols/signal/time_of_flight.rst @@ -37,7 +37,7 @@ Acquisition .. testcode:: :hide: - from qibolab.execution_parameters import AcquisitionType + from qibolab import AcquisitionType It is important to note that this experiment makes use of the RAW acquisition mode (see `Qibolab documentation `_), which may require some specific care depending on the instrument employed (for some devices demodulation could be used, or this mode could be available for just a single qubit at a time). diff --git a/doc/source/protocols/t1/t1.rst b/doc/source/protocols/t1/t1.rst index b051c26ba..28c6ccb31 100644 --- a/doc/source/protocols/t1/t1.rst +++ b/doc/source/protocols/t1/t1.rst @@ -99,36 +99,3 @@ Requirements ^^^^^^^^^^^^ - :ref:`rabi` - -T1 with for loops ------------------ - -If the instrument driver is not able to perform duration sweepers in real time, we provide -a protocol where the different waiting time are swept through a python for loop. Such -execution will be usually slower compared to the one where sweepers are supported but it -could be useful for debugging purposes. - - -Here is a possible runcard: - -.. code-block:: yaml - - - id: T1 with for loops - operation: t1_sequences - parameters: - delay_before_readout_end: 100008 - delay_before_readout_start: 16 - delay_before_readout_step: 1000 - nshots: 2048 - - -.. note:: - - For ``t1_sequences`` on the y-axis it will be shown the raw output from instruments, - not the population of :math:`\ket{1}`. - - -Requirements -^^^^^^^^^^^^ - -- :ref:`rabi` diff --git a/doc/source/protocols/t2/t2.rst b/doc/source/protocols/t2/t2.rst index 92da06b35..32c7bc694 100644 --- a/doc/source/protocols/t2/t2.rst +++ b/doc/source/protocols/t2/t2.rst @@ -93,30 +93,3 @@ Requirements ^^^^^^^^^^^^ - :ref:`rabi` - -T2 with for loops ------------------ - -If the instrument driver is not able to perform duration sweepers in real time, we provide -a protocol where the different waiting time are swept through a python for loop. Such -execution will be usually slower compared to the one where sweepers are supported but it -could be useful for debugging purposes. - -Here is a possible runcard: - -.. code-block:: yaml - - - id: T2 with for loops - operation: t2_sequences - parameters: - delay_between_pulses_end: 200000 - delay_between_pulses_start: 4 - delay_between_pulses_step: 4000 - nshots: 5000 - relaxation_time: 300000 - - -.. note:: - - For ``t2_sequences`` on the y-axis it will be shown the raw output from instruments, - not the population of :math:`\ket{1}`. diff --git a/doc/source/refs.bib b/doc/source/refs.bib index b971ff08d..a6fb06f20 100644 --- a/doc/source/refs.bib +++ b/doc/source/refs.bib @@ -190,3 +190,53 @@ @article{Nielsen_2002 author={Nielsen, Michael A}, year={2002}, month=oct, pages={249–252} } + +@article{Motzoi_2009, + title={Simple Pulses for Elimination of Leakage in Weakly Nonlinear Qubits}, + volume={103}, + ISSN={1079-7114}, + url={http://dx.doi.org/10.1103/PhysRevLett.103.110501}, + DOI={10.1103/physrevlett.103.110501}, + number={11}, + journal={Physical Review Letters}, + publisher={American Physical Society (APS)}, + author={Motzoi, F. and Gambetta, J. M. and Rebentrost, P. and Wilhelm, F. K.}, + year={2009}, + month=sep } + + +@article{Gambetta_2011, + title={Analytic control methods for high-fidelity unitary operations in a weakly nonlinear oscillator}, + volume={83}, + ISSN={1094-1622}, + url={http://dx.doi.org/10.1103/PhysRevA.83.012308}, + DOI={10.1103/physreva.83.012308}, + number={1}, + journal={Physical Review A}, + publisher={American Physical Society (APS)}, + author={Gambetta, J. M. and Motzoi, F. and Merkel, S. T. and Wilhelm, F. K.}, + year={2011}, + month=jan } + +@article{Sheldon_2016, + title={Characterizing errors on qubit operations via iterative randomized benchmarking}, + volume={93}, + ISSN={2469-9934}, + url={http://dx.doi.org/10.1103/PhysRevA.93.012301}, + DOI={10.1103/physreva.93.012301}, + number={1}, + journal={Physical Review A}, + publisher={American Physical Society (APS)}, + author={Sheldon, Sarah and Bishop, Lev S. and Magesan, Easwar and Filipp, Stefan and Chow, Jerry M. and Gambetta, Jay M.}, + year={2016}, + month=jan } + +@misc{reed2013entanglementquantumerrorcorrection, + title={Entanglement and Quantum Error Correction with Superconducting Qubits}, + author={Matthew Reed}, + year={2013}, + eprint={1311.6759}, + archivePrefix={arXiv}, + primaryClass={quant-ph}, + url={https://arxiv.org/abs/1311.6759}, +} diff --git a/doc/source/tutorials/advanced.rst b/doc/source/tutorials/advanced.rst index 45a43bdc1..ac150a88a 100644 --- a/doc/source/tutorials/advanced.rst +++ b/doc/source/tutorials/advanced.rst @@ -167,8 +167,8 @@ In the acquisition function we are going to perform the experiment. .. code-block:: python - from qibolab.platform import Platform - from qibolab.qubits import QubitId, QubitPairId + from qibolab import Platform + from qibocal.auto.operation import QubitId, QubitPairId from typing import Union def acquisition(params: RoutineParameters, platform: Platform, targets: Union[list[QubitId], list[QubitPairId], list[list[QubitId]]]) -> RoutineData @@ -177,8 +177,8 @@ In the acquisition function we are going to perform the experiment. .. code-block:: python - from qibolab.platform import Platform - from qibolab.qubits import QubitId + from qibolab import Platform + from qibocal.auto.operation import QubitId def acquisition( params: RotationParameters, @@ -229,7 +229,7 @@ parameters for each qubit. .. code-block:: python - from qibolab.qubits import QubitId + from qibocal.auto.operation import QubitId @dataclass class RotationResults(Results): @@ -321,7 +321,7 @@ Here is the plotting function for the protocol that we are coding: .. code-block:: python import plotly.graph_objects as go - from qibolab.qubits import QubitId + from qibocal.auto.operation import QubitId def plot(data: RotationData, fit: RotationResults, target: QubitId): """Plotting function for rotation.""" diff --git a/doc/source/tutorials/basic.rst b/doc/source/tutorials/basic.rst index 3f2fb1c4f..c6087b06f 100644 --- a/doc/source/tutorials/basic.rst +++ b/doc/source/tutorials/basic.rst @@ -56,7 +56,7 @@ user should make sure to specify an amplitude value sufficiently large. It is then possible to visualize a report included in the output folder. -.. image:: ../protocols/resonator_spectroscopy_high.png +.. image:: ../protocols/resonator_spectroscopy/resonator_spectroscopy_high.png The expected signal is a lorentzian centered around the bare frequency of the resonator. @@ -74,9 +74,9 @@ power we observe this shift it is possible to run a resonator punchout using the freq_width: 40_000_000 freq_step: 500_000 amplitude: 0.03 - min_amp_factor: 0.1 - max_amp_factor: 2.4 - step_amp_factor: 0.3 + min_amp: 0.1 + max_amp: 2.4 + step_amp: 0.3 nshots: 2048 relaxation_time: 5000 @@ -111,7 +111,7 @@ Note that in this case we changed the ``power_level`` entry from ``high`` to ``low``, this keyword is used by qibocal to upgrade correctly the QPU parameters depending on the power regime. -.. image:: ../protocols/resonator_spectroscopy_low.png +.. image:: ../protocols/resonator_spectroscopy/resonator_spectroscopy_low.png .. note:: @@ -180,9 +180,9 @@ the following runcard: operation: rabi_amplitude_signal parameters: - min_amp_factor: 0 - max_amp_factor: 1.1 - step_amp_factor: 0.1 + min_amp: 0 + max_amp: 1.1 + step_amp: 0.1 pulse_length: 40 relaxation_time: 100_000 nshots: 1024 @@ -191,7 +191,7 @@ In this particular case we are fixing the duration of the pulse to be 40 ns and a sweep in the drive amplitude to find the correct value. The :math:`\pi` corresponds to first half period of the oscillation. -.. image:: ../protocols/rabi_amplitude.png +.. image:: ../protocols/rabi/rabi_amplitude.png Classification model ^^^^^^^^^^^^^^^^^^^^ diff --git a/poetry.lock b/poetry.lock index f3c4c42d5..5da4c7f29 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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index 518bb66b0..092388048 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -16,9 +16,9 @@ classifiers = [ [tool.poetry.dependencies] -python = ">=3.9,<3.12" -qibolab = "^0.1.8" -qibo = "^0.2.12" +python = ">=3.9,<3.13" +qibolab = "^0.2.3" +qibo = "^0.2.13" numpy = "^1.26.4" scipy = "^1.10.1" pandas = { version = "^2.2.2", extras = ["html"] } @@ -27,7 +27,7 @@ click = "^8.1.3" jinja2 = "^3.1.2" plotly = "^5.22.0" dash = "^2.6.0" -skops = "^0.10.0" +skops = "^0.11.0" matplotlib = { version = "^3.7.0", optional = true } seaborn = { version = "^0.12.2", optional = true } pydot = { version = "^1.4.2", optional = true } @@ -84,6 +84,7 @@ docs-clean = "make -C doc clean" test-docs = "make -C doc doctest" [tool.pytest.ini_options] +env = ["QIBO_PLATFORM = dummy"] testpaths = ['tests/'] addopts = ['--cov=qibocal', '--cov-report=xml', '--cov-report=html'] diff --git a/src/qibocal/auto/execute.py b/src/qibocal/auto/execute.py index a7fa2a9b9..1b61e0e27 100644 --- a/src/qibocal/auto/execute.py +++ b/src/qibocal/auto/execute.py @@ -11,12 +11,11 @@ from typing import Optional, Union from qibo.backends import construct_backend -from qibolab import create_platform -from qibolab.platform import Platform from qibocal import protocols from qibocal.config import log +from ..calibration import CalibrationPlatform, create_calibration_platform from .history import History from .mode import AUTOCALIBRATION, ExecutionMode from .operation import Routine @@ -72,7 +71,7 @@ class Executor: """The execution history, with results and exit states.""" targets: Targets """Qubits/Qubit Pairs to be calibrated.""" - platform: Platform + platform: CalibrationPlatform """Qubits' platform.""" update: bool = True """Runcard update mechanism.""" @@ -99,12 +98,14 @@ def __post_init__(self): _register(self.name, self) @classmethod - def create(cls, name: str, platform: Union[Platform, str, None] = None): + def create(cls, name: str, platform: Union[CalibrationPlatform, str, None] = None): """Load list of protocols.""" platform = ( platform - if isinstance(platform, Platform) - else create_platform(platform if platform is not None else "dummy") + if isinstance(platform, CalibrationPlatform) + else create_calibration_platform( + platform if platform is not None else "dummy" + ) ) return cls( name=name, @@ -248,17 +249,21 @@ def init( self, path: os.PathLike, force: bool = False, - platform: Union[Platform, str, None] = None, + platform: Union[CalibrationPlatform, str, None] = None, update: Optional[bool] = None, targets: Optional[Targets] = None, ): """Initialize execution.""" - if platform is None: + if platform is None or isinstance(platform, CalibrationPlatform): platform = self.platform + elif isinstance(platform, str): + platform = self.platform = create_calibration_platform(platform) + else: + platform = self.platform = CalibrationPlatform.from_platform(platform) + + assert isinstance(platform, CalibrationPlatform) - backend = construct_backend(backend="qibolab", platform=platform) - platform = self.platform = backend.platform - assert isinstance(platform, Platform) + backend = construct_backend(backend="qibolab", platform=platform.name) if update is not None: self.update = update @@ -307,7 +312,7 @@ def open( name: str, path: os.PathLike, force: bool = False, - platform: Union[Platform, str, None] = None, + platform: Union[CalibrationPlatform, str, None] = None, update: Optional[bool] = None, targets: Optional[Targets] = None, ): diff --git a/src/qibocal/auto/history.py b/src/qibocal/auto/history.py index c5db3745d..e0496e836 100644 --- a/src/qibocal/auto/history.py +++ b/src/qibocal/auto/history.py @@ -87,7 +87,7 @@ def route(task_id: TaskId, folder: Path) -> Path: """Determine the path related to a completed task given TaskId. `folder` should be usually the general output folder, used by Qibocal to store - all the execution results. Cf. :cls:`qibocal.auto.output.Output`. + all the execution results. Cf. :class:`qibocal.auto.output.Output`. """ return folder / "data" / f"{task_id}" @@ -95,7 +95,7 @@ def flush(self, output: Optional[Path] = None): """Flush all content to disk. Specifying `output` is possible to select which folder should be considered as - the general Qibocal output folder. Cf. :cls:`qibocal.auto.output.Output`. + the general Qibocal output folder. Cf. :class:`qibocal.auto.output.Output`. """ for task_id, completed in self.items(): if output is not None: diff --git a/src/qibocal/auto/operation.py b/src/qibocal/auto/operation.py index 8b1f602eb..51aa98cec 100644 --- a/src/qibocal/auto/operation.py +++ b/src/qibocal/auto/operation.py @@ -9,12 +9,11 @@ import numpy as np import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import Qubit, QubitId, QubitPair, QubitPairId +from qibolab import AcquisitionType, AveragingMode, Platform, Qubit from qibocal.config import log +from ..calibration.calibration import QubitId, QubitPairId from .serialize import deserialize, load, serialize OperationId = NewType("OperationId", str) @@ -23,7 +22,6 @@ """Valid value for a routine and runcard parameter.""" Qubits = dict[QubitId, Qubit] """Convenient way of passing qubit pairs in the routines.""" -QubitsPairs = dict[tuple[QubitId, QubitId], QubitPair] DATAFILE = "data" @@ -112,7 +110,7 @@ def execution_parameters(self): if self.classify else AcquisitionType.INTEGRATION ) - return ExecutionParameters( + return dict( nshots=self.nshots, relaxation_time=self.relaxation_time, acquisition_type=acquisition_type, diff --git a/src/qibocal/auto/output.py b/src/qibocal/auto/output.py index 275c4cfd8..0f716b93d 100644 --- a/src/qibocal/auto/output.py +++ b/src/qibocal/auto/output.py @@ -7,9 +7,8 @@ from typing import Optional from qibo.backends import construct_backend -from qibolab import Platform -from qibolab.serialize import dump_platform +from ..calibration import CalibrationPlatform from ..config import log from ..version import __version__ from .history import History @@ -155,7 +154,7 @@ class Output: history: History meta: Metadata - platform: Optional[Platform] = None + platform: Optional[CalibrationPlatform] = None @classmethod def load(cls, path: Path): @@ -202,7 +201,7 @@ def dump(self, path: Path): self.update_platform(self.platform, path) @staticmethod - def update_platform(platform: Platform, path: Path): + def update_platform(platform: CalibrationPlatform, path: Path): """Dump platform used. If the original one is not defined, use the current one as the @@ -213,7 +212,7 @@ def update_platform(platform: Platform, path: Path): platpath = path / UPDATED_PLATFORM platpath.mkdir(parents=True, exist_ok=True) - dump_platform(platform, platpath) + platform.dump(platpath) def _export_stats(self): """Export task statistics. @@ -234,9 +233,10 @@ def process( force: bool = False, ): """Process existing output.""" - self.platform = construct_backend( + backend = construct_backend( backend=self.meta.backend, platform=self.meta.platform - ).platform + ) + self.platform = CalibrationPlatform.from_platform(backend.platform) assert self.platform is not None for task_id, completed in self.history.items(): diff --git a/src/qibocal/auto/runcard.py b/src/qibocal/auto/runcard.py index ec56c2aa2..3bb4def52 100644 --- a/src/qibocal/auto/runcard.py +++ b/src/qibocal/auto/runcard.py @@ -6,7 +6,7 @@ import yaml from pydantic.dataclasses import dataclass -from qibolab.platform import Platform +from qibolab import Platform from .. import protocols from .execute import Executor diff --git a/src/qibocal/auto/task.py b/src/qibocal/auto/task.py index c8a07d9fc..7f5f4d003 100644 --- a/src/qibocal/auto/task.py +++ b/src/qibocal/auto/task.py @@ -8,8 +8,9 @@ import yaml from qibo import Circuit -from qibolab.platform import Platform -from qibolab.qubits import QubitId, QubitPairId +from qibolab import Platform + +from qibocal.auto.operation import QubitId, QubitPairId from .. import protocols from ..config import log diff --git a/src/qibocal/auto/transpile.py b/src/qibocal/auto/transpile.py index 6a34f942b..5cba73abf 100644 --- a/src/qibocal/auto/transpile.py +++ b/src/qibocal/auto/transpile.py @@ -4,9 +4,11 @@ from qibo.backends import Backend from qibo.transpiler.pipeline import Passes from qibo.transpiler.unroller import NativeGates, Unroller -from qibolab.compilers.compiler import Compiler -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import PulseSequence +from qibolab._core.compilers import Compiler +from qibolab._core.native import NativeContainer + +from qibocal.auto.operation import QubitId REPLACEMENTS = { "RX": "GPI2", @@ -109,32 +111,35 @@ def execute_transpiled_circuit( ) -def natives(platform): +def natives(platform) -> dict[str, NativeContainer]: """ - Return the list of native gates defined in the `platform`. - This function assumes the native gates to be the same for each + Return the dict of native gates name with the associated native container + defined in the `platform`. This function assumes the native gates to be the same for each qubit and pair. """ - pair = next(iter(platform.pairs.values())) - qubit = next(iter(platform.qubits.values())) - two_qubit_natives = list(pair.native_gates.raw) - single_qubit_natives = list(qubit.native_gates.raw) + pair = next(iter(platform.pairs)) + qubit = next(iter(platform.qubits)) + two_qubit_natives_container = platform.natives.two_qubit[pair] + single_qubit_natives_container = platform.natives.single_qubit[qubit] + single_qubit_natives = list(single_qubit_natives_container.model_fields) + two_qubit_natives = list(two_qubit_natives_container.model_fields) # Solve Qibo-Qibolab mismatch single_qubit_natives.append("RZ") single_qubit_natives.append("Z") single_qubit_natives.remove("RX12") - new_single_natives = [REPLACEMENTS.get(i, i) for i in single_qubit_natives] - return new_single_natives + two_qubit_natives + single_qubit_natives.remove("RX90") + single_qubit_natives.remove("CP") + single_qubit_natives = [REPLACEMENTS.get(x, x) for x in single_qubit_natives] + return {i: platform.natives.single_qubit[qubit] for i in single_qubit_natives} | { + i: platform.natives.two_qubit[pair] for i in two_qubit_natives + } -def create_rule(native): - def rule(qubits_ids, platform, parameters=None): - if len(qubits_ids[1]) == 1: - native_gate = platform.qubits[tuple(qubits_ids[1])].native_gates - else: - native_gate = platform.pairs[tuple(qubits_ids[1])].native_gates - pulses = getattr(native_gate, native).pulses - return PulseSequence(pulses), {} +def create_rule(name, natives): + """Create rule for gate name given container natives.""" + + def rule(gate: gates.Gate, natives: NativeContainer) -> PulseSequence: + return natives.ensure(name).create_sequence() return rule @@ -145,10 +150,10 @@ def set_compiler(backend, natives_): """ compiler = backend.compiler rules = {} - for native in natives_: - gate = getattr(gates, native) + for name, natives_container in natives_.items(): + gate = getattr(gates, name) if gate not in compiler.rules: - rules[gate] = create_rule(native) + rules[gate] = create_rule(name, natives_container) else: rules[gate] = compiler.rules[gate] rules[gates.I] = compiler.rules[gates.I] @@ -167,7 +172,7 @@ def dummy_transpiler(backend: Backend) -> Passes: set_compiler(backend, native_gates) native_gates = [getattr(gates, x) for x in native_gates] unroller = Unroller(NativeGates.from_gatelist(native_gates)) - return Passes(connectivity=platform.topology, passes=[unroller]) + return Passes(connectivity=platform.pairs, passes=[unroller]) def pad_circuit(nqubits, circuit: Circuit, qubit_map: list[int]) -> Circuit: diff --git a/src/qibocal/calibration/__init__.py b/src/qibocal/calibration/__init__.py new file mode 100644 index 000000000..fc3d1d777 --- /dev/null +++ b/src/qibocal/calibration/__init__.py @@ -0,0 +1 @@ +from .platform import CalibrationPlatform, create_calibration_platform diff --git a/src/qibocal/calibration/calibration.py b/src/qibocal/calibration/calibration.py new file mode 100644 index 000000000..b2e463077 --- /dev/null +++ b/src/qibocal/calibration/calibration.py @@ -0,0 +1,185 @@ +from pathlib import Path +from typing import Annotated, Optional, Union + +import numpy as np +from pydantic import BaseModel, BeforeValidator, ConfigDict, Field, PlainSerializer + +from .serialize import NdArray, SparseArray + +QubitId = Annotated[Union[int, str], Field(union_mode="left_to_right")] +"""Qubit name.""" + +QubitPairId = Annotated[ + tuple[QubitId, QubitId], + BeforeValidator(lambda p: tuple(p.split("-")) if isinstance(p, str) else p), + PlainSerializer(lambda p: f"{p[0]}-{p[1]}"), +] +"""Qubit pair name.""" + +CALIBRATION = "calibration.json" +"""Calibration file.""" + +Measure = tuple[float, Optional[float]] +"""Measured is represented as two values: mean and error.""" + + +class Model(BaseModel): + """Global model, holding common configurations.""" + + model_config = ConfigDict(extra="forbid") + + +class Resonator(Model): + """Representation of resonator parameters.""" + + bare_frequency: Optional[float] = None + """Bare resonator frequency [Hz].""" + dressed_frequency: Optional[float] = None + """Dressed resonator frequency [Hz].""" + depletion_time: Optional[int] = None + """Depletion time [ns].""" + + @property + def dispersive_shift(self): + """Dispersive shift.""" + return self.bare_frequency - self.dressed_frequency + + # TODO: Add setter for dispersive shift as well + # TODO: Add something related to resonator calibration + + +class Qubit(Model): + """Representation of Qubit parameters""" + + frequency_01: Optional[float] = None + """"0->1 transition frequency [Hz].""" + frequency_12: Optional[float] = None + """1->2 transition frequency [Hz].""" + maximum_frequency: Optional[float] = None + """Maximum transition frequency [Hz].""" + asymmetry: Optional[float] = None + """Junctions asymmetry.""" + sweetspot: Optional[float] = None + """Qubit sweetspot [V].""" + + @property + def anharmonicity(self): + """Anharmonicity of the qubit [Hz].""" + if self.frequency_12 is None: + return 0 + return self.frequency_12 - self.frequency_01 + + @property + def charging_energy(self): + """Charging energy Ec [Hz].""" + return -self.anharmonicity + + @property + def josephson_energy(self): + """Josephson energy [Hz]. + + The following formula is the inversion of the maximum frequency + obtained from the flux dependence protoco. + + """ + return ( + (self.maximum_frequency + self.charging_energy) ** 2 + / 8 + / self.charging_energy + ) + + +class Readout(Model): + """Readout parameters.""" + + fidelity: Optional[float] = None + """Readout fidelity.""" + coupling: Optional[float] = None + """Readout coupling [Hz].""" + effective_temperature: Optional[float] = None + """Qubit effective temperature.""" + ground_state: list[float] = Field(default_factory=list) + """Ground state position in IQ plane.""" + excited_state: list[float] = Field(default_factory=list) + """Excited state position in IQ plane.""" + qudits_frequency: dict[int, float] = Field(default_factory=dict) + """Dictionary mapping state with readout frequency.""" + + @property + def assignment_fidelity(self): + """Assignment fidelity.""" + return (1 + self.fidelity) / 2 + + +class QubitCalibration(Model): + """Container for calibration of single qubit.""" + + resonator: Resonator = Field(default_factory=Resonator) + """Resonator calibration.""" + qubit: Qubit = Field(default_factory=Qubit) + """Qubit calibration.""" + readout: Readout = Field(default_factory=Readout) + """Readout information.""" + t1: Optional[Measure] = None + """Relaxation time [ns].""" + t2: Optional[Measure] = None + """T2 of the qubit [ns].""" + t2_spin_echo: Optional[Measure] = None + """T2 hanh echo [ns].""" + rb_fidelity: Optional[Measure] = None + """Standard rb pulse fidelity.""" + + +class TwoQubitCalibration(Model): + """Container for calibration of qubit pair.""" + + rb_fidelity: Optional[Measure] = None + """Two qubit standard rb fidelity.""" + cz_fidelity: Optional[Measure] = None + """CZ interleaved rb fidelity.""" + coupling: Optional[float] = None + """Qubit-qubit coupling.""" + + +class Calibration(Model): + """Calibration container.""" + + single_qubits: dict[QubitId, QubitCalibration] = Field(default_factory=dict) + """Dict with single qubit calibration.""" + two_qubits: dict[QubitPairId, TwoQubitCalibration] = Field(default_factory=dict) + """Dict with qubit pairs calibration.""" + readout_mitigation_matrix: Optional[SparseArray] = None + """Readout mitigation matrix.""" + flux_crosstalk_matrix: Optional[NdArray] = None + """Crosstalk flux matrix.""" + + def dump(self, path: Path): + """Dump calibration model.""" + (path / CALIBRATION).write_text(self.model_dump_json(indent=4)) + + @property + def qubits(self) -> list: + """List of qubits available in the model.""" + return list(self.single_qubits) + + @property + def nqubits(self) -> int: + """Number of qubits available.""" + return len(self.qubits) + + def qubit_index(self, qubit: QubitId): + """Return qubit index from platform qubits.""" + return self.qubits.index(qubit) + + # TODO: add crosstalk object where I can do this + def get_crosstalk_element(self, qubit1: QubitId, qubit2: QubitId): + if self.flux_crosstalk_matrix is None: + self.flux_crosstalk_matrix = np.zeros((self.nqubits, self.nqubits)) + a, b = self.qubit_index(qubit1), self.qubit_index(qubit2) + return self.flux_crosstalk_matrix[a, b] # pylint: disable=E1136 + + def set_crosstalk_element(self, qubit1: QubitId, qubit2: QubitId, value: float): + if self.flux_crosstalk_matrix is None: + self.flux_crosstalk_matrix = np.zeros((self.nqubits, self.nqubits)) + a, b = self.qubit_index(qubit1), self.qubit_index(qubit2) + self.flux_crosstalk_matrix[a, b] = value # pylint: disable=E1137 diff --git a/src/qibocal/calibration/dummy.json b/src/qibocal/calibration/dummy.json new file mode 100644 index 000000000..6aabbd896 --- /dev/null +++ b/src/qibocal/calibration/dummy.json @@ -0,0 +1,139 @@ +{ + "single_qubits": { + "0": { + "resonator": { + "bare_frequency": 0.0, + "dressed_frequency": 5200000000.0, + "depletion_time": 0 + }, + "qubit": { + "frequency_01": 4000000000.0, + "frequency_12": 4700000000.0, + "maximum_frequency": 4000000000.0, + "asymmetry": 0.0, + "sweetspot": 0.0 + }, + "readout": { + "fidelity": 0.0, + "ground_state": [ + 0.0, + 1.0 + ], + "excited_state": [ + 1.0, + 0.0 + ] + }, + "rb_fidelity": null + }, + "1": { + "resonator": { + "bare_frequency": 0.0, + "dressed_frequency": 4900000000.0, + "depletion_time": 0 + }, + "qubit": { + "frequency_01": 4200000000.0, + "frequency_12": 4855663000.0, + "maximum_frequency": 4000000000.0, + "asymmetry": 0.0, + "sweetspot": 0.0 + }, + "readout": { + "fidelity": 0.0, + "ground_state": [ + 0.25, + 0.0 + ], + "excited_state": [ + 0.0, + 0.25 + ] + }, + "rb_fidelity": null + }, + "2": { + "resonator": { + "bare_frequency": 0.0, + "dressed_frequency": 6100000000.0, + "depletion_time": 0 + }, + "qubit": { + "frequency_01": 4500000000.0, + "frequency_12": 2700000000.0, + "maximum_frequency": 4000000000.0, + "asymmetry": 0.0, + "sweetspot": 0.0 + }, + "readout": { + "fidelity": 0.0, + "ground_state": [ + 0.5, + 0.0 + ], + "excited_state": [ + 0.0, + 0.5 + ] + }, + "rb_fidelity": null + }, + "3": { + "resonator": { + "bare_frequency": 0.0, + "dressed_frequency": 5800000000.0, + "depletion_time": 0 + }, + "qubit": { + "frequency_01": 4150000000.0, + "frequency_12": 5855663000.0, + "maximum_frequency": 4000000000.0, + "asymmetry": 0.0, + "sweetspot": 0.0 + }, + "readout": { + "fidelity": 0.0, + "ground_state": [ + 0.75, + 0.0 + ], + "excited_state": [ + 0.0, + 0.75 + ] + }, + "rb_fidelity": null + }, + "4": { + "resonator": { + "bare_frequency": 0.0, + "dressed_frequency": 5500000000.0, + "depletion_time": 0 + }, + "qubit": { + "frequency_01": 4100000000.0, + "frequency_12": 5855663000.0, + "maximum_frequency": 4000000000.0, + "asymmetry": 0.0, + "sweetspot": 0.0 + }, + "readout": { + "fidelity": 0.0, + "ground_state": [ + 1.0, + 0.0 + ], + "excited_state": [ + 0.0, + 1.0 + ] + }, + "rb_fidelity": null + } + }, + "two_qubits": { + "1-2": { + "rb_fidelity": [0.99, 0.01] + } + } +} diff --git a/src/qibocal/calibration/platform.py b/src/qibocal/calibration/platform.py new file mode 100644 index 000000000..5a5e94e4f --- /dev/null +++ b/src/qibocal/calibration/platform.py @@ -0,0 +1,38 @@ +from dataclasses import dataclass +from pathlib import Path + +from qibolab import Platform, create_platform, locate_platform + +from .calibration import CALIBRATION, Calibration + + +@dataclass +class CalibrationPlatform(Platform): + """Qibolab platform with calibration information.""" + + calibration: Calibration = None + """Calibration information.""" + + @classmethod + def from_platform(cls, platform: Platform): + name = platform.name + if name == "dummy": + calibration = Calibration.model_validate_json( + (Path(__file__).parent / "dummy.json").read_text() + ) + else: # pragma: no cover + path = locate_platform(name) + calibration = Calibration.model_validate_json( + (path / CALIBRATION).read_text() + ) + # TODO: this is loading twice a platform + return cls(**vars(platform), calibration=calibration) + + def dump(self, path: Path): + super().dump(path) + self.calibration.dump(path) + + +def create_calibration_platform(name: str) -> CalibrationPlatform: + platform = create_platform(name) + return CalibrationPlatform.from_platform(platform) diff --git a/src/qibocal/calibration/serialize.py b/src/qibocal/calibration/serialize.py new file mode 100644 index 000000000..083436c00 --- /dev/null +++ b/src/qibocal/calibration/serialize.py @@ -0,0 +1,63 @@ +import base64 +import io +from typing import Annotated, Optional, Union + +import numpy as np +import numpy.typing as npt +from pydantic import PlainSerializer, PlainValidator +from scipy.sparse import csr_matrix, lil_matrix + + +# TODO: add tests about this +def sparse_serialize(matrix: lil_matrix) -> str: + """Serialize a lil_matrix to a base64 string.""" + csr_matrix = matrix.tocsr() + buffer = io.BytesIO() + np.save(buffer, csr_matrix.shape) + np.save(buffer, csr_matrix.data) + np.save(buffer, csr_matrix.indices) + np.save(buffer, csr_matrix.indptr) + buffer.seek(0) + return base64.standard_b64encode(buffer.read()).decode() + + +def sparse_deserialize(data: str) -> Optional[lil_matrix]: + """Deserialize a base64 string back into a lil_matrix.""" + buffer = io.BytesIO(base64.standard_b64decode(data)) + shape = np.load(buffer, allow_pickle=True) + data_array = np.load(buffer, allow_pickle=True) + indices_array = np.load(buffer, allow_pickle=True) + indptr_array = np.load(buffer, allow_pickle=True) + csr = csr_matrix((data_array, indices_array, indptr_array), shape=shape) + return lil_matrix(csr) + + +SparseArray = Annotated[ + lil_matrix, + PlainValidator(sparse_deserialize), + PlainSerializer(sparse_serialize, return_type=str), +] + + +def ndarray_serialize(ar: npt.NDArray) -> str: + """Serialize array to string.""" + buffer = io.BytesIO() + np.save(buffer, ar) + buffer.seek(0) + return base64.standard_b64encode(buffer.read()).decode() + + +def ndarray_deserialize(x: Union[str, npt.NDArray]) -> npt.NDArray: + """Deserialize array.""" + buffer = io.BytesIO() + buffer.write(base64.standard_b64decode(x)) + buffer.seek(0) + return np.load(buffer) + + +NdArray = Annotated[ + npt.NDArray, + PlainValidator(ndarray_deserialize), + PlainSerializer(ndarray_serialize, return_type=str), +] +"""Pydantic-compatible array representation.""" diff --git a/src/qibocal/cli/acquisition.py b/src/qibocal/cli/acquisition.py index dd8aa9285..956f553c9 100644 --- a/src/qibocal/cli/acquisition.py +++ b/src/qibocal/cli/acquisition.py @@ -6,6 +6,7 @@ from ..auto.mode import ExecutionMode from ..auto.output import Metadata, Output from ..auto.runcard import Runcard +from ..calibration import CalibrationPlatform def acquire(runcard: Runcard, folder: Path, force: bool): @@ -17,7 +18,7 @@ def acquire(runcard: Runcard, folder: Path, force: bool): """ # rename for brevity backend = construct_backend(backend=runcard.backend, platform=runcard.platform) - platform = backend.platform + platform = CalibrationPlatform.from_platform(backend.platform) if platform is None: raise ValueError("Qibocal requires a Qibolab platform to run.") diff --git a/src/qibocal/cli/report.py b/src/qibocal/cli/report.py index b6c4e6e20..edbfce5ba 100644 --- a/src/qibocal/cli/report.py +++ b/src/qibocal/cli/report.py @@ -4,13 +4,20 @@ import plotly.graph_objects as go from jinja2 import Environment, FileSystemLoader -from qibolab.qubits import QubitId, QubitPairId from qibocal.auto.history import History +from qibocal.auto.operation import QubitId, QubitPairId from qibocal.auto.output import Output from qibocal.auto.task import Completed from qibocal.config import log -from qibocal.web.report import STYLES, TEMPLATES, Report, report_css_styles +from qibocal.web.report import ( + SCRIPT, + STYLES, + TEMPLATES, + Report, + report_css_styles, + report_script, +) ReportOutcome = tuple[str, list[go.Figure]] """Report produced by protocol.""" @@ -24,6 +31,10 @@ def generate_figures_and_report( It operates on a completed `node` and a specific protocol `target`, generating a report outcome (cf. `ReportOutcome`). """ + # TODO: remove temporary fix + if isinstance(target, list): + target = tuple(target) + if node.results is None: # plot acquisition data return node.task.operation.report(data=node.data, fit=None, target=target) @@ -75,6 +86,7 @@ def report(path: pathlib.Path, history: Optional[History] = None): html = template.render( is_static=True, css_styles=report_css_styles(STYLES), + js_script=report_script(SCRIPT), path=path, title=path.name, report=Report( diff --git a/src/qibocal/cli/run.py b/src/qibocal/cli/run.py index 5edc9e46f..ae7fbf658 100644 --- a/src/qibocal/cli/run.py +++ b/src/qibocal/cli/run.py @@ -6,6 +6,7 @@ from ..auto.mode import AUTOCALIBRATION from ..auto.output import Metadata, Output from ..auto.runcard import Runcard +from ..calibration import CalibrationPlatform from .report import report @@ -18,7 +19,8 @@ def protocols_execution(runcard: Runcard, folder: Path, force, update): """ # rename for brevity backend = construct_backend(backend=runcard.backend, platform=runcard.platform) - platform = backend.platform + platform = CalibrationPlatform.from_platform(backend.platform) + if platform is None: raise ValueError("Qibocal requires a Qibolab platform to run.") diff --git a/src/qibocal/cli/update.py b/src/qibocal/cli/update.py index 9d57929fe..f4ccd3124 100644 --- a/src/qibocal/cli/update.py +++ b/src/qibocal/cli/update.py @@ -3,6 +3,8 @@ import pathlib import shutil +from qibolab import locate_platform + from ..auto.output import META, UPDATED_PLATFORM from ..config import log, raise_error @@ -18,7 +20,7 @@ def update(path: pathlib.Path): raise_error(FileNotFoundError, f"No updated runcard platform found in {path}.") platform_name = json.loads((path / META).read_text())["platform"] - platform_path = pathlib.Path(os.getenv("QIBOLAB_PLATFORMS")) / platform_name + platform_path = locate_platform(platform_name) for filename in os.listdir(new_platform_path): shutil.copy( diff --git a/src/qibocal/fitting/classifier/run.py b/src/qibocal/fitting/classifier/run.py index cf962085f..daefd2ccc 100644 --- a/src/qibocal/fitting/classifier/run.py +++ b/src/qibocal/fitting/classifier/run.py @@ -8,9 +8,10 @@ import numpy as np import pandas as pd -from qibolab.qubits import QubitId from sklearn.metrics import accuracy_score +from qibocal.auto.operation import QubitId + from . import data CLS_MODULES = [ diff --git a/src/qibocal/protocols/__init__.py b/src/qibocal/protocols/__init__.py index 7d420e9f3..77284fec9 100644 --- a/src/qibocal/protocols/__init__.py +++ b/src/qibocal/protocols/__init__.py @@ -1,31 +1,23 @@ from enum import Enum from .allxy.allxy import allxy +from .allxy.allxy_resonator_depletion_tuning import allxy_resonator_depletion_tuning from .classification import single_shot_classification +from .coherence.cpmg import cpmg from .coherence.spin_echo import spin_echo from .coherence.spin_echo_signal import spin_echo_signal from .coherence.t1 import t1 -from .coherence.t1_sequences import t1_sequences from .coherence.t1_signal import t1_signal from .coherence.t2 import t2 -from .coherence.t2_sequences import t2_sequences from .coherence.t2_signal import t2_signal from .coherence.zeno import zeno -from .coherence.zeno_signal import zeno_signal -from .couplers.coupler_chevron import coupler_chevron -from .couplers.coupler_qubit_spectroscopy import coupler_qubit_spectroscopy -from .couplers.coupler_resonator_spectroscopy import coupler_resonator_spectroscopy from .dispersive_shift import dispersive_shift from .dispersive_shift_qutrit import dispersive_shift_qutrit from .drag import drag_tuning -from .fast_reset.fast_reset import fast_reset +from .drag_simple import drag_simple from .flipping import flipping -from .flipping_signal import flipping_signal -from .flux_dependence.avoided_crossing import avoided_crossing from .flux_dependence.qubit_crosstalk import qubit_crosstalk from .flux_dependence.qubit_flux_dependence import qubit_flux -from .flux_dependence.qubit_flux_tracking import qubit_flux_tracking -from .flux_dependence.resonator_crosstalk import resonator_crosstalk from .flux_dependence.resonator_flux_dependence import resonator_flux from .qubit_spectroscopy import qubit_spectroscopy from .qubit_spectroscopy_ef import qubit_spectroscopy_ef @@ -35,7 +27,8 @@ from .rabi.amplitude_frequency_signal import rabi_amplitude_frequency_signal from .rabi.ef import rabi_amplitude_ef from .rabi.length import rabi_length -from .rabi.length_sequences import rabi_length_sequences +from .rabi.length_frequency import rabi_length_frequency +from .rabi.length_frequency_signal import rabi_length_frequency_signal from .rabi.length_signal import rabi_length_signal from .ramsey.ramsey import ramsey from .ramsey.ramsey_signal import ramsey_signal @@ -46,14 +39,7 @@ from .readout_characterization import readout_characterization from .readout_mitigation_matrix import readout_mitigation_matrix from .readout_optimization.resonator_amplitude import resonator_amplitude -from .readout_optimization.resonator_frequency import resonator_frequency -from .readout_optimization.twpa_calibration.frequency import twpa_frequency -from .readout_optimization.twpa_calibration.frequency_power import twpa_frequency_power -from .readout_optimization.twpa_calibration.frequency_SNR import twpa_frequency_snr -from .readout_optimization.twpa_calibration.power import twpa_power -from .readout_optimization.twpa_calibration.power_SNR import twpa_power_snr from .resonator_punchout import resonator_punchout -from .resonator_punchout_attenuation import resonator_punchout_attenuation from .resonator_spectroscopy import resonator_spectroscopy from .signal_experiments.calibrate_state_discrimination import ( calibrate_state_discrimination, @@ -62,11 +48,7 @@ from .two_qubit_interaction import ( chevron, chevron_signal, - chsh_circuits, - chsh_pulses, correct_virtual_z_phases, - correct_virtual_z_phases_signal, - mermin, optimize_two_qubit_gate, ) from .two_qubit_interaction import ( @@ -84,32 +66,20 @@ __all__ = [ "allxy", - "allxy_drag_pulse_tuning", "single_shot_classification", "spin_echo", "spin_echo_signal", "t1", - "t1_sequences", "t1_signal", "t2", - "t2_sequences", "t2_signal", "zeno", - "zeno_signal", - "coupler_chevron", - "coupler_qubit_spectroscopy", - "coupler_resonator_spectroscopy", "dispersive_shift", "dispersive_shift_qutrit", "drag_tuning", - "fast_reset", "flipping", - "flipping_signal", - "avoided_crossing", "qubit_crosstalk", "qubit_flux", - "qubit_flux_tracking", - "resonator_crosstalk", "resonator_flux", "qubit_spectroscopy", "qubit_spectroscopy_ef", @@ -118,7 +88,6 @@ "rabi_amplitude_signal", "rabi_length", "rabi_amplitude_ef", - "rabi_length_sequences", "rabi_length_signal", "ramsey", "ramsey_signal", @@ -127,23 +96,13 @@ "readout_characterization", "readout_mitigation_matrix", "resonator_amplitude", - "resonator_frequency", - "twpa_frequency", - "twpa_frequency_power", - "twpa_frequency_snr", - "twpa_power", - "twpa_power_snr", "resonator_punchout", - "resonator_punchout_attenuation", "resonator_spectroscopy", "calibrate_state_discrimination", "time_of_flight_readout", "chevron", "chevron_signal", - "chsh_circuits", - "chsh_pulses", "correct_virtual_z_phases", - "correct_virtual_z_phases_signal", "state_tomography", "allxy_resonator_depletion_tuning", "two_qubit_state_tomography", @@ -155,7 +114,6 @@ "standard_rb_2q", "standard_rb_2q_inter", "optimize_two_qubit_gate", - "mermin", "ramsey_zz", "cross_resonance_length", "cross_resonance_length_sequences", @@ -165,4 +123,6 @@ "cross_resonance_chevron_amplitude_frequency", "cross_resonance_chevron_coupler", "cross_resonance_cnot", + "cpmg", + "drag_simple", ] diff --git a/src/qibocal/protocols/allxy/allxy.py b/src/qibocal/protocols/allxy/allxy.py index 3c52b4f72..379b494fd 100644 --- a/src/qibocal/protocols/allxy/allxy.py +++ b/src/qibocal/protocols/allxy/allxy.py @@ -1,14 +1,22 @@ from dataclasses import dataclass, field +from typing import Optional import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import ( + AcquisitionType, + AveragingMode, + Delay, + Drag, + Gaussian, + Pulse, + PulseSequence, +) -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.update import replace @dataclass @@ -67,53 +75,50 @@ class AllXYData(Data): def _acquisition( params: AllXYParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> AllXYData: r""" Data acquisition for allXY experiment. - The AllXY experiment is a simple test of the calibration of single qubit gatesThe qubit (initialized in the |0> state) + The AllXY experiment is a simple test of the calibration of single qubit gatesThe qubit (initialized in the 0 state) is subjected to two back-to-back single-qubit gates and measured. In each round, we run 21 different gate pairs: - ideally, the first 5 return the qubit to |0>, the next 12 drive it to superposition state, and the last 4 put the - qubit in |1> state. + ideally, the first 5 return the qubit to 0, the next 12 drive it to superposition state, and the last 4 put the + qubit in 1 state. """ # create a Data object to store the results data = AllXYData(beta_param=params.beta_param) - # repeat the experiment as many times as defined by software_averages - # for iteration in range(params.software_averages): sequences, all_ro_pulses = [], [] for gates in gatelist: - sequences.append(PulseSequence()) - all_ro_pulses.append({}) + sequence = PulseSequence() + ro_pulses = {} for qubit in targets: - sequences[-1], all_ro_pulses[-1][qubit] = add_gate_pair_pulses_to_sequence( - platform, gates, qubit, sequences[-1], beta_param=params.beta_param + qubit_sequence, ro_pulses[qubit] = allxy_sequence( + platform, gates, qubit, beta_param=params.beta_param ) + sequence += qubit_sequence + sequences.append(sequence) + all_ro_pulses.append(ro_pulses) # execute the pulse sequence - options = ExecutionParameters( - nshots=params.nshots, averaging_mode=AveragingMode.CYCLIC + options = dict( + nshots=params.nshots, + averaging_mode=AveragingMode.CYCLIC, + acquisition_type=AcquisitionType.DISCRIMINATION, ) if params.unrolling: - results = platform.execute_pulse_sequences(sequences, options) + results = platform.execute(sequences, **options) else: - results = [ - platform.execute_pulse_sequence(sequence, options) for sequence in sequences - ] + results = {} + for sequence in sequences: + results.update(platform.execute([sequence], **options)) - for ig, (gates, ro_pulses) in enumerate(zip(gatelist, all_ro_pulses)): + for gates, ro_pulses in zip(gatelist, all_ro_pulses): gate = "-".join(gates) for qubit in targets: - serial = ro_pulses[qubit].serial - if params.unrolling: - prob = results[serial][ig].probability(0) - z_proj = 2 * prob - 1 - else: - prob = results[ig][serial].probability(0) - z_proj = 2 * prob - 1 - + prob = results[ro_pulses[qubit].id] + z_proj = 1 - 2 * prob errors = 2 * np.sqrt(prob * (1 - prob) / params.nshots) data.register_qubit( AllXYType, @@ -129,94 +134,74 @@ def _acquisition( return data -def add_gate_pair_pulses_to_sequence( - platform: Platform, +def apply_drag(pulse: Pulse, beta_param: Optional[float] = None) -> Pulse: + """Apply Drag with parameter beta.""" + if beta_param is None: + return replace( + pulse, + envelope=Gaussian( + rel_sigma=pulse.envelope.rel_sigma, + ), + ) + return replace( # pragma: no cover + pulse, + envelope=Drag( + rel_sigma=pulse.envelope.rel_sigma, + beta=beta_param, + ), + ) + + +def allxy_sequence( + platform: CalibrationPlatform, gates, qubit, - sequence, - sequence_delay=0, - readout_delay=0, + sequence_delay=None, + readout_delay=None, beta_param=None, ): - pulse_duration = platform.create_RX_pulse(qubit, start=0).duration - # All gates have equal pulse duration - - sequence_duration = sequence.get_qubit_pulses(qubit).duration + sequence_delay - pulse_start = sequence.get_qubit_pulses(qubit).duration + sequence_delay - + natives = platform.natives.single_qubit[qubit] + qd_channel, _ = natives.RX()[0] + sequence = PulseSequence() + if sequence_delay is not None: + sequence.append((qd_channel, Delay(duration=sequence_delay))) for gate in gates: if gate == "I": pass if gate == "Xp": - if beta_param == None: - RX_pulse = platform.create_RX_pulse( - qubit, - start=pulse_start, - ) - else: - RX_pulse = platform.create_RX_drag_pulse( - qubit, - start=pulse_start, - beta=beta_param, - ) - sequence.add(RX_pulse) + qd_channel, rx_pulse = natives.RX()[0] + sequence.append((qd_channel, apply_drag(rx_pulse, beta_param))) if gate == "X9": - if beta_param == None: - RX90_pulse = platform.create_RX90_pulse( - qubit, - start=pulse_start, - ) - else: - RX90_pulse = platform.create_RX90_drag_pulse( - qubit, - start=pulse_start, - beta=beta_param, - ) - sequence.add(RX90_pulse) + qd_channel, rx90_pulse = natives.R(theta=np.pi / 2)[0] + sequence.append((qd_channel, apply_drag(rx90_pulse, beta_param))) if gate == "Yp": - if beta_param == None: - RY_pulse = platform.create_RX_pulse( - qubit, - start=pulse_start, - relative_phase=np.pi / 2, - ) - else: - RY_pulse = platform.create_RX_drag_pulse( - qubit, - start=pulse_start, - relative_phase=np.pi / 2, - beta=beta_param, - ) - sequence.add(RY_pulse) - + qd_channel, ry_pulse = natives.R(phi=np.pi / 2)[0] + sequence.append((qd_channel, apply_drag(ry_pulse, beta_param))) if gate == "Y9": - if beta_param == None: - RY90_pulse = platform.create_RX90_pulse( - qubit, - start=pulse_start, - relative_phase=np.pi / 2, - ) - else: - RY90_pulse = platform.create_RX90_drag_pulse( - qubit, - start=pulse_start, - relative_phase=np.pi / 2, - beta=beta_param, - ) - sequence.add(RY90_pulse) - - sequence_duration += pulse_duration - pulse_start = sequence_duration + qd_channel, ry90_pulse = natives.R(theta=np.pi / 2, phi=np.pi / 2)[0] + sequence.append((qd_channel, apply_drag(ry90_pulse, beta_param))) # RO pulse starting just after pair of gates - ro_pulse = platform.create_qubit_readout_pulse( - qubit, start=sequence_duration + readout_delay - ) - - sequence.add(ro_pulse) + qd_channel = platform.qubits[qubit].drive + ro_channel, ro_pulse = natives.MZ()[0] + if readout_delay is not None: + sequence.append( + ( + ro_channel, + Delay(duration=sequence.channel_duration(qd_channel) + readout_delay), + ) + ) + else: + sequence.append( + ( + ro_channel, + Delay(duration=sequence.channel_duration(qd_channel)), + ) + ) + sequence.append((ro_channel, ro_pulse)) return sequence, ro_pulse diff --git a/src/qibocal/protocols/allxy/allxy_drag_pulse_tuning.py b/src/qibocal/protocols/allxy/allxy_drag_pulse_tuning.py deleted file mode 100644 index df76e1ca1..000000000 --- a/src/qibocal/protocols/allxy/allxy_drag_pulse_tuning.py +++ /dev/null @@ -1,166 +0,0 @@ -from dataclasses import dataclass, field -from typing import Optional - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from qibolab import AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId - -from qibocal.auto.operation import Data, Parameters, Results, Routine - -from . import allxy - - -@dataclass -class AllXYDragParameters(Parameters): - """AllXYDrag runcard inputs.""" - - beta_start: float - """Initial beta parameter for Drag pulse.""" - beta_end: float - """Final beta parameter for Drag pulse.""" - beta_step: float - """Step beta parameter for Drag pulse.""" - - -@dataclass -class AllXYDragResults(Results): - """AllXYDrag outputs.""" - - -@dataclass -class AllXYDragData(Data): - """AllXY acquisition outputs.""" - - beta_param: Optional[float] = None - """Beta parameter for drag pulse.""" - data: dict[tuple[QubitId, float], npt.NDArray[allxy.AllXYType]] = field( - default_factory=dict - ) - """Raw data acquired.""" - - @property - def beta_params(self): - """Access qubits from data structure.""" - return np.unique([b[1] for b in self.data]) - - -def _acquisition( - params: AllXYDragParameters, - platform: Platform, - targets: list[QubitId], -) -> AllXYDragData: - r""" - Data acquisition for allXY experiment varying beta. - The AllXY experiment is a simple test of the calibration of single qubit gatesThe qubit (initialized in the |0> state) - is subjected to two back-to-back single-qubit gates and measured. In each round, we run 21 different gate pairs: - ideally, the first 5 return the qubit to |0>, the next 12 drive it to superposition state, and the last 4 put the - qubit in |1> state. - - The AllXY iteration method allows the user to execute iteratively the list of gates playing with the drag pulse shape - in order to find the optimal drag pulse coefficient for pi pulses. - """ - - data = AllXYDragData() - - betas = np.arange(params.beta_start, params.beta_end, params.beta_step).round(4) - # sweep the parameters - for beta_param in betas: - for gates in allxy.gatelist: - # create a sequence of pulses - ro_pulses = {} - sequence = PulseSequence() - for qubit in targets: - sequence, ro_pulses[qubit] = allxy.add_gate_pair_pulses_to_sequence( - platform, gates, qubit, sequence, beta_param - ) - - # execute the pulse sequence - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - averaging_mode=AveragingMode.CYCLIC, - ), - ) - - # retrieve the results for every qubit - for qubit in targets: - z_proj = 2 * results[ro_pulses[qubit].serial].probability(0) - 1 - # store the results - gate = "-".join(gates) - data.register_qubit( - allxy.AllXYType, - (qubit, beta_param), - dict(prob=np.array([z_proj]), gate=np.array([gate])), - ) - return data - - -def _fit(_data: AllXYDragData) -> AllXYDragResults: - """Post-processing for allXYDrag.""" - return AllXYDragResults() - - -def _plot(data: AllXYDragData, target: QubitId, fit: AllXYDragResults = None): - """Plotting function for allXYDrag.""" - - figures = [] - fitting_report = "" - - fig = go.Figure() - beta_params = data.beta_params - - for j, beta_param in enumerate(beta_params): - beta_param_data = data[target, beta_param] - fig.add_trace( - go.Scatter( - x=beta_param_data.gate, - y=beta_param_data.prob, - mode="markers+lines", - opacity=0.5, - name=f"Beta {beta_param}", - showlegend=True, - legendgroup=f"group{j}", - text=allxy.gatelist, - textposition="bottom center", - ), - ) - - fig.add_hline( - y=0, - line_width=2, - line_dash="dash", - line_color="grey", - ) - fig.add_hline( - y=1, - line_width=2, - line_dash="dash", - line_color="grey", - ) - - fig.add_hline( - y=-1, - line_width=2, - line_dash="dash", - line_color="grey", - ) - - fig.update_layout( - showlegend=True, - xaxis_title="Gate sequence number", - yaxis_title="Expectation value of Z", - ) - - figures.append(fig) - - return figures, fitting_report - - -allxy_drag_pulse_tuning = Routine(_acquisition, _fit, _plot) -"""AllXYDrag Routine object.""" diff --git a/src/qibocal/protocols/allxy/allxy_resonator_depletion_tuning.py b/src/qibocal/protocols/allxy/allxy_resonator_depletion_tuning.py index 6807ab993..d50190fbe 100644 --- a/src/qibocal/protocols/allxy/allxy_resonator_depletion_tuning.py +++ b/src/qibocal/protocols/allxy/allxy_resonator_depletion_tuning.py @@ -4,12 +4,10 @@ import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AveragingMode, PulseSequence -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from . import allxy @@ -24,6 +22,13 @@ class AllXYResonatorParameters(Parameters): """Final delay parameter for resonator depletion.""" delay_step: float """Step delay parameter for resonator depletion.""" + readout_delay: int = 1000 + """Delay on readout.""" + unrolling: bool = False + """If ``True`` it uses sequence unrolling to deploy multiple sequences in a single instrument call. + Defaults to ``False``.""" + beta_param: float = None + """Beta parameter for drag pulse.""" @dataclass @@ -50,7 +55,7 @@ def delay_params(self): def _acquisition( params: AllXYResonatorParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> AllXYResonatorData: r""" @@ -65,45 +70,47 @@ def _acquisition( delays = np.arange(params.delay_start, params.delay_end, params.delay_step) # sweep the parameters - for delay_param in delays: + for delay in delays: + sequences, all_ro_pulses = [], [] for gates in allxy.gatelist: - # create a sequence of pulses - ro_pulses = {} sequence = PulseSequence() + ro_pulses = {} for qubit in targets: - ro_pulse = platform.create_qubit_readout_pulse(qubit, start=0) - sequence.add(ro_pulse) - sequence, ro_pulses[qubit] = allxy.add_gate_pair_pulses_to_sequence( + qubit_sequence, ro_pulses[qubit] = allxy.allxy_sequence( platform, gates, qubit, - sequence, - sequence_delay=int( - delay_param - ), # We need conversion to int due to devices for now + beta_param=params.beta_param, + sequence_delay=delay, readout_delay=1000, ) - - # execute the pulse sequence - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - averaging_mode=AveragingMode.CYCLIC, - ), - ) - - # retrieve the results for every qubit + sequence += qubit_sequence + sequences.append(sequence) + all_ro_pulses.append(ro_pulses) + options = dict(nshots=params.nshots, averaging_mode=AveragingMode.CYCLIC) + if params.unrolling: + results = platform.execute(sequences, **options) + else: + results = {} + for sequence in sequences: + results.update(platform.execute([sequence], **options)) + + for gates, ro_pulses in zip(allxy.gatelist, all_ro_pulses): + gate = "-".join(gates) for qubit in targets: - z_proj = 2 * results[ro_pulses[qubit].serial].probability(0) - 1 - # store the results - gate = "-".join(gates) + prob = 1 - results[ro_pulses[qubit].id] + z_proj = 2 * prob - 1 + errors = 2 * np.sqrt(prob * (1 - prob) / params.nshots) data.register_qubit( allxy.AllXYType, - (qubit, float(delay_param)), - dict(prob=np.array([z_proj]), gate=np.array([gate])), + (qubit, float(delay)), + dict( + prob=np.array([z_proj]), + gate=np.array([gate]), + errors=np.array([errors]), + ), ) + return data diff --git a/src/qibocal/protocols/classification.py b/src/qibocal/protocols/classification.py index 6731e08a0..98acb4f6c 100644 --- a/src/qibocal/protocols/classification.py +++ b/src/qibocal/protocols/classification.py @@ -7,15 +7,20 @@ import numpy.typing as npt import pandas as pd import plotly.graph_objects as go -from qibolab import AcquisitionType, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, PulseSequence from sklearn.metrics import roc_auc_score, roc_curve from qibocal import update -from qibocal.auto.operation import RESULTSFILE, Data, Parameters, Results, Routine +from qibocal.auto.operation import ( + RESULTSFILE, + Data, + Parameters, + QubitId, + Results, + Routine, +) from qibocal.auto.serialize import serialize +from qibocal.calibration import CalibrationPlatform from qibocal.fitting.classifier import run from qibocal.protocols.utils import ( LEGEND_FONT_SIZE, @@ -35,19 +40,33 @@ DEFAULT_CLASSIFIER = "qubit_fit" +def evaluate_snr(zeros: npt.NDArray, ones: npt.NDArray) -> float: + """Compute snr for zeros and ones""" + line = np.mean(ones, axis=0) - np.mean(zeros, axis=0) + projection_zeros, projection_ones = np.dot(zeros, line), np.dot(ones, line) + mu0, std0 = np.mean(projection_zeros), np.std(projection_zeros) + mu1, std1 = np.mean(projection_ones), np.std(projection_ones) + return np.abs(mu1 - mu0) ** 2 / 2 / std0 / std1 + + @dataclass class SingleShotClassificationParameters(Parameters): """SingleShotClassification runcard inputs.""" unrolling: bool = False - """If ``True`` it uses sequence unrolling to deploy multiple sequences in a single instrument call. - Defaults to ``False``.""" + """Whether to unroll the sequences. + + If ``True`` it uses sequence unrolling to deploy multiple sequences in a + single instrument call. + + Defaults to ``False``. + """ classifiers_list: Optional[list[str]] = field( default_factory=lambda: [DEFAULT_CLASSIFIER] ) - """List of models to classify the qubit states""" + """List of models to classify the qubit states.""" savedir: Optional[str] = " " - """Dumping folder of the classification results""" + """Dumping folder of the classification results.""" ClassificationType = np.dtype([("i", np.float64), ("q", np.float64), ("state", int)]) @@ -59,7 +78,7 @@ class SingleShotClassificationData(Data): nshots: int """Number of shots.""" savedir: str - """Dumping folder of the classification results""" + """Dumping folder of the classification results.""" qubit_frequencies: dict[QubitId, float] = field(default_factory=dict) """Qubit frequencies.""" data: dict[QubitId, npt.NDArray] = field(default_factory=dict) @@ -67,7 +86,17 @@ class SingleShotClassificationData(Data): classifiers_list: Optional[list[str]] = field( default_factory=lambda: [DEFAULT_CLASSIFIER] ) - """List of models to classify the qubit states""" + """List of models to classify the qubit states.""" + + def state_zero(self, qubit: QubitId) -> npt.NDArray: + """Get state zero data.""" + state_zero = self.data[qubit][self.data[qubit].state == 0] + return np.column_stack([state_zero.i, state_zero.q]) + + def state_one(self, qubit: QubitId) -> npt.NDArray: + """Get state one data.""" + state_one = self.data[qubit][self.data[qubit].state == 1] + return np.column_stack([state_one.i, state_one.q]) @dataclass @@ -106,12 +135,14 @@ class SingleShotClassificationResults(Results): """Test set.""" y_tests: dict[QubitId, list] = field(default_factory=dict) """Test set.""" + snr: dict[QubitId, float] = field(default_factory=dict) + """SNR for two clouds""" def __contains__(self, key: QubitId): """Checking if key is in Results. - Overwritten because classifiers_hpars is empty when running - the default_classifier. + Overwritten because classifiers_hpars is empty when running the + default_classifier. """ return all( key in getattr(self, field.name) @@ -142,7 +173,7 @@ def save(self, path): def _acquisition( params: SingleShotClassificationParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> SingleShotClassificationData: """ @@ -173,19 +204,21 @@ def _acquisition( # state1_sequence: RX - MZ # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel + native = platform.natives.single_qubit sequences, all_ro_pulses = [], [] for state in [0, 1]: - sequence = PulseSequence() - RX_pulses = {} ro_pulses = {} - for qubit in targets: - RX_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=RX_pulses[qubit].finish - ) - if state == 1: - sequence.add(RX_pulses[qubit]) - sequence.add(ro_pulses[qubit]) + sequence = PulseSequence() + for q in targets: + ro_sequence = native[q].MZ() + ro_pulses[q] = ro_sequence[0][1].id + sequence += ro_sequence + + if state == 1: + rx_sequence = PulseSequence() + for q in targets: + rx_sequence += native[q].RX() + sequence = rx_sequence | sequence sequences.append(sequence) all_ro_pulses.append(ro_pulses) @@ -193,38 +226,36 @@ def _acquisition( data = SingleShotClassificationData( nshots=params.nshots, qubit_frequencies={ - qubit: platform.qubits[qubit].drive_frequency for qubit in targets + qubit: platform.config(platform.qubits[qubit].drive).frequency + for qubit in targets }, classifiers_list=params.classifiers_list, savedir=params.savedir, ) - options = ExecutionParameters( + options = dict( nshots=params.nshots, relaxation_time=params.relaxation_time, acquisition_type=AcquisitionType.INTEGRATION, ) if params.unrolling: - results = platform.execute_pulse_sequences(sequences, options) + results = platform.execute(sequences, **options) else: - results = [ - platform.execute_pulse_sequence(sequence, options) for sequence in sequences - ] + results = {} + for sequence in sequences: + results.update(platform.execute([sequence], **options)) - for ig, (state, ro_pulses) in enumerate(zip([0, 1], all_ro_pulses)): + for state, ro_pulses in zip([0, 1], all_ro_pulses): for qubit in targets: - serial = ro_pulses[qubit].serial - if params.unrolling: - result = results[serial][ig] - else: - result = results[ig][serial] + serial = ro_pulses[qubit] + result = results[serial] data.register_qubit( ClassificationType, (qubit), dict( - i=result.voltage_i, - q=result.voltage_q, + i=result[..., 0], + q=result[..., 1], state=[state] * params.nshots, ), ) @@ -240,6 +271,7 @@ def _fit(data: SingleShotClassificationData) -> SingleShotClassificationResults: y_tests = {} x_tests = {} hpars = {} + snr = {} threshold = {} rotation_angle = {} mean_gnd_states = {} @@ -281,6 +313,7 @@ def _fit(data: SingleShotClassificationData) -> SingleShotClassificationResults: mean_gnd_states[qubit] = models[i].iq_mean0.tolist() mean_exc_states[qubit] = models[i].iq_mean1.tolist() fidelity[qubit] = models[i].fidelity + snr[qubit] = evaluate_snr(data.state_zero(qubit), data.state_one(qubit)) assignment_fidelity[qubit] = models[i].assignment_fidelity predictions_state0 = models[i].predict(iq_state0.tolist()) effective_temperature[qubit] = models[i].effective_temperature( @@ -305,6 +338,7 @@ def _fit(data: SingleShotClassificationData) -> SingleShotClassificationResults: savedir=data.savedir, y_preds=y_test_predict, grid_preds=grid_preds_dict, + snr=snr, ) @@ -367,6 +401,7 @@ def _plot( "Threshold", "Readout Fidelity", "Assignment Fidelity", + "SNR", "Effective Qubit Temperature [K]", ], [ @@ -376,6 +411,7 @@ def _plot( np.round(fit.threshold[target], 6), np.round(fit.fidelity[target], 3), np.round(fit.assignment_fidelity[target], 3), + np.round(fit.snr[target], 1), format_error_single_cell( round_report([fit.effective_temperature[target]]) ), @@ -387,14 +423,18 @@ def _plot( def _update( - results: SingleShotClassificationResults, platform: Platform, target: QubitId + results: SingleShotClassificationResults, + platform: CalibrationPlatform, + target: QubitId, ): update.iq_angle(results.rotation_angle[target], platform, target) update.threshold(results.threshold[target], platform, target) update.mean_gnd_states(results.mean_gnd_states[target], platform, target) update.mean_exc_states(results.mean_exc_states[target], platform, target) update.readout_fidelity(results.fidelity[target], platform, target) - update.assignment_fidelity(results.assignment_fidelity[target], platform, target) + platform.calibration.single_qubits[target].readout.effective_temperature = ( + results.effective_temperature[target][0] + ) single_shot_classification = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/coherence/cpmg.py b/src/qibocal/protocols/coherence/cpmg.py new file mode 100644 index 000000000..d3f6b5d49 --- /dev/null +++ b/src/qibocal/protocols/coherence/cpmg.py @@ -0,0 +1,107 @@ +from dataclasses import dataclass + +import numpy as np +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper + +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.result import probability + +from . import t1 +from .spin_echo import SpinEchoParameters, SpinEchoResults +from .utils import dynamical_decoupling_sequence, exponential_fit_probability, plot + + +@dataclass +class CpmgParameters(SpinEchoParameters): + """Cpmg runcard inputs.""" + + n: int = 1 + """Number of pi rotations.""" + + +@dataclass +class CpmgResults(SpinEchoResults): + """SpinEcho outputs.""" + + +class CpmgData(t1.T1Data): + """SpinEcho acquisition outputs.""" + + +def _acquisition( + params: CpmgParameters, + platform: CalibrationPlatform, + targets: list[QubitId], +) -> CpmgData: + """Data acquisition for Cpmg""" + # create a sequence of pulses for the experiment: + sequence, delays = dynamical_decoupling_sequence( + platform, targets, n=params.n, kind="CPMG" + ) + + # define the parameter to sweep and its range: + # delay between pulses + wait_range = np.arange( + params.delay_between_pulses_start, + params.delay_between_pulses_end, + params.delay_between_pulses_step, + ) + durations = [] + for q in targets: + # this is assuming that RX and RX90 have the same duration + duration = platform.natives.single_qubit[q].RX()[0][1].duration + durations.append(duration) + assert ( + params.delay_between_pulses_start - params.n * duration + ) / 2 / params.n >= 0, ( + f"Initial delay too short for qubit {q}, " + f"minimum delay should be {params.n * duration}" + ) + + assert ( + len(set(durations)) == 1 + ), "Cannot run on mulitple qubit with different RX duration." + + sweeper = Sweeper( + parameter=Parameter.duration, + values=(wait_range - params.n * durations[0]) / 2 / params.n, + pulses=delays, + ) + + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, + ) + + data = CpmgData() + for qubit in targets: + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[-1] + result = results[ro_pulse.id] + prob = probability(result, state=1) + error = np.sqrt(prob * (1 - prob) / params.nshots) + data.register_qubit( + t1.CoherenceProbType, + (qubit), + dict( + wait=wait_range, + prob=prob, + error=error, + ), + ) + + return data + + +def _fit(data: CpmgData) -> CpmgResults: + """Post-processing for Cpmg.""" + t2Echos, fitted_parameters, pcovs, chi2 = exponential_fit_probability(data) + return CpmgResults(t2Echos, fitted_parameters, pcovs, chi2) + + +cpmg = Routine(_acquisition, _fit, plot) +"""Cpmg Routine object.""" diff --git a/src/qibocal/protocols/coherence/spin_echo.py b/src/qibocal/protocols/coherence/spin_echo.py index 20e8fb042..bd77fb115 100644 --- a/src/qibocal/protocols/coherence/spin_echo.py +++ b/src/qibocal/protocols/coherence/spin_echo.py @@ -1,20 +1,16 @@ -from copy import deepcopy from dataclasses import dataclass, field from typing import Optional import numpy as np -import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.result import probability -from ..utils import table_dict, table_html from . import t1 from .spin_echo_signal import SpinEchoSignalParameters, SpinEchoSignalResults, _update -from .utils import exp_decay, exponential_fit_probability +from .utils import dynamical_decoupling_sequence, exponential_fit_probability, plot @dataclass @@ -38,42 +34,43 @@ class SpinEchoData(t1.T1Data): def _acquisition( params: SpinEchoParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> SpinEchoData: """Data acquisition for SpinEcho""" # create a sequence of pulses for the experiment: - # Spin Echo 3 Pulses: RX(pi/2) - wait t(rotates z) - RX(pi) - wait t(rotates z) - RX(pi/2) - readout - ro_pulses = {} - RX90_pulses1 = {} - RX_pulses = {} - RX90_pulses2 = {} - sequence = PulseSequence() - for qubit in targets: - RX90_pulses1[qubit] = platform.create_RX90_pulse(qubit, start=0) - RX_pulses[qubit] = platform.create_RX_pulse( - qubit, start=RX90_pulses1[qubit].finish - ) - RX90_pulses2[qubit] = platform.create_RX90_pulse( - qubit, start=RX_pulses[qubit].finish - ) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=RX90_pulses2[qubit].finish - ) - sequence.add(RX90_pulses1[qubit]) - sequence.add(RX_pulses[qubit]) - sequence.add(RX90_pulses2[qubit]) - sequence.add(ro_pulses[qubit]) + sequence, delays = dynamical_decoupling_sequence(platform, targets, kind="CP") # define the parameter to sweep and its range: # delay between pulses - ro_wait_range = np.arange( + wait_range = np.arange( params.delay_between_pulses_start, params.delay_between_pulses_end, params.delay_between_pulses_step, ) - options = ExecutionParameters( + durations = [] + for q in targets: + # this is assuming that RX and RX90 have the same duration + duration = platform.natives.single_qubit[q].RX()[0][1].duration + durations.append(duration) + assert (params.delay_between_pulses_start - duration) / 2 >= 0, ( + f"Initial delay too short for qubit {q}, " + f"minimum delay should be {duration}" + ) + assert ( + len(set(durations)) == 1 + ), "Cannot run on mulitple qubit with different RX duration." + + sweeper = Sweeper( + parameter=Parameter.duration, + values=(wait_range - durations[0]) / 2, + pulses=delays, + ) + + results = platform.execute( + [sequence], + [[sweeper]], nshots=params.nshots, relaxation_time=params.relaxation_time, acquisition_type=AcquisitionType.DISCRIMINATION, @@ -81,45 +78,20 @@ def _acquisition( ) data = SpinEchoData() - sequences, all_ro_pulses = [], [] - # sweep the parameter - for wait in ro_wait_range: - # save data as often as defined by points - - for qubit in targets: - RX_pulses[qubit].start = RX90_pulses1[qubit].finish + wait // 2 - RX90_pulses2[qubit].start = RX_pulses[qubit].finish + wait // 2 - ro_pulses[qubit].start = RX90_pulses2[qubit].finish - - sequences.append(deepcopy(sequence)) - all_ro_pulses.append(deepcopy(sequence).ro_pulses) - - if params.unrolling: - results = platform.execute_pulse_sequences(sequences, options) - - elif not params.unrolling: - results = [ - platform.execute_pulse_sequence(sequence, options) for sequence in sequences - ] - - for ig, (wait, ro_pulses) in enumerate(zip(ro_wait_range, all_ro_pulses)): - for qubit in targets: - serial = ro_pulses.get_qubit_pulses(qubit)[0].serial - if params.unrolling: - result = results[serial][0] - else: - result = results[ig][serial] - prob = result.probability(state=0) - error = np.sqrt(prob * (1 - prob) / params.nshots) - data.register_qubit( - t1.CoherenceProbType, - (qubit), - dict( - wait=np.array([wait]), - prob=np.array([prob]), - error=np.array([error]), - ), - ) + for qubit in targets: + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[-1] + result = results[ro_pulse.id] + prob = probability(result, state=1) + error = np.sqrt(prob * (1 - prob) / params.nshots) + data.register_qubit( + t1.CoherenceProbType, + (qubit), + dict( + wait=wait_range, + prob=prob, + error=error, + ), + ) return data @@ -130,77 +102,5 @@ def _fit(data: SpinEchoData) -> SpinEchoResults: return SpinEchoResults(t2Echos, fitted_parameters, pcovs, chi2) -def _plot(data: SpinEchoData, target: QubitId, fit: SpinEchoResults = None): - """Plotting for SpinEcho""" - - figures = [] - # iterate over multiple data folders - fitting_report = "" - - qubit_data = data[target] - waits = qubit_data.wait - probs = qubit_data.prob - error_bars = qubit_data.error - - fig = go.Figure( - [ - go.Scatter( - x=waits, - y=probs, - opacity=1, - name="Probability of 0", - showlegend=True, - legendgroup="Probability of 0", - mode="lines", - ), - go.Scatter( - x=np.concatenate((waits, waits[::-1])), - y=np.concatenate((probs + error_bars, (probs - error_bars)[::-1])), - fill="toself", - fillcolor=t1.COLORBAND, - line=dict(color=t1.COLORBAND_LINE), - showlegend=True, - name="Errors", - ), - ] - ) - - if fit is not None: - # add fitting trace - waitrange = np.linspace( - min(waits), - max(waits), - 2 * len(qubit_data), - ) - params = fit.fitted_parameters[target] - - fig.add_trace( - go.Scatter( - x=waitrange, - y=exp_decay(waitrange, *params), - name="Fit", - line=go.scatter.Line(dash="dot"), - ), - ) - fitting_report = table_html( - table_dict( - target, - ["T2 Spin Echo [ns]", "chi2 reduced"], - [fit.t2_spin_echo[target], fit.chi2[target]], - display_error=True, - ) - ) - - fig.update_layout( - showlegend=True, - xaxis_title="Time [ns]", - yaxis_title="Probability of State 0", - ) - - figures.append(fig) - - return figures, fitting_report - - -spin_echo = Routine(_acquisition, _fit, _plot, _update) +spin_echo = Routine(_acquisition, _fit, plot, _update) """SpinEcho Routine object.""" diff --git a/src/qibocal/protocols/coherence/spin_echo_signal.py b/src/qibocal/protocols/coherence/spin_echo_signal.py index 94a852f01..8b8885f85 100644 --- a/src/qibocal/protocols/coherence/spin_echo_signal.py +++ b/src/qibocal/protocols/coherence/spin_echo_signal.py @@ -1,20 +1,23 @@ -from copy import deepcopy from dataclasses import dataclass from typing import Union import numpy as np import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper -from qibocal import update -from qibocal.auto.operation import Parameters, Results, Routine +from qibocal.auto.operation import Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.result import magnitude, phase +from ... import update from ..utils import table_dict, table_html from .t1_signal import T1SignalData -from .utils import CoherenceType, exp_decay, exponential_fit +from .utils import ( + CoherenceType, + dynamical_decoupling_sequence, + exp_decay, + exponential_fit, +) @dataclass @@ -27,18 +30,14 @@ class SpinEchoSignalParameters(Parameters): """Final delay between pulses [ns].""" delay_between_pulses_step: int """Step delay between pulses [ns].""" - unrolling: bool = False - """If ``True`` it uses sequence unrolling to deploy multiple sequences in a single instrument call. - Defaults to ``False``.""" single_shot: bool = False - """If ``True`` save single shot signal data.""" @dataclass class SpinEchoSignalResults(Results): """SpinEchoSignal outputs.""" - t2_spin_echo: dict[QubitId, Union[float, list[float]]] + t2: dict[QubitId, Union[float, list[float]]] """T2 echo for each qubit.""" fitted_parameters: dict[QubitId, dict[str, float]] """Raw fitting output.""" @@ -52,42 +51,44 @@ class SpinEchoSignalData(T1SignalData): def _acquisition( params: SpinEchoSignalParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> SpinEchoSignalData: """Data acquisition for SpinEcho""" # create a sequence of pulses for the experiment: - # Spin Echo 3 Pulses: RX(pi/2) - wait t(rotates z) - RX(pi) - wait t(rotates z) - RX(pi/2) - readout - ro_pulses = {} - RX90_pulses1 = {} - RX_pulses = {} - RX90_pulses2 = {} - sequence = PulseSequence() - for qubit in targets: - RX90_pulses1[qubit] = platform.create_RX90_pulse(qubit, start=0) - RX_pulses[qubit] = platform.create_RX_pulse( - qubit, start=RX90_pulses1[qubit].finish - ) - RX90_pulses2[qubit] = platform.create_RX90_pulse( - qubit, start=RX_pulses[qubit].finish - ) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=RX90_pulses2[qubit].finish - ) - sequence.add(RX90_pulses1[qubit]) - sequence.add(RX_pulses[qubit]) - sequence.add(RX90_pulses2[qubit]) - sequence.add(ro_pulses[qubit]) + sequence, delays = dynamical_decoupling_sequence(platform, targets, kind="CP") # define the parameter to sweep and its range: # delay between pulses - ro_wait_range = np.arange( + wait_range = np.arange( params.delay_between_pulses_start, params.delay_between_pulses_end, params.delay_between_pulses_step, ) - options = ExecutionParameters( + durations = [] + for q in targets: + # this is assuming that RX and RX90 have the same duration + duration = platform.natives.single_qubit[q].RX()[0][1].duration + durations.append(duration) + assert (params.delay_between_pulses_start - duration) / 2 >= 0, ( + f"Initial delay too short for qubit {q}, " + f"minimum delay should be {duration}" + ) + + assert ( + len(set(durations)) == 1 + ), "Cannot run on mulitple qubit with different RX duration." + + sweeper = Sweeper( + parameter=Parameter.duration, + values=(wait_range - durations[0]) / 2, + pulses=delays, + ) + + results = platform.execute( + [sequence], + [[sweeper]], nshots=params.nshots, relaxation_time=params.relaxation_time, acquisition_type=AcquisitionType.INTEGRATION, @@ -96,55 +97,24 @@ def _acquisition( ), ) - sequences, all_ro_pulses = [], [] - - # sweep the parameter - for wait in ro_wait_range: - # save data as often as defined by points - - for qubit in targets: - RX_pulses[qubit].start = RX90_pulses1[qubit].finish + wait / 2 - RX90_pulses2[qubit].start = RX_pulses[qubit].finish + wait / 2 - ro_pulses[qubit].start = RX90_pulses2[qubit].finish - - sequences.append(deepcopy(sequence)) - all_ro_pulses.append(deepcopy(sequence).ro_pulses) - - if params.unrolling: - results = platform.execute_pulse_sequences(sequences, options) - - elif not params.unrolling: - results = [ - platform.execute_pulse_sequence(sequence, options) for sequence in sequences - ] - data = SpinEchoSignalData() - for ig, (wait, ro_pulses) in enumerate(zip(ro_wait_range, all_ro_pulses)): - for qubit in targets: - serial = ro_pulses.get_qubit_pulses(qubit)[0].serial - if params.unrolling: - result = results[serial][0] - else: - result = results[ig][serial] - if params.single_shot: - _wait = np.array(len(result.magnitude) * [wait]) - else: - _wait = np.array([wait]) - data.register_qubit( - CoherenceType, - (qubit), - dict( - wait=_wait, - signal=np.array([result.magnitude]), - phase=np.array([result.phase]), - ), - ) - - if params.single_shot: - data.data = { - qubit: values.reshape((len(ro_wait_range), params.nshots)).T - for qubit, values in data.data.items() - } + for qubit in targets: + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[-1] + result = results[ro_pulse.id] + signal = magnitude(result) + if params.single_shot: + _wait = np.array(len(signal) * [wait_range]) + else: + _wait = wait_range + data.register_qubit( + CoherenceType, + (qubit), + dict( + wait=_wait, + signal=signal, + phase=phase(result), + ), + ) return data @@ -204,7 +174,7 @@ def _plot(data: SpinEchoSignalData, target: QubitId, fit: SpinEchoSignalResults table_dict( target, ["T2 Spin Echo [ns]"], - [np.round(fit.t2_spin_echo[target])], + [np.round(fit.t2[target])], display_error=True, ) ) @@ -220,8 +190,10 @@ def _plot(data: SpinEchoSignalData, target: QubitId, fit: SpinEchoSignalResults return figures, fitting_report -def _update(results: SpinEchoSignalResults, platform: Platform, target: QubitId): - update.t2_spin_echo(results.t2_spin_echo[target], platform, target) +def _update( + results: SpinEchoSignalResults, platform: CalibrationPlatform, target: QubitId +): + update.t2_spin_echo(results.t2[target], platform, target) spin_echo_signal = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/coherence/t1.py b/src/qibocal/protocols/coherence/t1.py index 54b99ee93..d6630a3aa 100644 --- a/src/qibocal/protocols/coherence/t1.py +++ b/src/qibocal/protocols/coherence/t1.py @@ -4,20 +4,15 @@ import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper -from qibocal.auto.operation import Data, Routine +from qibocal.auto.operation import Data, QubitId, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.result import probability from ..utils import table_dict, table_html from . import t1_signal, utils -COLORBAND = "rgba(0,100,80,0.2)" -COLORBAND_LINE = "rgba(255,255,255,0)" - @dataclass class T1Parameters(t1_signal.T1SignalParameters): @@ -47,41 +42,14 @@ class T1Data(Data): def _acquisition( - params: T1Parameters, platform: Platform, targets: list[QubitId] + params: T1Parameters, platform: CalibrationPlatform, targets: list[QubitId] ) -> T1Data: - r"""Data acquisition for T1 experiment. - In a T1 experiment, we measure an excited qubit after a delay. Due to decoherence processes - (e.g. amplitude damping channel), it is possible that, at the time of measurement, after the delay, - the qubit will not be excited anymore. The larger the delay time is, the more likely is the qubit to - fall to the ground state. The goal of the experiment is to characterize the decay rate of the qubit - towards the ground state. - - Args: - params: - platform (Platform): Qibolab platform object - targets (list): list of target qubits to perform the action - delay_before_readout_start (int): Initial time delay before ReadOut - delay_before_readout_end (list): Maximum time delay before ReadOut - delay_before_readout_step (int): Scan range step for the delay before ReadOut - software_averages (int): Number of executions of the routine for averaging results - points (int): Save data results in a file every number of points - """ + """Data acquisition for T1 experiment.""" - # create a sequence of pulses for the experiment - # RX - wait t - MZ - qd_pulses = {} - ro_pulses = {} - sequence = PulseSequence() - for qubit in targets: - qd_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].duration - ) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) + sequence, ro_pulses, delays = t1_signal.t1_sequence( + platform=platform, targets=targets + ) - # define the parameter to sweep and its range: - # wait time before readout ro_wait_range = np.arange( params.delay_before_readout_start, params.delay_before_readout_end, @@ -89,29 +57,24 @@ def _acquisition( ) sweeper = Sweeper( - Parameter.start, - ro_wait_range, - [ro_pulses[qubit] for qubit in targets], - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + values=ro_wait_range, + pulses=[delays[q] for q in targets], ) data = T1Data() - # sweep the parameter - # execute the pulse sequence - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ), - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, ) for qubit in targets: - probs = results[ro_pulses[qubit].serial].probability(state=1) + probs = probability(results[ro_pulses[qubit].id], state=1) errors = np.sqrt(probs * (1 - probs) / params.nshots) data.register_qubit( CoherenceProbType, @@ -159,8 +122,8 @@ def _plot(data: T1Data, target: QubitId, fit: T1Results = None): x=np.concatenate((waits, waits[::-1])), y=np.concatenate((probs + error_bars, (probs - error_bars)[::-1])), fill="toself", - fillcolor=COLORBAND, - line=dict(color=COLORBAND_LINE), + fillcolor=utils.COLORBAND, + line=dict(color=utils.COLORBAND_LINE), showlegend=True, name="Errors", ), diff --git a/src/qibocal/protocols/coherence/t1_sequences.py b/src/qibocal/protocols/coherence/t1_sequences.py deleted file mode 100644 index d932e3acb..000000000 --- a/src/qibocal/protocols/coherence/t1_sequences.py +++ /dev/null @@ -1,88 +0,0 @@ -import numpy as np -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId - -from qibocal.auto.operation import Routine - -from . import t1_signal -from .utils import CoherenceType - - -def _acquisition( - params: t1_signal.T1SignalParameters, platform: Platform, targets: list[QubitId] -) -> t1_signal.T1SignalData: - r"""Data acquisition for T1 experiment. - In a T1 experiment, we measure an excited qubit after a delay. Due to decoherence processes - (e.g. amplitude damping channel), it is possible that, at the time of measurement, after the delay, - the qubit will not be excited anymore. The larger the delay time is, the more likely is the qubit to - fall to the ground state. The goal of the experiment is to characterize the decay rate of the qubit - towards the ground state. - - Args: - params: - platform (Platform): Qibolab platform object - targets (list): list of target qubits to perform the action - delay_before_readout_start (int): Initial time delay before ReadOut - delay_before_readout_end (list): Maximum time delay before ReadOut - delay_before_readout_step (int): Scan range step for the delay before ReadOut - software_averages (int): Number of executions of the routine for averaging results - points (int): Save data results in a file every number of points - """ - - # create a sequence of pulses for the experiment - # RX - wait t - MZ - qd_pulses = {} - ro_pulses = {} - sequence = PulseSequence() - for qubit in targets: - qd_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].duration - ) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - - # define the parameter to sweep and its range: - # wait time before readout - ro_wait_range = np.arange( - params.delay_before_readout_start, - params.delay_before_readout_end, - params.delay_before_readout_step, - ) - - data = t1_signal.T1SignalData() - - # repeat the experiment as many times as defined by software_averages - # sweep the parameter - for wait in ro_wait_range: - for qubit in targets: - ro_pulses[qubit].start = qd_pulses[qubit].duration + wait - - # execute the pulse sequence - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - ) - for qubit in targets: - result = results[ro_pulses[qubit].serial] - data.register_qubit( - CoherenceType, - (qubit), - dict( - wait=np.array([wait]), - signal=np.array([result.magnitude]), - phase=np.array([result.phase]), - ), - ) - return data - - -t1_sequences = Routine(_acquisition, t1_signal._fit, t1_signal._plot, t1_signal._update) -"""T1 Routine object.""" diff --git a/src/qibocal/protocols/coherence/t1_signal.py b/src/qibocal/protocols/coherence/t1_signal.py index 74c13fc90..c3a8d28a6 100644 --- a/src/qibocal/protocols/coherence/t1_signal.py +++ b/src/qibocal/protocols/coherence/t1_signal.py @@ -4,15 +4,20 @@ import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine - +from qibolab import ( + AcquisitionType, + AveragingMode, + Delay, + Parameter, + PulseSequence, + Sweeper, +) + +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.result import magnitude, phase + +from ... import update from ..utils import table_dict, table_html from . import utils @@ -57,42 +62,35 @@ def average(self): return self +def t1_sequence(platform: CalibrationPlatform, targets: list[QubitId]): + """Create sequence for T1 experiment with a given optional delay.""" + sequence = PulseSequence() + ro_pulses, delays = {}, {} + for q in targets: + natives = platform.natives.single_qubit[q] + qd_channel, qd_pulse = natives.RX()[0] + ro_channel, ro_pulse = natives.MZ()[0] + + ro_pulses[q] = ro_pulse + delays[q] = Delay(duration=0) + + sequence.append((qd_channel, qd_pulse)) + sequence.append((ro_channel, Delay(duration=qd_pulse.duration))) + sequence.append((ro_channel, delays[q])) + sequence.append((ro_channel, ro_pulse)) + + return sequence, ro_pulses, delays + + def _acquisition( - params: T1SignalParameters, platform: Platform, targets: list[QubitId] + params: T1SignalParameters, platform: CalibrationPlatform, targets: list[QubitId] ) -> T1SignalData: - r"""Data acquisition for T1 experiment. - In a T1 experiment, we measure an excited qubit after a delay. Due to decoherence processes - (e.g. amplitude damping channel), it is possible that, at the time of measurement, after the delay, - the qubit will not be excited anymore. The larger the delay time is, the more likely is the qubit to - fall to the ground state. The goal of the experiment is to characterize the decay rate of the qubit - towards the ground state. - - Args: - params: - platform (Platform): Qibolab platform object - targets (list): list of target qubits to perform the action - delay_before_readout_start (int): Initial time delay before ReadOut - delay_before_readout_end (list): Maximum time delay before ReadOut - delay_before_readout_step (int): Scan range step for the delay before ReadOut - software_averages (int): Number of executions of the routine for averaging results - points (int): Save data results in a file every number of points - """ + """Data acquisition for T1 experiment. - # create a sequence of pulses for the experiment - # RX - wait t - MZ - qd_pulses = {} - ro_pulses = {} - sequence = PulseSequence() - for qubit in targets: - qd_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].duration - ) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) + In this protocol the y axis is the magnitude of signal in the IQ plane.""" + + sequence, ro_pulses, delays = t1_sequence(platform, targets) - # define the parameter to sweep and its range: - # wait time before readout ro_wait_range = np.arange( params.delay_before_readout_start, params.delay_before_readout_end, @@ -100,38 +98,35 @@ def _acquisition( ) sweeper = Sweeper( - Parameter.start, - ro_wait_range, - [ro_pulses[qubit] for qubit in targets], - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + values=ro_wait_range, + pulses=[delays[q] for q in targets], ) - # sweep the parameter - # execute the pulse sequence - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=( - AveragingMode.SINGLESHOT if params.single_shot else AveragingMode.CYCLIC - ), + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=( + AveragingMode.SINGLESHOT if params.single_shot else AveragingMode.CYCLIC ), - sweeper, ) data = T1SignalData() - for qubit in targets: - result = results[ro_pulses[qubit].serial] + + for q in targets: + result = results[ro_pulses[q].id] + signal = magnitude(result) if params.single_shot: - _waits = np.array(len(result.magnitude) * [ro_wait_range]) + _waits = np.array(len(signal) * [ro_wait_range]) else: _waits = ro_wait_range data.register_qubit( utils.CoherenceType, - (qubit), - dict(wait=_waits, signal=result.magnitude, phase=result.phase), + (q), + dict(wait=_waits, signal=signal, phase=phase(result)), ) return data @@ -207,7 +202,7 @@ def _plot(data: T1SignalData, target: QubitId, fit: T1SignalResults = None): return figures, fitting_report -def _update(results: T1SignalResults, platform: Platform, target: QubitId): +def _update(results: T1SignalResults, platform: CalibrationPlatform, target: QubitId): update.t1(results.t1[target], platform, target) diff --git a/src/qibocal/protocols/coherence/t2.py b/src/qibocal/protocols/coherence/t2.py index 0b2be1f16..7d8111249 100644 --- a/src/qibocal/protocols/coherence/t2.py +++ b/src/qibocal/protocols/coherence/t2.py @@ -2,16 +2,13 @@ from typing import Optional import numpy as np -import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform -from ..utils import table_dict, table_html +from ...result import probability +from ..ramsey.utils import ramsey_sequence from . import t1, t2_signal, utils @@ -43,60 +40,39 @@ class T2Data(t1.T1Data): def _acquisition( params: T2Parameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> T2Data: - """Data acquisition for Ramsey Experiment (detuned).""" - # create a sequence of pulses for the experiment - # RX90 - t - RX90 - MZ - ro_pulses = {} - RX90_pulses1 = {} - RX90_pulses2 = {} - sequence = PulseSequence() - for qubit in targets: - RX90_pulses1[qubit] = platform.create_RX90_pulse(qubit, start=0) - RX90_pulses2[qubit] = platform.create_RX90_pulse( - qubit, - start=RX90_pulses1[qubit].finish, - ) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=RX90_pulses2[qubit].finish - ) - sequence.add(RX90_pulses1[qubit]) - sequence.add(RX90_pulses2[qubit]) - sequence.add(ro_pulses[qubit]) + """Data acquisition for T2 experiment.""" - # define the parameter to sweep and its range: waits = np.arange( - # wait time between RX90 pulses params.delay_between_pulses_start, params.delay_between_pulses_end, params.delay_between_pulses_step, ) + sequence, delays = ramsey_sequence(platform, targets) + data = T2Data() sweeper = Sweeper( - Parameter.start, - waits, - [RX90_pulses2[qubit] for qubit in targets], - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + values=waits, + pulses=delays, ) - # execute the sweep - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ), - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, ) for qubit in targets: - probs = results[ro_pulses[qubit].serial].probability(state=1) + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[-1] + probs = probability(results[ro_pulse.id], state=1) errors = np.sqrt(probs * (1 - probs) / params.nshots) data.register_qubit( t1.CoherenceProbType, (qubit), dict(wait=waits, prob=probs, error=errors) @@ -115,80 +91,5 @@ def _fit(data: T2Data) -> T2Results: return T2Results(t2s, fitted_parameters, pcovs, chi2) -def _plot(data: T2Data, target: QubitId, fit: T2Results = None): - """Plotting function for Ramsey Experiment.""" - - figures = [] - fitting_report = "" - qubit_data = data[target] - waits = qubit_data.wait - probs = qubit_data.prob - error_bars = qubit_data.error - - fig = go.Figure( - [ - go.Scatter( - x=waits, - y=probs, - opacity=1, - name="Probability of 1", - showlegend=True, - legendgroup="Probability of 1", - mode="lines", - ), - go.Scatter( - x=np.concatenate((waits, waits[::-1])), - y=np.concatenate((probs + error_bars, (probs - error_bars)[::-1])), - fill="toself", - fillcolor=t1.COLORBAND, - line=dict(color=t1.COLORBAND_LINE), - showlegend=True, - name="Errors", - ), - ] - ) - - if fit is not None: - # add fitting trace - waitrange = np.linspace( - min(qubit_data.wait), - max(qubit_data.wait), - 2 * len(qubit_data), - ) - - params = fit.fitted_parameters[target] - fig.add_trace( - go.Scatter( - x=waitrange, - y=utils.exp_decay( - waitrange, - *params, - ), - name="Fit", - line=go.scatter.Line(dash="dot"), - ) - ) - fitting_report = table_html( - table_dict( - target, - [ - "T2 [ns]", - "chi2 reduced", - ], - [fit.t2[target], fit.chi2[target]], - display_error=True, - ) - ) - fig.update_layout( - showlegend=True, - xaxis_title="Time [ns]", - yaxis_title="Probability of State 1", - ) - - figures.append(fig) - - return figures, fitting_report - - -t2 = Routine(_acquisition, _fit, _plot, t2_signal._update) +t2 = Routine(_acquisition, _fit, utils.plot, t2_signal._update) """T2 Routine object.""" diff --git a/src/qibocal/protocols/coherence/t2_sequences.py b/src/qibocal/protocols/coherence/t2_sequences.py deleted file mode 100644 index 85a38159a..000000000 --- a/src/qibocal/protocols/coherence/t2_sequences.py +++ /dev/null @@ -1,79 +0,0 @@ -import numpy as np -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId - -from qibocal.auto.operation import Routine - -from .t2_signal import T2SignalData, T2SignalParameters, _fit, _plot, _update -from .utils import CoherenceType - - -def _acquisition( - params: T2SignalParameters, - platform: Platform, - targets: list[QubitId], -) -> T2SignalData: - """Data acquisition for Ramsey Experiment (detuned).""" - # create a sequence of pulses for the experiment - # RX90 - t - RX90 - MZ - ro_pulses = {} - RX90_pulses1 = {} - RX90_pulses2 = {} - sequence = PulseSequence() - for qubit in targets: - RX90_pulses1[qubit] = platform.create_RX90_pulse(qubit, start=0) - RX90_pulses2[qubit] = platform.create_RX90_pulse( - qubit, - start=RX90_pulses1[qubit].finish, - ) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=RX90_pulses2[qubit].finish - ) - sequence.add(RX90_pulses1[qubit]) - sequence.add(RX90_pulses2[qubit]) - sequence.add(ro_pulses[qubit]) - - # define the parameter to sweep and its range: - waits = np.arange( - # wait time between RX90 pulses - params.delay_between_pulses_start, - params.delay_between_pulses_end, - params.delay_between_pulses_step, - ) - - data = T2SignalData() - - # sweep the parameter - for wait in waits: - for qubit in targets: - RX90_pulses2[qubit].start = RX90_pulses1[qubit].finish + wait - ro_pulses[qubit].start = RX90_pulses2[qubit].finish - - # execute the pulse sequence - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - ) - for qubit in targets: - result = results[ro_pulses[qubit].serial] - data.register_qubit( - CoherenceType, - (qubit), - dict( - wait=np.array([wait]), - signal=np.array([result.magnitude]), - phase=np.array([result.phase]), - ), - ) - return data - - -t2_sequences = Routine(_acquisition, _fit, _plot, _update) -"""T2 Routine object.""" diff --git a/src/qibocal/protocols/coherence/t2_signal.py b/src/qibocal/protocols/coherence/t2_signal.py index 4c8ffc714..4f1a2dea4 100644 --- a/src/qibocal/protocols/coherence/t2_signal.py +++ b/src/qibocal/protocols/coherence/t2_signal.py @@ -3,15 +3,14 @@ import numpy as np import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper from qibocal import update -from qibocal.auto.operation import Parameters, Results, Routine +from qibocal.auto.operation import Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform +from ...result import magnitude, phase +from ..ramsey.utils import ramsey_sequence from ..utils import table_dict, table_html from . import t1_signal, t2, utils @@ -53,69 +52,54 @@ class T2SignalData(t1_signal.T1SignalData): def _acquisition( params: T2SignalParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> T2SignalData: - """Data acquisition for Ramsey Experiment (detuned).""" - # create a sequence of pulses for the experiment - # RX90 - t - RX90 - MZ - ro_pulses = {} - RX90_pulses1 = {} - RX90_pulses2 = {} - sequence = PulseSequence() - for qubit in targets: - RX90_pulses1[qubit] = platform.create_RX90_pulse(qubit, start=0) - RX90_pulses2[qubit] = platform.create_RX90_pulse( - qubit, - start=RX90_pulses1[qubit].finish, - ) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=RX90_pulses2[qubit].finish - ) - sequence.add(RX90_pulses1[qubit]) - sequence.add(RX90_pulses2[qubit]) - sequence.add(ro_pulses[qubit]) + """Data acquisition for T2 experiment. + + In this protocol the y axis is the magnitude of signal in the IQ plane. + + """ - # define the parameter to sweep and its range: waits = np.arange( - # wait time between RX90 pulses params.delay_between_pulses_start, params.delay_between_pulses_end, params.delay_between_pulses_step, ) + sequence, delays = ramsey_sequence(platform, targets) + + data = T2SignalData() + sweeper = Sweeper( - Parameter.start, - waits, - [RX90_pulses2[qubit] for qubit in targets], - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + values=waits, + pulses=delays, ) - # execute the sweep - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=( - AveragingMode.SINGLESHOT if params.single_shot else AveragingMode.CYCLIC - ), + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=( + AveragingMode.SINGLESHOT if params.single_shot else AveragingMode.CYCLIC ), - sweeper, ) - data = T2SignalData() - for qubit in targets: - result = results[ro_pulses[qubit].serial] + for q in targets: + ro_pulse = list(sequence.channel(platform.qubits[q].acquisition))[-1] + result = results[ro_pulse.id] + signal = magnitude(result) if params.single_shot: - _waits = np.array(len(result.magnitude) * [waits]) + _waits = np.array(len(signal) * [waits]) else: _waits = waits data.register_qubit( utils.CoherenceType, - (qubit), - dict(wait=_waits, signal=result.magnitude, phase=result.phase), + (q), + dict(wait=_waits, signal=signal, phase=phase(result)), ) return data @@ -191,7 +175,7 @@ def _plot(data: T2SignalData, target: QubitId, fit: T2SignalResults = None): return figures, fitting_report -def _update(results: T2SignalResults, platform: Platform, target: QubitId): +def _update(results: T2SignalResults, platform: CalibrationPlatform, target: QubitId): update.t2(results.t2[target], platform, target) diff --git a/src/qibocal/protocols/coherence/utils.py b/src/qibocal/protocols/coherence/utils.py index 099293daf..2054d2a86 100644 --- a/src/qibocal/protocols/coherence/utils.py +++ b/src/qibocal/protocols/coherence/utils.py @@ -1,15 +1,21 @@ import numpy as np +import plotly.graph_objects as go +from qibolab import Delay, Platform, PulseSequence from scipy.optimize import curve_fit +from qibocal.auto.operation import QubitId from qibocal.config import log -from ..utils import chi2_reduced +from ..utils import chi2_reduced, table_dict, table_html CoherenceType = np.dtype( [("wait", np.float64), ("signal", np.float64), ("phase", np.float64)] ) """Custom dtype for coherence routines.""" +COLORBAND = "rgba(0,100,80,0.2)" +COLORBAND_LINE = "rgba(255,255,255,0)" + def average_single_shots(data_type, single_shots): """Convert single shot acquisition results of signal routines to averaged. @@ -28,6 +34,57 @@ def average_single_shots(data_type, single_shots): return data +def dynamical_decoupling_sequence( + platform: Platform, + targets: list[QubitId], + wait: int = 0, + n: int = 1, + kind: str = "CPMG", +) -> tuple[PulseSequence, list[Delay]]: + """Create dynamical decoupling sequence. + + Two sequences are available: + - CP: RX90 (wait RX wait )^N RX90 + - CPMG: RX90 (wait RY wait )^N RX90 + """ + + assert kind in ["CPMG", "CP"], f"Unknown sequence {kind}, please use CP or CPMG" + sequence = PulseSequence() + all_delays = [] + for qubit in targets: + natives = platform.natives.single_qubit[qubit] + qd_channel, rx90_pulse = natives.R(theta=np.pi / 2)[0] + _, pulse = natives.R(phi=np.pi / 2)[0] if kind == "CPMG" else natives.RX()[0] + ro_channel, ro_pulse = natives.MZ()[0] + + drive_delays = 2 * n * [Delay(duration=wait)] + ro_delays = 2 * n * [Delay(duration=wait)] + + sequence.append((qd_channel, rx90_pulse)) + + for i in range(n): + sequence.append((qd_channel, drive_delays[2 * i])) + sequence.append((ro_channel, ro_delays[2 * i])) + sequence.append((qd_channel, pulse)) + sequence.append((qd_channel, drive_delays[2 * i + 1])) + sequence.append((ro_channel, ro_delays[2 * i + 1])) + + sequence.append((qd_channel, rx90_pulse)) + + sequence.append( + ( + ro_channel, + Delay(duration=2 * rx90_pulse.duration + n * pulse.duration), + ) + ) + + sequence.append((ro_channel, ro_pulse)) + all_delays.extend(drive_delays) + all_delays.extend(ro_delays) + + return sequence, all_delays + + def exp_decay(x, *p): return p[0] - p[1] * np.exp(-1 * x / p[2]) @@ -41,10 +98,7 @@ def exponential_fit(data, zeno=False): for qubit in qubits: voltages = data[qubit].signal - if zeno: - times = np.arange(1, len(data[qubit].signal) + 1) - else: - times = data[qubit].wait + times = data[qubit].wait try: y_max = np.max(voltages) @@ -72,7 +126,7 @@ def exponential_fit(data, zeno=False): ) popt = [ (y_max - y_min) * popt[0] + y_min, - (y_max - y_min) * popt[1] * np.exp(x_min * popt[2] / (x_max - x_min)), + (y_max - y_min) * popt[1] * np.exp(x_min / popt[2] / (x_max - x_min)), popt[2] * (x_max - x_min), ] fitted_parameters[qubit] = popt @@ -94,10 +148,8 @@ def exponential_fit_probability(data, zeno=False): pcovs = {} for qubit in qubits: - if zeno: - times = np.arange(1, len(data[qubit].signal) + 1) - else: - times = data[qubit].wait + + times = data[qubit].wait x_max = np.max(times) x_min = np.min(times) x = (times - x_min) / (x_max - x_min) @@ -123,9 +175,10 @@ def exponential_fit_probability(data, zeno=False): ) popt = [ popt[0], - popt[1] * np.exp(x_min * popt[2] / (x_max - x_min)), + popt[1] * np.exp(x_min / (x_max - x_min) / popt[2]), popt[2] * (x_max - x_min), ] + pcovs[qubit] = pcov.tolist() fitted_parameters[qubit] = popt dec = popt[2] @@ -143,3 +196,72 @@ def exponential_fit_probability(data, zeno=False): log.warning(f"Exponential decay fit failed for qubit {qubit} due to {e}") return decay, fitted_parameters, pcovs, chi2 + + +def plot(data, target: QubitId, fit=None) -> tuple[list[go.Figure], str]: + """Plotting function for spin-echo or CPMG protocol.""" + + figures = [] + fitting_report = "" + qubit_data = data[target] + waits = qubit_data.wait + probs = qubit_data.prob + error_bars = qubit_data.error + + fig = go.Figure( + [ + go.Scatter( + x=waits, + y=probs, + opacity=1, + name="Probability of 1", + showlegend=True, + legendgroup="Probability of 1", + mode="lines", + ), + go.Scatter( + x=np.concatenate((waits, waits[::-1])), + y=np.concatenate((probs + error_bars, (probs - error_bars)[::-1])), + fill="toself", + fillcolor=COLORBAND, + line=dict(color=COLORBAND_LINE), + showlegend=True, + name="Errors", + ), + ] + ) + + if fit is not None: + waitrange = np.linspace( + min(waits), + max(waits), + 2 * len(qubit_data), + ) + params = fit.fitted_parameters[target] + + fig.add_trace( + go.Scatter( + x=waitrange, + y=exp_decay(waitrange, *params), + name="Fit", + line=go.scatter.Line(dash="dot"), + ), + ) + fitting_report = table_html( + table_dict( + target, + ["T2", "chi2 reduced"], + [fit.t2[target], fit.chi2[target]], + display_error=True, + ) + ) + + fig.update_layout( + showlegend=True, + xaxis_title="Time [ns]", + yaxis_title="Probability of State 1", + ) + + figures.append(fig) + + return figures, fitting_report diff --git a/src/qibocal/protocols/coherence/zeno.py b/src/qibocal/protocols/coherence/zeno.py index 42561b60c..50b4e7eb4 100644 --- a/src/qibocal/protocols/coherence/zeno.py +++ b/src/qibocal/protocols/coherence/zeno.py @@ -3,40 +3,67 @@ import numpy as np import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, AveragingMode, PulseSequence, Readout -from qibocal.auto.operation import Routine +from qibocal import update +from qibocal.auto.operation import Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform -from ..utils import table_dict, table_html +from ...result import probability +from ..utils import COLORBAND, COLORBAND_LINE, table_dict, table_html from . import t1, utils -from .zeno_signal import ZenoSignalParameters, ZenoSignalResults, _update @dataclass -class ZenoParameters(ZenoSignalParameters): +class ZenoParameters(Parameters): """Zeno runcard inputs.""" - -@dataclass -class ZenoData(t1.T1Data): - readout_duration: dict[QubitId, float] = field(default_factory=dict) - """Readout durations for each qubit""" + readouts: int + "Number of readout pulses" @dataclass -class ZenoResults(ZenoSignalResults): +class ZenoResults(Results): """Zeno outputs.""" + zeno_t1: dict[QubitId, int] + """T1 for each qubit.""" + fitted_parameters: dict[QubitId, dict[str, float]] + """Raw fitting output.""" + pcov: dict[QubitId, list[float]] + """Approximate covariance of fitted parameters.""" chi2: dict[QubitId, tuple[float, Optional[float]]] """Chi squared estimate mean value and error.""" +def zeno_sequence( + platform: CalibrationPlatform, targets: list[QubitId], readouts: int +) -> tuple[PulseSequence, dict[QubitId, int]]: + """Generating sequence for Zeno experiment.""" + + sequence = PulseSequence() + readout_duration = {} + for q in targets: + natives = platform.natives.single_qubit[q] + _, ro_pulse = natives.MZ()[0] + readout_duration[q] = ro_pulse.duration + qubit_sequence = natives.RX() | natives.MZ() + for _ in range(readouts - 1): + qubit_sequence += natives.MZ() + sequence += qubit_sequence + + return sequence, readout_duration + + +@dataclass +class ZenoData(t1.T1Data): + readout_duration: dict[QubitId, float] = field(default_factory=dict) + """Readout durations for each qubit""" + + def _acquisition( params: ZenoParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> ZenoData: """ @@ -48,50 +75,39 @@ def _acquisition( Reference: https://link.aps.org/accepted/10.1103/PhysRevLett.118.240401. """ - # create sequence of pulses: - sequence = PulseSequence() - RX_pulses = {} - ro_pulses = {} - ro_pulse_duration = {} - for qubit in targets: - RX_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - sequence.add(RX_pulses[qubit]) - start = RX_pulses[qubit].finish - ro_pulses[qubit] = [] - for _ in range(params.readouts): - ro_pulse = platform.create_qubit_readout_pulse(qubit, start=start) - start += ro_pulse.duration - sequence.add(ro_pulse) - ro_pulses[qubit].append(ro_pulse) - ro_pulse_duration[qubit] = ro_pulse.duration - - # create a DataUnits object to store the results - data = ZenoData(readout_duration=ro_pulse_duration) - - # execute the first pulse sequence - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ), + sequence, readout_duration = zeno_sequence( + platform, targets, readouts=params.readouts + ) + data = ZenoData(readout_duration=readout_duration) + + results = platform.execute( + [sequence], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, ) - # retrieve and store the results for every qubit - probs = {qubit: [] for qubit in targets} for qubit in targets: - for ro_pulse in ro_pulses[qubit]: - probs[qubit].append(results[ro_pulse.serial].probability(state=1)) - errors = [np.sqrt(prob * (1 - prob) / params.nshots) for prob in probs[qubit]] + probs = [] + readouts = [ + pulse + for pulse in sequence.channel(platform.qubits[qubit].acquisition) + if isinstance(pulse, Readout) + ] + for i in range(params.readouts): + ro_pulse = readouts[i] + probs.append(probability(results[ro_pulse.id], state=1)) + data.register_qubit( t1.CoherenceProbType, (qubit), dict( - wait=np.arange(1, len(probs[qubit]) + 1), - prob=probs[qubit], - error=errors, + wait=np.arange(params.readouts) + 1, + prob=np.array(probs), + error=np.array( + [np.sqrt(prob * (1 - prob) / params.nshots) for prob in probs] + ), ), ) return data @@ -117,7 +133,7 @@ def _plot(data: ZenoData, fit: ZenoResults, target: QubitId): qubit_data = data[target] probs = qubit_data.prob error_bars = qubit_data.error - readouts = np.arange(1, len(qubit_data.prob) + 1) + readouts = qubit_data.wait fig = go.Figure( [ @@ -134,8 +150,8 @@ def _plot(data: ZenoData, fit: ZenoResults, target: QubitId): x=np.concatenate((readouts, readouts[::-1])), y=np.concatenate((probs + error_bars, (probs - error_bars)[::-1])), fill="toself", - fillcolor=t1.COLORBAND, - line=dict(color=t1.COLORBAND_LINE), + fillcolor=COLORBAND, + line=dict(color=COLORBAND_LINE), showlegend=True, name="Errors", ), @@ -163,8 +179,8 @@ def _plot(data: ZenoData, fit: ZenoResults, target: QubitId): target, ["T1 [ns]", "Readout Pulse [ns]", "chi2 reduced"], [ - fit.zeno_t1[target], np.array(fit.zeno_t1[target]) * data.readout_duration[target], + (data.readout_duration[target], 0), fit.chi2[target], ], display_error=True, @@ -184,4 +200,8 @@ def _plot(data: ZenoData, fit: ZenoResults, target: QubitId): return figures, fitting_report +def _update(results: ZenoResults, platform: CalibrationPlatform, qubit: QubitId): + update.t1(results.zeno_t1[qubit], platform, qubit) + + zeno = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/coherence/zeno_signal.py b/src/qibocal/protocols/coherence/zeno_signal.py deleted file mode 100644 index 1d0240eeb..000000000 --- a/src/qibocal/protocols/coherence/zeno_signal.py +++ /dev/null @@ -1,194 +0,0 @@ -from dataclasses import dataclass, field - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId - -from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine - -from ..utils import table_dict, table_html -from . import utils - - -@dataclass -class ZenoSignalParameters(Parameters): - """Zeno runcard inputs.""" - - readouts: int - "Number of readout pulses" - - -ZenoSignalType = np.dtype([("signal", np.float64), ("phase", np.float64)]) -"""Custom dtype for Zeno.""" - - -@dataclass -class ZenoSignalData(Data): - - readout_duration: dict[QubitId, float] = field(default_factory=dict) - """Readout durations for each qubit""" - data: dict[QubitId, npt.NDArray] = field(default_factory=dict) - """Raw data acquired.""" - - def register_qubit(self, qubit, signal, phase): - """Store output for single qubit.""" - ar = np.empty((1,), dtype=ZenoSignalType) - ar["signal"] = signal - ar["phase"] = phase - if qubit in self.data: - self.data[qubit] = np.rec.array(np.concatenate((self.data[qubit], ar))) - else: - self.data[qubit] = np.rec.array(ar) - - -@dataclass -class ZenoSignalResults(Results): - """Zeno outputs.""" - - zeno_t1: dict[QubitId, int] - """T1 for each qubit.""" - fitted_parameters: dict[QubitId, dict[str, float]] - """Raw fitting output.""" - pcov: dict[QubitId, list[float]] - """Approximate covariance of fitted parameters.""" - - -def _acquisition( - params: ZenoSignalParameters, - platform: Platform, - targets: list[QubitId], -) -> ZenoSignalData: - """ - In a T1_Zeno experiment, we measure an excited qubit repeatedly. Due to decoherence processes, - it is possible that, at the time of measurement, the qubit will not be excited anymore. - The quantum zeno effect consists of measuring allowing a particle's time evolution to be slowed - down by measuring it frequently enough. However, in the experiments we see that due the QND-ness of the readout - pulse that the qubit decoheres faster. - Reference: https://link.aps.org/accepted/10.1103/PhysRevLett.118.240401. - """ - - # create sequence of pulses: - sequence = PulseSequence() - RX_pulses = {} - ro_pulses = {} - ro_pulse_duration = {} - for qubit in targets: - RX_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - sequence.add(RX_pulses[qubit]) - start = RX_pulses[qubit].finish - ro_pulses[qubit] = [] - for _ in range(params.readouts): - ro_pulse = platform.create_qubit_readout_pulse(qubit, start=start) - start += ro_pulse.duration - sequence.add(ro_pulse) - ro_pulses[qubit].append(ro_pulse) - ro_pulse_duration[qubit] = ro_pulse.duration - - # create a DataUnits object to store the results - data = ZenoSignalData(readout_duration=ro_pulse_duration) - - # execute the first pulse sequence - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - ) - - # retrieve and store the results for every qubit - for qubit in targets: - for ro_pulse in ro_pulses[qubit]: - result = results[ro_pulse.serial] - data.register_qubit( - qubit=qubit, signal=result.magnitude, phase=result.phase - ) - return data - - -def _fit(data: ZenoSignalData) -> ZenoSignalResults: - """ - Fitting routine for T1 experiment. The used model is - - .. math:: - - y = p_0-p_1 e^{-x p_2}. - """ - - t1s, fitted_parameters, pcovs = utils.exponential_fit(data, zeno=True) - - return ZenoSignalResults(t1s, fitted_parameters, pcovs) - - -def _plot(data: ZenoSignalData, fit: ZenoSignalResults, target: QubitId): - """Plotting function for T1 experiment.""" - figures = [] - fig = go.Figure() - - fitting_report = "" - qubit_data = data[target] - readouts = np.arange(1, len(qubit_data.signal) + 1) - - fig.add_trace( - go.Scatter( - x=readouts, - y=qubit_data.signal, - opacity=1, - name="Signal", - showlegend=True, - legendgroup="Signal", - ) - ) - - if fit is not None: - fitting_report = "" - waitrange = np.linspace( - min(readouts), - max(readouts), - 2 * len(qubit_data), - ) - params = fit.fitted_parameters[target] - fig.add_trace( - go.Scatter( - x=waitrange, - y=utils.exp_decay(waitrange, *params), - name="Fit", - line=go.scatter.Line(dash="dot"), - ) - ) - fitting_report = table_html( - table_dict( - target, - ["T1", "Readout Pulse"], - [ - np.round(fit.zeno_t1[target]), - np.round(fit.zeno_t1[target] * data.readout_duration[target]), - ], - ) - ) - # FIXME: Pulse duration (+ time of flight ?) - - # last part - fig.update_layout( - showlegend=True, - xaxis_title="Number of readouts", - yaxis_title="Signal [a.u.]", - ) - - figures.append(fig) - - return figures, fitting_report - - -def _update(results: ZenoSignalResults, platform: Platform, qubit: QubitId): - update.t1(results.zeno_t1[qubit], platform, qubit) - - -zeno_signal = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/couplers/__init__.py b/src/qibocal/protocols/couplers/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/src/qibocal/protocols/couplers/coupler_chevron.py b/src/qibocal/protocols/couplers/coupler_chevron.py deleted file mode 100644 index dc69a71a9..000000000 --- a/src/qibocal/protocols/couplers/coupler_chevron.py +++ /dev/null @@ -1,141 +0,0 @@ -import numpy as np -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence, PulseType -from qibolab.qubits import QubitPairId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal.auto.operation import Results, Routine - -from ..two_qubit_interaction.chevron.chevron import ( - ChevronData, - ChevronParameters, - _plot, -) -from ..two_qubit_interaction.utils import order_pair - - -def _acquisition( - params: ChevronParameters, - platform: Platform, - targets: list[QubitPairId], -) -> ChevronData: - r""" - Perform an CZ experiment between pairs of qubits by changing the coupler state, - qubits need to be pulses into their interaction point. - - Args: - platform: Platform to use. - params: Experiment parameters. - targets (list): List of pairs to use sequentially. - - Returns: - ChevronData: Acquisition data. - """ - # define the parameter to sweep and its range: - delta_amplitude_range = np.arange( - params.amplitude_min_factor, - params.amplitude_max_factor, - params.amplitude_step_factor, - ) - delta_duration_range = np.arange( - params.duration_min, params.duration_max, params.duration_step - ) - - data = ChevronData() - for pair in targets: - sequence = PulseSequence() - - ordered_pair = order_pair(pair, platform) - - # initialize system to state 11(CZ) or 10(iSWAP) - if params.native == "CZ": - initialize_lowfreq = platform.create_RX_pulse(ordered_pair[0], start=0) - sequence.add(initialize_lowfreq) - - initialize_highfreq = platform.create_RX_pulse(ordered_pair[1], start=0) - - sequence.add(initialize_highfreq) - - if params.native == "CZ": - native_gate, _ = platform.create_CZ_pulse_sequence( - (ordered_pair[1], ordered_pair[0]), - start=sequence.finish + params.dt, - ) - elif params.native == "iSWAP": - native_gate, _ = platform.create_iSWAP_pulse_sequence( - (ordered_pair[1], ordered_pair[0]), - start=sequence.finish + params.dt, - ) - data.native_amplitude[ordered_pair] = getattr( - native_gate.coupler_pulses(*pair)[:1][0], "amplitude" - ) - sequence.add(native_gate) - - ro_pulse1 = platform.create_MZ_pulse( - ordered_pair[1], start=sequence.finish + params.dt - ) - ro_pulse2 = platform.create_MZ_pulse( - ordered_pair[0], start=sequence.finish + params.dt - ) - - sequence += ro_pulse1 + ro_pulse2 - - coupler_flux_pulses = [p for p in native_gate.coupler_pulses(*pair)] - assert ( - len(coupler_flux_pulses) == 1 - ), f"coupler_chevron expects exactly one coupler flux pulse, but {len(coupler_flux_pulses)} are present." - qubit_flux_pulses = [ - p for p in native_gate.get_qubit_pulses(*pair) if p.type is PulseType.FLUX - ] - assert all( - len(list(filter(lambda x: x.qubit == q, qubit_flux_pulses))) < 2 - for q in pair - ), f"coupler_chevron expects no more than 1 flux pulse for each qubit, but more are present for the pair {pair}" - sweeper_amplitude = Sweeper( - Parameter.amplitude, - delta_amplitude_range, - pulses=coupler_flux_pulses, - type=SweeperType.FACTOR, - ) - sweeper_duration = Sweeper( - Parameter.duration, - delta_duration_range, - pulses=coupler_flux_pulses + qubit_flux_pulses, - ) - - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper_duration, - sweeper_amplitude, - ) - - data.register_qubit( - ordered_pair[0], - ordered_pair[1], - delta_duration_range, - delta_amplitude_range * data.native_amplitude[ordered_pair], - results[ordered_pair[0]].probability(state=1), - results[ordered_pair[1]].probability(state=1), - ) - data.label = "Probability of state |1>" - - return data - - -def _fit(data: ChevronData) -> Results: - """Results for ChevronCouplers.""" - return Results() - - -def plot(data: ChevronData, fit: Results, target): - return _plot(data, None, target) - - -coupler_chevron = Routine(_acquisition, _fit, plot, two_qubit_gates=True) -"""Coupler cz/swap flux routine.""" diff --git a/src/qibocal/protocols/couplers/coupler_qubit_spectroscopy.py b/src/qibocal/protocols/couplers/coupler_qubit_spectroscopy.py deleted file mode 100644 index 8b5cb1c15..000000000 --- a/src/qibocal/protocols/couplers/coupler_qubit_spectroscopy.py +++ /dev/null @@ -1,132 +0,0 @@ -from typing import Optional - -import numpy as np -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitPairId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal.auto.operation import Routine - -from ..two_qubit_interaction.utils import order_pair -from .coupler_resonator_spectroscopy import _fit, _plot, _update -from .utils import CouplerSpectroscopyData, CouplerSpectroscopyParameters - - -class CouplerSpectroscopyParametersQubit(CouplerSpectroscopyParameters): - drive_duration: Optional[int] = 2000 - """Drive pulse duration to excite the qubit before the measurement""" - - -def _acquisition( - params: CouplerSpectroscopyParametersQubit, - platform: Platform, - targets: list[QubitPairId], -) -> CouplerSpectroscopyData: - """ - Data acquisition for CouplerQubit spectroscopy. - - This consist on a frequency sweep on the qubit frequency while we change the flux coupler pulse amplitude of - the coupler pulse. We expect to enable the coupler during the amplitude sweep and detect an avoided crossing - that will be followed by the frequency sweep. This needs the qubits at resonance, the routine assumes a sweetspot - value for the higher frequency qubit that moves it to the lower frequency qubit instead of trying to calibrate both pulses at once. This should be run after - qubit_spectroscopy to further adjust the coupler sweetspot if needed and get some information - on the flux coupler pulse amplitude requiered to enable 2q interactions. - - """ - - # TODO: Do we want to measure both qubits on the pair ? - - # create a sequence of pulses for the experiment: - # Coupler pulse while Drive pulse - MZ - - if params.measured_qubits is None: - params.measured_qubits = [order_pair(pair, platform)[0] for pair in targets] - - sequence = PulseSequence() - ro_pulses = {} - qd_pulses = {} - offset = {} - couplers = [] - for i, pair in enumerate(targets): - ordered_pair = order_pair(pair, platform) - measured_qubit = params.measured_qubits[i] - - qubit = platform.qubits[measured_qubit].name - offset[qubit] = platform.pairs[tuple(sorted(ordered_pair))].coupler.sweetspot - coupler = platform.pairs[tuple(sorted(ordered_pair))].coupler.name - couplers.append(coupler) - - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=params.drive_duration - ) - qd_pulses[qubit] = platform.create_qubit_drive_pulse( - qubit, start=0, duration=params.drive_duration - ) - if params.amplitude is not None: - qd_pulses[qubit].amplitude = params.amplitude - - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - - # define the parameter to sweep and its range: - delta_frequency_range = np.arange( - -params.freq_width / 2, params.freq_width / 2, params.freq_step - ) - - sweeper_freq = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[qd_pulses[qubit] for qubit in params.measured_qubits], - type=SweeperType.OFFSET, - ) - - delta_bias_range = np.arange( - -params.bias_width / 2, params.bias_width / 2, params.bias_step - ) - sweepers = [ - Sweeper( - Parameter.bias, - delta_bias_range, - qubits=couplers, - type=SweeperType.OFFSET, - ) - ] - - data = CouplerSpectroscopyData( - resonator_type=platform.resonator_type, - offset=offset, - ) - - for bias_sweeper in sweepers: - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - bias_sweeper, - sweeper_freq, - ) - - # retrieve the results for every qubit - for i, pair in enumerate(targets): - # TODO: May measure both qubits on the pair - qubit = platform.qubits[params.measured_qubits[i]].name - result = results[ro_pulses[qubit].serial] - # store the results - data.register_qubit( - qubit, - signal=result.magnitude, - phase=result.phase, - freq=delta_frequency_range + qd_pulses[qubit].frequency, - bias=delta_bias_range, - ) - return data - - -coupler_qubit_spectroscopy = Routine(_acquisition, _fit, _plot, _update) -"""CouplerQubitSpectroscopy Routine object.""" diff --git a/src/qibocal/protocols/couplers/coupler_resonator_spectroscopy.py b/src/qibocal/protocols/couplers/coupler_resonator_spectroscopy.py deleted file mode 100644 index 9848a2a8c..000000000 --- a/src/qibocal/protocols/couplers/coupler_resonator_spectroscopy.py +++ /dev/null @@ -1,172 +0,0 @@ -import numpy as np -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitPairId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal.auto.operation import Routine - -from ..flux_dependence.utils import flux_dependence_plot -from ..two_qubit_interaction.utils import order_pair -from .utils import ( - CouplerSpectroscopyData, - CouplerSpectroscopyParameters, - CouplerSpectroscopyResults, -) - - -def _acquisition( - params: CouplerSpectroscopyParameters, - platform: Platform, - targets: list[QubitPairId], -) -> CouplerSpectroscopyData: - """ - Data acquisition for CouplerResonator spectroscopy. - - This consist on a frequency sweep on the readout frequency while we change the flux coupler pulse amplitude of - the coupler pulse. We expect to enable the coupler during the amplitude sweep and detect an avoided crossing - that will be followed by the frequency sweep. No need to have the qubits at resonance. This should be run after - resonator_spectroscopy to detect couplers and adjust the coupler sweetspot if needed and get some information - on the flux coupler pulse amplitude requiered to enable 2q interactions. - - """ - - # TODO: Do we want to measure both qubits on the pair ? - - # create a sequence of pulses for the experiment: - # Coupler pulse while MZ - - if params.measured_qubits is None: - params.measured_qubits = [order_pair(pair, platform)[0] for pair in targets] - - sequence = PulseSequence() - ro_pulses = {} - offset = {} - couplers = [] - for i, pair in enumerate(targets): - ordered_pair = order_pair(pair, platform) - measured_qubit = params.measured_qubits[i] - - qubit = platform.qubits[measured_qubit].name - offset[qubit] = platform.pairs[tuple(sorted(ordered_pair))].coupler.sweetspot - coupler = platform.pairs[tuple(sorted(ordered_pair))].coupler.name - couplers.append(coupler) - # TODO: May measure both qubits on the pair - ro_pulses[qubit] = platform.create_qubit_readout_pulse(qubit, start=0) - if params.amplitude is not None: - ro_pulses[qubit].amplitude = params.amplitude - - sequence.add(ro_pulses[qubit]) - - # define the parameter to sweep and its range: - delta_frequency_range = np.arange( - -params.freq_width / 2, params.freq_width / 2, params.freq_step - ) - - sweeper_freq = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[ro_pulses[qubit] for qubit in params.measured_qubits], - type=SweeperType.OFFSET, - ) - - delta_bias_range = np.arange( - -params.bias_width / 2, params.bias_width / 2, params.bias_step - ) - sweepers = [ - Sweeper( - Parameter.bias, - delta_bias_range, - qubits=couplers, - type=SweeperType.OFFSET, - ) - ] - - data = CouplerSpectroscopyData( - resonator_type=platform.resonator_type, - offset=offset, - ) - - for bias_sweeper in sweepers: - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - bias_sweeper, - sweeper_freq, - ) - - # retrieve the results for every qubit - for i, pair in enumerate(targets): - # TODO: May measure both qubits on the pair - qubit = platform.qubits[params.measured_qubits[i]].name - result = results[ro_pulses[qubit].serial] - # store the results - data.register_qubit( - qubit, - signal=result.magnitude, - phase=result.phase, - freq=delta_frequency_range + ro_pulses[qubit].frequency, - bias=delta_bias_range, - ) - return data - - -def _fit(data: CouplerSpectroscopyData) -> CouplerSpectroscopyResults: - """Post-processing function for CouplerResonatorSpectroscopy.""" - qubits = data.qubits - pulse_amp = {} - sweetspot = {} - fitted_parameters = {} - - # TODO: Implement fit - """It should get two things: - Coupler sweetspot: the value that makes both features centered and symmetric - Pulse_amp: That turn on the feature taking into account the shift introduced by the coupler sweetspot - """ - - return CouplerSpectroscopyResults( - pulse_amp=pulse_amp, - sweetspot=sweetspot, - fitted_parameters=fitted_parameters, - ) - - -def _plot( - data: CouplerSpectroscopyData, - target: QubitPairId, - fit: CouplerSpectroscopyResults, -): - """ - We may want to measure both qubits on the pair, - that will require a different plotting that takes both. - """ - qubit_pair = target # TODO: Patch for 2q gate routines - - for qubit in qubit_pair: - if qubit in data.data.keys(): - fig = flux_dependence_plot(data, fit, qubit)[0] - - fig.layout.annotations[0].update( - text="Signal [a.u.] Qubit" + str(qubit), - ) - fig.layout.annotations[1].update( - text="Phase [rad] Qubit" + str(qubit), - ) - - return [fig], "" - - -def _update( - results: CouplerSpectroscopyResults, platform: Platform, target: QubitPairId -): - pass - - -coupler_resonator_spectroscopy = Routine(_acquisition, _fit, _plot, _update) -"""CouplerResonatorSpectroscopy Routine object.""" diff --git a/src/qibocal/protocols/couplers/utils.py b/src/qibocal/protocols/couplers/utils.py deleted file mode 100644 index 9e2648dce..000000000 --- a/src/qibocal/protocols/couplers/utils.py +++ /dev/null @@ -1,63 +0,0 @@ -from dataclasses import dataclass, field -from typing import Optional, Union - -import numpy as np -import numpy.typing as npt -from qibolab.qubits import QubitId - -from qibocal.auto.operation import Data, Results - -from ..flux_dependence.resonator_flux_dependence import ResonatorFluxParameters -from ..flux_dependence.utils import create_data_array - - -@dataclass -class CouplerSpectroscopyParameters(ResonatorFluxParameters): - """CouplerResonatorSpectroscopy and CouplerQubitSpectroscopy runcard inputs.""" - - measured_qubits: Optional[list[QubitId]] = None - """Qubit to measure from the pair""" - amplitude: Optional[Union[int, float]] = None - """Readout or qubit drive amplitude (optional). If defined, same amplitude will be used in all qubits. - Otherwise the default amplitude defined on the platform runcard will be used""" - - -CouplerSpecType = np.dtype( - [ - ("freq", np.float64), - ("bias", np.float64), - ("signal", np.float64), - ("phase", np.float64), - ] -) -"""Custom dtype for coupler resonator spectroscopy.""" - - -@dataclass -class CouplerSpectroscopyResults(Results): - """CouplerResonatorSpectroscopy or CouplerQubitSpectroscopy outputs.""" - - sweetspot: dict[QubitId, float] - """Sweetspot for each coupler.""" - pulse_amp: dict[QubitId, float] - """Pulse amplitude for the coupler.""" - fitted_parameters: dict[QubitId, dict[str, float]] - """Raw fitted parameters.""" - - -@dataclass -class CouplerSpectroscopyData(Data): - """Data structure for CouplerResonatorSpectroscopy or CouplerQubitSpectroscopy.""" - - resonator_type: str - """Resonator type.""" - offset: dict[QubitId, float] = field(default_factory=dict) - """Qubit bias offset.""" - data: dict[QubitId, npt.NDArray[CouplerSpecType]] = field(default_factory=dict) - """Raw data acquired.""" - - def register_qubit(self, qubit, freq, bias, signal, phase): - """Store output for single qubit.""" - self.data[qubit] = create_data_array( - freq, bias, signal, phase, dtype=CouplerSpecType - ) diff --git a/src/qibocal/protocols/dispersive_shift.py b/src/qibocal/protocols/dispersive_shift.py index a022709ec..3a63792f8 100644 --- a/src/qibocal/protocols/dispersive_shift.py +++ b/src/qibocal/protocols/dispersive_shift.py @@ -4,14 +4,11 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, PulseSequence, Sweeper from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.protocols.utils import ( HZ_TO_GHZ, lorentzian, @@ -20,6 +17,8 @@ table_html, ) +from ..result import magnitude, phase, unpack + @dataclass class DispersiveShiftParameters(Parameters): @@ -74,7 +73,9 @@ class DispersiveShiftData(Data): def _acquisition( - params: DispersiveShiftParameters, platform: Platform, targets: list[QubitId] + params: DispersiveShiftParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> DispersiveShiftData: r""" Data acquisition for dispersive shift experiment. @@ -83,75 +84,57 @@ def _acquisition( Args: params (DispersiveShiftParameters): experiment's parameters - platform (Platform): Qibolab platform object + platform (CalibrationPlatform): Qibolab platform object targets (list): list of target qubits to perform the action - """ - # create 2 sequences of pulses for the experiment: - # sequence_0: I - MZ - # sequence_1: RX - MZ - - # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel sequence_0 = PulseSequence() sequence_1 = PulseSequence() - ro_pulses = {} - qd_pulses = {} for qubit in targets: - qd_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].duration - ) - sequence_0.add(ro_pulses[qubit]) - sequence_1.add(qd_pulses[qubit]) - sequence_1.add(ro_pulses[qubit]) + natives = platform.natives.single_qubit[qubit] + sequence_0 += natives.MZ() + sequence_1 += natives.RX() | natives.MZ() - # define the parameter to sweep and its range: delta_frequency_range = np.arange( -params.freq_width / 2, params.freq_width / 2, params.freq_step ) - # create a DataUnits objects to store the results data = DispersiveShiftData(resonator_type=platform.resonator_type) - sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[ro_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - execution_pars = ExecutionParameters( + sweepers = [ + Sweeper( + parameter=Parameter.frequency, + values=platform.config(platform.qubits[q].probe).frequency + + delta_frequency_range, + channels=[platform.qubits[q].probe], + ) + for q in targets + ] + + results = platform.execute( + [sequence_0, sequence_1], + [sweepers], nshots=params.nshots, relaxation_time=params.relaxation_time, acquisition_type=AcquisitionType.INTEGRATION, averaging_mode=AveragingMode.CYCLIC, ) - results_0 = platform.sweep( - sequence_0, - execution_pars, - sweeper, - ) - - results_1 = platform.sweep( - sequence_1, - execution_pars, - sweeper, - ) - # retrieve the results for every qubit for qubit in targets: - for i, results in enumerate([results_0, results_1]): - result = results[ro_pulses[qubit].serial].average - # store the results + ro_frequency = platform.config(platform.qubits[qubit].probe).frequency + for state, sequence in enumerate([sequence_0, sequence_1]): + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[-1] + result = results[ro_pulse.id] + i, q = unpack(result) data.register_qubit( DispersiveShiftType, - (qubit, i), + (qubit, state), dict( - freq=ro_pulses[qubit].frequency + delta_frequency_range, - signal=result.magnitude, - phase=result.phase, - i=result.voltage_i, - q=result.voltage_q, + freq=ro_frequency + delta_frequency_range, + signal=magnitude(result), + phase=phase(result), + i=i, + q=q, ), ) return data @@ -335,12 +318,23 @@ def _plot(data: DispersiveShiftData, target: QubitId, fit: DispersiveShiftResult return figures, fitting_report -def _update(results: DispersiveShiftResults, platform: Platform, target: QubitId): +def _update( + results: DispersiveShiftResults, platform: CalibrationPlatform, target: QubitId +): update.readout_frequency(results.best_freq[target], platform, target) if results.frequencies[target] is not None: - delta = platform.qubits[target].drive_frequency - results.frequencies[target][0] + delta = ( + platform.calibration.single_qubits[target].qubit.frequency_01 + - results.frequencies[target][0] + ) g = np.sqrt(np.abs(results.chi(target) * delta)) update.coupling(g, platform, target) + update.dressed_resonator_frequency( + results.frequencies[target][0], platform, target + ) + platform.calibration.single_qubits[target].readout.qudits_frequency[1] = ( + results.frequencies[target][1] + ) dispersive_shift = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/dispersive_shift_qutrit.py b/src/qibocal/protocols/dispersive_shift_qutrit.py index 79545826c..0ce0f09c8 100644 --- a/src/qibocal/protocols/dispersive_shift_qutrit.py +++ b/src/qibocal/protocols/dispersive_shift_qutrit.py @@ -1,16 +1,12 @@ -from copy import deepcopy from dataclasses import asdict, dataclass import numpy as np import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, PulseSequence, Sweeper -from qibocal.auto.operation import Results, Routine +from qibocal.auto.operation import QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.protocols.utils import ( GHZ_TO_HZ, HZ_TO_GHZ, @@ -20,6 +16,7 @@ table_html, ) +from ..result import magnitude, phase from .dispersive_shift import DispersiveShiftData, DispersiveShiftParameters from .resonator_spectroscopy import ResSpecType @@ -68,40 +65,37 @@ class DispersiveShiftQutritData(DispersiveShiftData): def _acquisition( - params: DispersiveShiftParameters, platform: Platform, targets: list[QubitId] + params: DispersiveShiftParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> DispersiveShiftQutritData: r""" - Data acquisition for dispersive shift experiment. - Perform spectroscopy on the readout resonator, with the qubit in ground and excited state, showing - the resonator shift produced by the coupling between the resonator and the qubit. + Data acquisition for dispersive shift qutrit experiment. + Perform spectroscopy on the readout resonator, with the qubit in ground, excited state and + second excited state showing the resonator shift produced by the coupling between the resonator and the qubit. Args: params (DispersiveShiftParameters): experiment's parameters - platform (Platform): Qibolab platform object + platform (CalibrationPlatform): Qibolab platform object targets (list): list of target qubits to perform the action """ - # create 3 sequences of pulses for the experiment: - # sequence_0: I - MZ - # sequence_1: RX - MZ - # sequence_2: RX - RX12 - MZ - - # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel sequence_0 = PulseSequence() sequence_1 = PulseSequence() sequence_2 = PulseSequence() for qubit in targets: - rx_pulse = platform.create_RX_pulse(qubit, start=0) - rx_12_pulse = platform.create_RX12_pulse(qubit, start=rx_pulse.finish) - ro_pulse = platform.create_qubit_readout_pulse(qubit, start=0) - sequence_1.add(rx_pulse) - sequence_2.add(rx_pulse, rx_12_pulse) - for sequence in [sequence_0, sequence_1, sequence_2]: - readout_pulse = deepcopy(ro_pulse) - readout_pulse.start = sequence.qd_pulses.finish - sequence.add(readout_pulse) + natives = platform.natives.single_qubit[qubit] + # prepare 0 and measure + sequence_0 += natives.MZ() + + # prepare 1 and measure + sequence_1 += natives.RX() | natives.MZ() + + # prepare 2 and measure + assert natives.RX12 is not None, f"Missing RX12 calibration for qubit {qubit}" + sequence_2 += (natives.RX() + natives.RX12()) | natives.MZ() # define the parameter to sweep and its range: delta_frequency_range = np.arange( @@ -110,36 +104,37 @@ def _acquisition( data = DispersiveShiftQutritData(resonator_type=platform.resonator_type) - for state, sequence in enumerate([sequence_0, sequence_1, sequence_2]): - sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=list(sequence.ro_pulses), - type=SweeperType.OFFSET, - ) - - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper, + sweepers = [ + Sweeper( + parameter=Parameter.frequency, + values=platform.config(platform.qubits[q].probe).frequency + + delta_frequency_range, + channels=[platform.qubits[q].probe], ) + for q in targets + ] + + results = platform.execute( + [sequence_0, sequence_1, sequence_2], + [sweepers], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, + ) - for qubit in targets: - result = results[qubit].average - # store the results + for qubit in targets: + ro_frequency = platform.config(platform.qubits[qubit].probe).frequency + for state, sequence in enumerate([sequence_0, sequence_1, sequence_2]): + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[-1] + result = results[ro_pulse.id] data.register_qubit( ResSpecType, (qubit, state), dict( - freq=sequence.get_qubit_pulses(qubit).ro_pulses[0].frequency - + delta_frequency_range, - signal=result.magnitude, - phase=result.phase, + freq=ro_frequency + delta_frequency_range, + signal=magnitude(result), + phase=phase(result), ), ) diff --git a/src/qibocal/protocols/drag.py b/src/qibocal/protocols/drag.py index d915d78bd..4afce36b4 100644 --- a/src/qibocal/protocols/drag.py +++ b/src/qibocal/protocols/drag.py @@ -4,20 +4,19 @@ import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, AveragingMode, Delay, Drag, PulseSequence from scipy.optimize import curve_fit from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log +from qibocal.result import probability +from qibocal.update import replace from .utils import ( COLORBAND, COLORBAND_LINE, - HZ_TO_GHZ, chi2_reduced, fallback_period, guess_period, @@ -25,9 +24,8 @@ table_html, ) -# TODO: add errors in fitting - +# TODO: add errors in fitting @dataclass class DragTuningParameters(Parameters): """DragTuning runcard inputs.""" @@ -41,6 +39,8 @@ class DragTuningParameters(Parameters): unrolling: bool = False """If ``True`` it uses sequence unrolling to deploy multiple sequences in a single instrument call. Defaults to ``False``.""" + nflips: int = 1 + """Repetitions of (Xpi - Xmpi).""" @dataclass @@ -64,15 +64,13 @@ class DragTuningResults(Results): class DragTuningData(Data): """DragTuning acquisition outputs.""" - anharmonicity: dict[QubitId, float] = field(default_factory=dict) - """Anharmonicity of each qubit.""" data: dict[QubitId, npt.NDArray[DragTuningType]] = field(default_factory=dict) """Raw data acquired.""" def _acquisition( params: DragTuningParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> DragTuningData: r""" @@ -80,72 +78,91 @@ def _acquisition( See https://arxiv.org/pdf/1504.06597.pdf Fig. 2 (c). """ - data = DragTuningData( - anharmonicity={ - qubit: platform.qubits[qubit].anharmonicity * HZ_TO_GHZ for qubit in targets - } - ) - # define the parameter to sweep and its range: - # qubit drive DRAG pulse beta parameter + data = DragTuningData() beta_param_range = np.arange(params.beta_start, params.beta_end, params.beta_step) sequences, all_ro_pulses = [], [] for beta_param in beta_param_range: sequence = PulseSequence() ro_pulses = {} - for qubit in targets: - RX_drag_pulse = platform.create_RX_drag_pulse( - qubit, start=0, beta=beta_param / data.anharmonicity[qubit] - ) - RX_drag_pulse_minus = platform.create_RX_drag_pulse( - qubit, - start=RX_drag_pulse.finish, - beta=beta_param / data.anharmonicity[qubit], - relative_phase=np.pi, + for q in targets: + natives = platform.natives.single_qubit[q] + qd_channel, qd_pulse = natives.RX()[0] + ro_channel, ro_pulse = natives.MZ()[0] + + drag = replace( + qd_pulse, + envelope=Drag( + rel_sigma=qd_pulse.envelope.rel_sigma, + beta=beta_param, + ), ) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=RX_drag_pulse_minus.finish + drag_negative = replace(drag, relative_phase=np.pi) + + for _ in range(params.nflips): + sequence.append((qd_channel, drag)) + sequence.append((qd_channel, drag_negative)) + sequence.append( + ( + ro_channel, + Delay( + duration=params.nflips + * (drag.duration + drag_negative.duration) + ), + ) ) + sequence.append((ro_channel, ro_pulse)) - sequence.add(RX_drag_pulse) - sequence.add(RX_drag_pulse_minus) - sequence.add(ro_pulses[qubit]) sequences.append(sequence) - all_ro_pulses.append(ro_pulses) + all_ro_pulses.append( + { + qubit: list(sequence.channel(platform.qubits[q].acquisition))[-1] + for qubit in targets + } + ) + + options = { + "nshots": params.nshots, + "relaxation_time": params.relaxation_time, + "acquisition_type": AcquisitionType.DISCRIMINATION, + "averaging_mode": AveragingMode.SINGLESHOT, + } - options = ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ) # execute the pulse sequence if params.unrolling: - results = platform.execute_pulse_sequences(sequences, options) - - elif not params.unrolling: - results = [ - platform.execute_pulse_sequence(sequence, options) for sequence in sequences - ] - - for ig, (beta, ro_pulses) in enumerate(zip(beta_param_range, all_ro_pulses)): - for qubit in targets: - serial = ro_pulses[qubit].serial - if params.unrolling: - result = results[serial][ig] - else: - result = results[ig][serial] - prob = result.probability(state=0) - # store the results - data.register_qubit( - DragTuningType, - (qubit), - dict( - prob=np.array([prob]), - error=np.array([np.sqrt(prob * (1 - prob) / params.nshots)]), - beta=np.array([beta]), - ), - ) + results = platform.execute(sequences, **options) + for beta, ro_pulses in zip(beta_param_range, all_ro_pulses): + for qubit in targets: + result = results[ro_pulses[qubit].id] + prob = probability(result, state=0) + # store the results + data.register_qubit( + DragTuningType, + (qubit), + dict( + prob=np.array([prob]), + error=np.array([np.sqrt(prob * (1 - prob) / params.nshots)]), + beta=np.array([beta]), + ), + ) + else: + for i, sequence in enumerate(sequences): + result = platform.execute([sequence], **options) + for qubit in targets: + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[ + -1 + ] + prob = probability(result[ro_pulse.id], state=0) + # store the results + data.register_qubit( + DragTuningType, + (qubit), + dict( + prob=np.array([prob]), + error=np.array([np.sqrt(prob * (1 - prob) / params.nshots)]), + beta=np.array([beta_param_range[i]]), + ), + ) return data @@ -162,22 +179,27 @@ def _fit(data: DragTuningData) -> DragTuningResults: for qubit in qubits: qubit_data = data[qubit] - beta_params = qubit_data.beta + + # normalize prob prob = qubit_data.prob + prob_min = np.min(prob) + prob_max = np.max(prob) + normalized_prob = (prob - prob_min) / (prob_max - prob_min) + # normalize beta + beta_params = qubit_data.beta beta_min = np.min(beta_params) beta_max = np.max(beta_params) normalized_beta = (beta_params - beta_min) / (beta_max - beta_min) # Guessing period using fourier transform - period = fallback_period(guess_period(normalized_beta, prob)) + period = fallback_period(guess_period(normalized_beta, normalized_prob)) pguess = [0.5, 0.5, period, 0] - try: popt, _ = curve_fit( drag_fit, normalized_beta, - prob, + normalized_prob, p0=pguess, maxfev=100000, bounds=( @@ -187,8 +209,8 @@ def _fit(data: DragTuningData) -> DragTuningResults: sigma=qubit_data.error, ) translated_popt = [ - popt[0], - popt[1], + popt[0] * (prob_max - prob_min) + prob_min, + popt[1] * (prob_max - prob_min), popt[2] * (beta_max - beta_min), popt[3] - 2 * np.pi * beta_min / popt[2] / (beta_max - beta_min), ] @@ -280,17 +302,12 @@ def _plot(data: DragTuningData, target: QubitId, fit: DragTuningResults): return figures, fitting_report -def _update(results: DragTuningResults, platform: Platform, target: QubitId): - try: - update.drag_pulse_beta( - results.betas[target] / platform.qubits[target].anharmonicity / HZ_TO_GHZ, - platform, - target, - ) - except ZeroDivisionError: - log.warning( - f"Beta parameter cannot be updated since the anharmoncity for qubit {target} is 0." - ) +def _update(results: DragTuningResults, platform: CalibrationPlatform, target: QubitId): + update.drag_pulse_beta( + results.betas[target], + platform, + target, + ) drag_tuning = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/drag_simple.py b/src/qibocal/protocols/drag_simple.py new file mode 100644 index 000000000..a93acac0a --- /dev/null +++ b/src/qibocal/protocols/drag_simple.py @@ -0,0 +1,258 @@ +from dataclasses import dataclass + +import numpy as np +import plotly.graph_objects as go +from qibolab import AcquisitionType, AveragingMode, Delay, Drag, Pulse, PulseSequence +from scipy.optimize import curve_fit + +from qibocal import update +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.protocols import drag +from qibocal.result import probability +from qibocal.update import replace + +from .utils import COLORBAND, COLORBAND_LINE, table_dict, table_html + +SEQUENCES = ["YpX9", "XpY9"] +"""Sequences used to fit drag parameter.""" + + +@dataclass +class DragTuningSimpleParameters(drag.DragTuningParameters): + """DragTuningSimple runcard inputs.""" + + +@dataclass +class DragTuningSimpleResults(drag.DragTuningResults): + """DragTuningSimple outputs.""" + + def __contains__(self, key): + return key in self.betas + + +@dataclass +class DragTuningSimpleData(drag.DragTuningData): + """DragTuningSimple acquisition outputs.""" + + def __getitem__(self, key: tuple[QubitId, str]): + qubit, setup = key + if setup == "YpX9": + return self.data[qubit][::2] + return self.data[qubit][1::2] + + +def add_drag(pulse: Pulse, beta: float) -> Pulse: + """Add DRAG component to Gaussian Pulse.""" + return replace(pulse, envelope=Drag(rel_sigma=pulse.envelope.rel_sigma, beta=beta)) + + +def _acquisition( + params: DragTuningSimpleParameters, + platform: CalibrationPlatform, + targets: list[QubitId], +) -> DragTuningSimpleData: + """Acquisition function for DRAG experiments. + + We execute two sequences YpX9 and XpY9 following + https://rsl.yale.edu/sites/default/files/2024-08/2011-RSL-Thesis-Matthew-Reed.pdf + for different value of the DRAG parameter. + """ + + data = DragTuningSimpleData() + beta_range = np.arange(params.beta_start, params.beta_end, params.beta_step) + + sequences, all_ro_pulses = [], [] + for beta in beta_range: + for setup in SEQUENCES: + sequence = PulseSequence() + ro_pulses = {} + for q in targets: + natives = platform.natives.single_qubit[q] + ro_channel, ro_pulse = natives.MZ()[0] + if setup == "YpX9": + qd_channel, ry = natives.R(phi=np.pi / 2)[0] + _, rx90 = natives.R(theta=np.pi / 2)[0] + sequence.append((qd_channel, add_drag(ry, beta=beta))) + sequence.append((qd_channel, add_drag(rx90, beta=beta))) + sequence.append( + (ro_channel, Delay(duration=rx90.duration + ry.duration)) + ) + else: + qd_channel, rx = natives.RX()[0] + _, ry90 = natives.R(theta=np.pi / 2, phi=np.pi / 2)[0] + sequence.append((qd_channel, add_drag(rx, beta=beta))) + sequence.append((qd_channel, add_drag(ry90, beta=beta))) + sequence.append( + (ro_channel, Delay(duration=rx.duration + ry90.duration)) + ) + sequence.append((ro_channel, ro_pulse)) + + sequences.append(sequence) + all_ro_pulses.append( + { + qubit: list(sequence.channel(platform.qubits[q].acquisition))[-1] + for qubit in targets + } + ) + + options = { + "nshots": params.nshots, + "relaxation_time": params.relaxation_time, + "acquisition_type": AcquisitionType.DISCRIMINATION, + "averaging_mode": AveragingMode.SINGLESHOT, + } + + # execute the pulse sequence + if params.unrolling: + results = platform.execute(sequences, **options) + for beta, ro_pulses in zip(np.repeat(beta_range, 2), all_ro_pulses): + for qubit in targets: + result = results[ro_pulses[qubit].id] + prob = probability(result, state=1) + # store the results + data.register_qubit( + drag.DragTuningType, + (qubit), + dict( + prob=np.array([prob]), + error=np.array([np.sqrt(prob * (1 - prob) / params.nshots)]), + beta=np.array([beta]), + ), + ) + else: + for i, sequence in enumerate(sequences): + result = platform.execute([sequence], **options) + setup = "YpX9" if i % 2 == 2 else "XpY9" + for qubit in targets: + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[ + -1 + ] + prob = probability(result[ro_pulse.id], state=1) + # store the results + data.register_qubit( + drag.DragTuningType, + (qubit), + dict( + prob=np.array([prob]), + error=np.array([np.sqrt(prob * (1 - prob) / params.nshots)]), + beta=np.array([beta_range[i // 2]]), + ), + ) + + return data + + +def _fit(data: DragTuningSimpleData) -> DragTuningSimpleResults: + """Post-processing for DRAG protocol. + + A linear fit is applied for the probability of both sequences. + The optimal is determined as the point in which the two lines met. + """ + qubits = data.qubits + fitted_parameters = {} + betas_optimal = {} + for qubit in qubits: + for setup in SEQUENCES: + qubit_data = data[qubit, setup] + popt, _ = curve_fit( + lambda x, a, b: a * x + b, qubit_data.beta, qubit_data.prob + ) + fitted_parameters[qubit, setup] = popt.tolist() + betas_optimal[qubit] = -( + fitted_parameters[qubit, "YpX9"][1] - fitted_parameters[qubit, "XpY9"][1] + ) / (fitted_parameters[qubit, "YpX9"][0] - fitted_parameters[qubit, "XpY9"][0]) + + return DragTuningSimpleResults(betas_optimal, fitted_parameters) + + +def _plot(data: DragTuningSimpleData, target: QubitId, fit: DragTuningSimpleResults): + """Plotting function for DragTuning.""" + + figures = [] + fitting_report = "" + + fig = go.Figure() + for setup in SEQUENCES: + qubit_data = data[target, setup] + fig.add_trace( + go.Scatter( + x=qubit_data.beta, + y=qubit_data.prob, + opacity=1, + mode="lines", + name=setup, + showlegend=True, + legendgroup=setup, + ) + ) + + fig.add_trace( + go.Scatter( + x=np.concatenate((qubit_data.beta, qubit_data.beta[::-1])), + y=np.concatenate( + ( + qubit_data.prob + qubit_data.error, + (qubit_data.prob - qubit_data.error)[::-1], + ) + ), + fill="toself", + fillcolor=COLORBAND, + line=dict(color=COLORBAND_LINE), + name=setup, + showlegend=False, + legendgroup=setup, + ) + ) + + # # add fitting traces + if fit is not None: + for setup in SEQUENCES: + qubit_data = data[target, setup] + betas = qubit_data.beta + beta_range = np.linspace( + min(betas), + max(betas), + 20, + ) + + fig.add_trace( + go.Scatter( + x=beta_range, + y=fit.fitted_parameters[target, setup][0] * betas + + fit.fitted_parameters[target, setup][1], + name=f"Fit {setup}", + line=go.scatter.Line(dash="dot"), + ), + ) + fitting_report = table_html( + table_dict( + target, + ["Best DRAG parameter"], + [np.round(fit.betas[target], 4)], + ) + ) + + fig.update_layout( + showlegend=True, + xaxis_title="Beta parameter", + yaxis_title="Excited state probability", + ) + + figures.append(fig) + + return figures, fitting_report + + +def _update( + results: DragTuningSimpleResults, platform: CalibrationPlatform, target: QubitId +): + update.drag_pulse_beta( + results.betas[target], + platform, + target, + ) + + +drag_simple = Routine(_acquisition, _fit, _plot, _update) +"""DragTuning Routine object.""" diff --git a/src/qibocal/protocols/fast_reset/_init__.py b/src/qibocal/protocols/fast_reset/_init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/src/qibocal/protocols/fast_reset/fast_reset.py b/src/qibocal/protocols/fast_reset/fast_reset.py deleted file mode 100644 index a6081b424..000000000 --- a/src/qibocal/protocols/fast_reset/fast_reset.py +++ /dev/null @@ -1,234 +0,0 @@ -from dataclasses import dataclass, field - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from plotly.subplots import make_subplots -from qibolab import ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId - -from qibocal.auto.operation import Data, Parameters, Results, Routine -from qibocal.protocols.utils import table_dict, table_html - -# TODO: IBM Fast Reset until saturation loop -# https://quantum-computing.ibm.com/lab/docs/iql/manage/systems/reset/backend_reset - - -@dataclass -class FastResetParameters(Parameters): - """FastReset runcard inputs.""" - - -@dataclass -class FastResetResults(Results): - """FastReset outputs.""" - - fidelity_nfr: dict[QubitId, float] - "Fidelity of the measurement with relaxation time" - Lambda_M_nfr: dict[QubitId, float] - "Mapping between a given initial state to an outcome adter the measurement with relaxation time" - fidelity_fr: dict[QubitId, float] - "Fidelity of the measurement with fast reset" - Lambda_M_fr: dict[QubitId, float] - "Mapping between a given initial state to an outcome adter the measurement with fast reset" - - -FastResetType = np.dtype( - [ - ("probability", np.float64), - ] -) -"""Custom dtype for FastReset.""" - - -@dataclass -class FastResetData(Data): - """FastReset acquisition outputs.""" - - data: dict[tuple, npt.NDArray[FastResetType]] = field(default_factory=dict) - """Raw data acquired.""" - - -def _acquisition( - params: FastResetParameters, platform: Platform, targets: list[QubitId] -) -> FastResetData: - """Data acquisition for resonator spectroscopy.""" - - data = FastResetData() - for state in [0, 1]: - for fast_reset in [True, False]: - # Define the pulse sequences - if state == 1: - RX_pulses = {} - ro_pulses = {} - sequence = PulseSequence() - for qubit in targets: - if state == 1: - RX_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=RX_pulses[qubit].finish - ) - sequence.add(RX_pulses[qubit]) - else: - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=0 - ) - sequence.add(ro_pulses[qubit]) - - # execute the pulse sequence - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - fast_reset=fast_reset, - ), - ) - - # Save the data - for ro_pulse in ro_pulses.values(): - result = results[ro_pulse.serial] - qubit = ro_pulse.qubit - data.register_qubit( - FastResetType, - (qubit, state, fast_reset), - dict(probability=result.samples), - ) - - return data - - -def _fit(data: FastResetData) -> FastResetResults: - """Post-processing function for FastReset.""" - - qubits = data.qubits - fidelity_nfr = {} - Lambda_M_nfr = {} - fidelity_fr = {} - Lambda_M_fr = {} - for qubit in qubits: - # state 1 - fr_states = data[qubit, 1, True].probability - nfr_states = data[qubit, 1, False].probability - - nshots = len(fr_states) - - state1_count_1fr = np.count_nonzero(fr_states) - state0_count_1fr = nshots - state1_count_1fr - - state1_count_1nfr = np.count_nonzero(nfr_states) - state0_count_1nfr = nshots - state1_count_1nfr - - # state 0 - fr_states = data[qubit, 0, True].probability - nfr_states = data[qubit, 0, False].probability - - state1_count_0fr = np.count_nonzero(fr_states) - state0_count_0fr = nshots - state1_count_0fr - - state1_count_0nfr = np.count_nonzero(nfr_states) - state0_count_0nfr = nshots - state1_count_0nfr - - # Repeat Lambda and fidelity for each measurement ? - Lambda_M_nfr[qubit] = [ - [state0_count_0nfr / nshots, state0_count_1nfr / nshots], - [state1_count_0nfr / nshots, state1_count_1nfr / nshots], - ] - - # Repeat Lambda and fidelity for each measurement ? - Lambda_M_fr[qubit] = [ - [state0_count_0fr / nshots, state0_count_1fr / nshots], - [state1_count_0fr / nshots, state1_count_1fr / nshots], - ] - - fidelity_nfr[qubit] = ( - 1 - (state1_count_0nfr / nshots + state0_count_1nfr / nshots) / 2 - ) - - fidelity_fr[qubit] = ( - 1 - (state1_count_0fr / nshots + state0_count_1fr / nshots) / 2 - ) - - return FastResetResults(fidelity_nfr, Lambda_M_nfr, fidelity_fr, Lambda_M_fr) - - -def _plot(data: FastResetData, fit: FastResetResults, target: QubitId): - """Plotting function for FastReset.""" - - # Maybe the plot can just be something like a confusion matrix between 0s and 1s ??? - - figures = [] - fitting_report = "" - fig = make_subplots( - rows=1, - cols=2, - horizontal_spacing=0.1, - vertical_spacing=0.1, - subplot_titles=( - "Fast Reset", - "Relaxation Time [ns]", - ), - ) - - if fit is not None: - fig.add_trace( - go.Heatmap( - z=fit.Lambda_M_fr[target], - coloraxis="coloraxis", - ), - row=1, - col=1, - ) - fitting_report = table_html( - table_dict( - target, - ["Fidelity [Fast Reset]", "Fidelity [Relaxation Time]"], - [ - np.round(fit.fidelity_fr[target], 6), - np.round(fit.fidelity_nfr[target], 6), - ], - ) - ) - - fig.add_trace( - go.Heatmap( - z=fit.Lambda_M_nfr[target], - coloraxis="coloraxis", - ), - row=1, - col=2, - ) - - fig.update_xaxes( - title_text=f"{target}: Fast Reset", - row=1, - col=1, - ) - fig.update_yaxes(title_text="State", row=1, col=1) - fig.update_yaxes(tickvals=[0, 1]) - fig.update_xaxes(tickvals=[0, 1]) - - fig.update_layout(coloraxis={"colorscale": "viridis"}) - - fig.update_xaxes( - title_text="State prepared", - row=1, - col=2, - ) - - # last part - fig.update_layout( - showlegend=False, - xaxis_title="State prepared", - yaxis_title="State measured", - ) - - figures.append(fig) - - return figures, fitting_report - - -fast_reset = Routine(_acquisition, _fit, _plot) -"""FastReset Routine object.""" diff --git a/src/qibocal/protocols/flipping.py b/src/qibocal/protocols/flipping.py index 981be1b08..ba3247f75 100644 --- a/src/qibocal/protocols/flipping.py +++ b/src/qibocal/protocols/flipping.py @@ -1,15 +1,15 @@ from dataclasses import dataclass, field +from typing import Union import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, AveragingMode, PulseSequence from scipy.optimize import curve_fit -from qibocal.auto.operation import Routine +from qibocal import update +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import ( fallback_period, @@ -18,26 +18,77 @@ table_html, ) -from .flipping_signal import ( - FlippingSignalData, - FlippingSignalParameters, - FlippingSignalResults, - _update, - flipping_fit, - flipping_sequence, -) +from ..result import probability from .utils import COLORBAND, COLORBAND_LINE, chi2_reduced +def flipping_sequence( + platform: CalibrationPlatform, + qubit: QubitId, + delta_amplitude: float, + flips: int, + rx90: bool, +): + """Pulse sequence for flipping experiment.""" + + sequence = PulseSequence() + natives = platform.natives.single_qubit[qubit] + + sequence |= natives.R(theta=np.pi / 2) + + for _ in range(flips): + + if rx90: + qd_channel, qd_pulse = natives.RX90()[0] + else: + qd_channel, qd_pulse = natives.RX()[0] + + qd_detuned = update.replace( + qd_pulse, amplitude=qd_pulse.amplitude + delta_amplitude + ) + sequence.append((qd_channel, qd_detuned)) + sequence.append((qd_channel, qd_detuned)) + + if rx90: + sequence.append((qd_channel, qd_detuned)) + sequence.append((qd_channel, qd_detuned)) + + sequence |= natives.MZ() + + return sequence + + @dataclass -class FlippingParameters(FlippingSignalParameters): +class FlippingParameters(Parameters): """Flipping runcard inputs.""" + nflips_max: int + """Maximum number of flips ([RX(pi) - RX(pi)] sequences). """ + nflips_step: int + """Flip step.""" + unrolling: bool = False + """If ``True`` it uses sequence unrolling to deploy multiple sequences in a single instrument call. + Defaults to ``False``.""" + delta_amplitude: float = 0 + """Amplitude detuning.""" + rx90: bool = False + """Calibration of native pi pulse, if true calibrates pi/2 pulse""" + @dataclass -class FlippingResults(FlippingSignalResults): +class FlippingResults(Results): """Flipping outputs.""" + amplitude: dict[QubitId, Union[float, list[float]]] + """Drive amplitude for each qubit.""" + delta_amplitude: dict[QubitId, Union[float, list[float]]] + """Difference in amplitude between initial value and fit.""" + delta_amplitude_detuned: dict[QubitId, Union[float, list[float]]] + """Difference in amplitude between detuned value and fit.""" + fitted_parameters: dict[QubitId, dict[str, float]] + """Raw fitting output.""" + rx90: bool + """Pi or Pi_half calibration""" chi2: dict[QubitId, list[float]] = field(default_factory=dict) """Chi squared estimate mean value and error. """ @@ -48,16 +99,24 @@ class FlippingResults(FlippingSignalResults): @dataclass -class FlippingData(FlippingSignalData): +class FlippingData(Data): """Flipping acquisition outputs.""" + resonator_type: str + """Resonator type.""" + delta_amplitude: float + """Amplitude detuning.""" + pulse_amplitudes: dict[QubitId, float] + """Pulse amplitudes for each qubit.""" + rx90: bool + """Pi or Pi_half calibration""" data: dict[QubitId, npt.NDArray[FlippingType]] = field(default_factory=dict) """Raw data acquired.""" def _acquisition( params: FlippingParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> FlippingData: r""" @@ -65,10 +124,11 @@ def _acquisition( The flipping experiment correct the delta amplitude in the qubit drive pulse. We measure a qubit after applying a Rx(pi/2) and N flips (Rx(pi) rotations). After fitting we can obtain the delta amplitude to refine pi pulses. + On the y axis we measure the excited state probability. Args: params (:class:`SingleShotClassificationParameters`): input parameters - platform (:class:`Platform`): Qibolab's platform + platform (:class:`CalibrationPlatform`): Qibolab's platform qubits (dict): dict of target :class:`Qubit` objects to be characterized Returns: @@ -78,23 +138,26 @@ def _acquisition( data = FlippingData( resonator_type=platform.resonator_type, delta_amplitude=params.delta_amplitude, - pi_pulse_amplitudes={ - qubit: platform.qubits[qubit].native_gates.RX.amplitude for qubit in targets + pulse_amplitudes={ + qubit: getattr( + platform.natives.single_qubit[qubit], "RX90" if params.rx90 else "RX" + )[0][1].amplitude + for qubit in targets }, + rx90=params.rx90, ) - options = ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ) + options = { + "nshots": params.nshots, + "relaxation_time": params.relaxation_time, + "acquisition_type": AcquisitionType.DISCRIMINATION, + "averaging_mode": AveragingMode.SINGLESHOT, + } + + sequences = [] - # sweep the parameter - sequences, all_ro_pulses = [], [] flips_sweep = range(0, params.nflips_max, params.nflips_step) for flips in flips_sweep: - # create a sequence of pulses for the experiment sequence = PulseSequence() for qubit in targets: sequence += flipping_sequence( @@ -102,42 +165,43 @@ def _acquisition( qubit=qubit, delta_amplitude=params.delta_amplitude, flips=flips, + rx90=params.rx90, ) sequences.append(sequence) - all_ro_pulses.append(sequence.ro_pulses) - # execute the pulse sequence if params.unrolling: - results = platform.execute_pulse_sequences(sequences, options) - - elif not params.unrolling: - results = [ - platform.execute_pulse_sequence(sequence, options) for sequence in sequences - ] + results = platform.execute(sequences, **options) + else: + results = [platform.execute([sequence], **options) for sequence in sequences] - for ig, (flips, ro_pulses) in enumerate(zip(flips_sweep, all_ro_pulses)): + for i in range(len(sequences)): for qubit in targets: - serial = ro_pulses.get_qubit_pulses(qubit)[0].serial + ro_pulse = list(sequences[i].channel(platform.qubits[qubit].acquisition))[ + -1 + ] if params.unrolling: - result = results[serial][0] + result = results[ro_pulse.id] else: - result = results[ig][serial] - prob = result.probability(state=1) + result = results[i][ro_pulse.id] + prob = probability(result, state=1) error = np.sqrt(prob * (1 - prob) / params.nshots) data.register_qubit( FlippingType, (qubit), dict( - flips=np.array([flips]), + flips=np.array([flips_sweep[i]]), prob=np.array([prob]), error=np.array([error]), ), ) - return data +def flipping_fit(x, offset, amplitude, omega, phase, gamma): + return np.sin(x * omega + phase) * amplitude * np.exp(-x * gamma) + offset + + def _fit(data: FlippingData) -> FlippingResults: r"""Post-processing function for Flipping. @@ -155,9 +219,7 @@ def _fit(data: FlippingData) -> FlippingResults: chi2 = {} for qubit in qubits: qubit_data = data[qubit] - detuned_pi_pulse_amplitude = ( - data.pi_pulse_amplitudes[qubit] + data.delta_amplitude - ) + detuned_pulse_amplitude = data.pulse_amplitudes[qubit] + data.delta_amplitude y = qubit_data.prob x = qubit_data.flips @@ -180,10 +242,14 @@ def _fit(data: FlippingData) -> FlippingResults: perr = np.sqrt(np.diag(perr)).tolist() popt = popt.tolist() correction = popt[2] / 2 + + if data.rx90: + correction /= 2 + corrected_amplitudes[qubit] = [ - float(detuned_pi_pulse_amplitude * np.pi / (np.pi + correction)), + float(detuned_pulse_amplitude * np.pi / (np.pi + correction)), float( - detuned_pi_pulse_amplitude + detuned_pulse_amplitude * np.pi * 1 / (np.pi + correction) ** 2 @@ -195,11 +261,9 @@ def _fit(data: FlippingData) -> FlippingResults: fitted_parameters[qubit] = popt delta_amplitude_detuned[qubit] = [ - -correction * detuned_pi_pulse_amplitude / (np.pi + correction), + -correction * detuned_pulse_amplitude / (np.pi + correction), np.abs( - np.pi - * detuned_pi_pulse_amplitude - * np.power(np.pi + correction, -2) + np.pi * detuned_pulse_amplitude * np.power(np.pi + correction, -2) ) * perr[2] / 2, @@ -225,6 +289,7 @@ def _fit(data: FlippingData) -> FlippingResults: delta_amplitude, delta_amplitude_detuned, fitted_parameters, + data.rx90, chi2, ) @@ -315,5 +380,9 @@ def _plot(data: FlippingData, target: QubitId, fit: FlippingResults = None): return figures, fitting_report +def _update(results: FlippingResults, platform: CalibrationPlatform, qubit: QubitId): + update.drive_amplitude(results.amplitude[qubit], results.rx90, platform, qubit) + + flipping = Routine(_acquisition, _fit, _plot, _update) """Flipping Routine object.""" diff --git a/src/qibocal/protocols/flipping_signal.py b/src/qibocal/protocols/flipping_signal.py deleted file mode 100644 index 33e7900c4..000000000 --- a/src/qibocal/protocols/flipping_signal.py +++ /dev/null @@ -1,334 +0,0 @@ -from dataclasses import dataclass, field -from typing import Union - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from scipy.optimize import curve_fit - -from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine -from qibocal.config import log -from qibocal.protocols.utils import ( - fallback_period, - guess_period, - table_dict, - table_html, -) - - -@dataclass -class FlippingSignalParameters(Parameters): - """Flipping runcard inputs.""" - - nflips_max: int - """Maximum number of flips ([RX(pi) - RX(pi)] sequences). """ - nflips_step: int - """Flip step.""" - unrolling: bool = False - """If ``True`` it uses sequence unrolling to deploy multiple sequences in a single instrument call. - Defaults to ``False``.""" - delta_amplitude: float = 0 - """Amplitude detuning.""" - - -@dataclass -class FlippingSignalResults(Results): - """Flipping outputs.""" - - amplitude: dict[QubitId, Union[float, list[float]]] - """Drive amplitude for each qubit.""" - delta_amplitude: dict[QubitId, Union[float, list[float]]] - """Difference in amplitude between initial value and fit.""" - delta_amplitude_detuned: dict[QubitId, Union[float, list[float]]] - """Difference in amplitude between detuned value and fit.""" - fitted_parameters: dict[QubitId, dict[str, float]] - """Raw fitting output.""" - - -FlippingType = np.dtype([("flips", np.float64), ("signal", np.float64)]) - - -@dataclass -class FlippingSignalData(Data): - """Flipping acquisition outputs.""" - - resonator_type: str - """Resonator type.""" - delta_amplitude: float - """Amplitude detuning.""" - pi_pulse_amplitudes: dict[QubitId, float] - """Pi pulse amplitudes for each qubit.""" - data: dict[QubitId, npt.NDArray[FlippingType]] = field(default_factory=dict) - """Raw data acquired.""" - - -def flipping_sequence( - platform: Platform, qubit: QubitId, delta_amplitude: float, flips: int -): - - sequence = PulseSequence() - RX90_pulse = platform.create_RX90_pulse(qubit, start=0) - sequence.add(RX90_pulse) - # execute sequence RX(pi/2) - [RX(pi) - RX(pi)] from 0...flips times - RO - start1 = RX90_pulse.duration - drive_amplitude = platform.qubits[qubit].native_gates.RX.amplitude - for _ in range(flips): - RX_pulse1 = platform.create_RX_pulse(qubit, start=start1) - RX_pulse1.amplitude = drive_amplitude + delta_amplitude - start2 = start1 + RX_pulse1.duration - RX_pulse2 = platform.create_RX_pulse(qubit, start=start2) - RX_pulse2.amplitude = drive_amplitude + delta_amplitude - - sequence.add(RX_pulse1) - sequence.add(RX_pulse2) - start1 = start2 + RX_pulse2.duration - - # add ro pulse at the end of the sequence - sequence.add(platform.create_qubit_readout_pulse(qubit, start=start1)) - - return sequence - - -def _acquisition( - params: FlippingSignalParameters, - platform: Platform, - targets: list[QubitId], -) -> FlippingSignalData: - r""" - Data acquisition for flipping. - - The flipping experiment correct the delta amplitude in the qubit drive pulse. We measure a qubit after applying - a Rx(pi/2) and N flips (Rx(pi) rotations). After fitting we can obtain the delta amplitude to refine pi pulses. - - Args: - params (:class:`FlippingSignalParameters`): input parameters - platform (:class:`Platform`): Qibolab's platform - qubits (dict): dict of target :class:`Qubit` objects to be characterized - - Returns: - data (:class:`FlippingSignalData`) - """ - - data = FlippingSignalData( - resonator_type=platform.resonator_type, - delta_amplitude=params.delta_amplitude, - pi_pulse_amplitudes={ - qubit: platform.qubits[qubit].native_gates.RX.amplitude for qubit in targets - }, - ) - - options = ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ) - - # sweep the parameter - sequences, all_ro_pulses = [], [] - flips_sweep = range(0, params.nflips_max, params.nflips_step) - for flips in flips_sweep: - # create a sequence of pulses for the experiment - sequence = PulseSequence() - for qubit in targets: - sequence += flipping_sequence( - platform=platform, - qubit=qubit, - delta_amplitude=params.delta_amplitude, - flips=flips, - ) - - sequences.append(sequence) - all_ro_pulses.append(sequence.ro_pulses) - - # execute the pulse sequence - if params.unrolling: - results = platform.execute_pulse_sequences(sequences, options) - - elif not params.unrolling: - results = [ - platform.execute_pulse_sequence(sequence, options) for sequence in sequences - ] - - for ig, (flips, ro_pulses) in enumerate(zip(flips_sweep, all_ro_pulses)): - for qubit in targets: - serial = ro_pulses.get_qubit_pulses(qubit)[0].serial - if params.unrolling: - result = results[serial][0] - else: - result = results[ig][serial] - data.register_qubit( - FlippingType, - (qubit), - dict( - flips=np.array([flips]), - signal=np.array([result.magnitude]), - ), - ) - - return data - - -def flipping_fit(x, offset, amplitude, omega, phase, gamma): - return np.sin(x * omega + phase) * amplitude * np.exp(-x * gamma) + offset - - -def _fit(data: FlippingSignalData) -> FlippingSignalResults: - r"""Post-processing function for Flipping. - - The used model is - - .. math:: - - y = p_0 sin\Big(\frac{2 \pi x}{p_2} + p_3\Big)*\exp{-x*p4} + p_1. - """ - qubits = data.qubits - corrected_amplitudes = {} - fitted_parameters = {} - delta_amplitude = {} - delta_amplitude_detuned = {} - for qubit in qubits: - qubit_data = data[qubit] - detuned_pi_pulse_amplitude = ( - data.pi_pulse_amplitudes[qubit] + data.delta_amplitude - ) - voltages = qubit_data.signal - flips = qubit_data.flips - - x_min = np.min(flips) - x_max = np.max(flips) - x = (flips - x_min) / (x_max - x_min) - y_max = np.max(voltages) - y_min = np.min(voltages) - # normalize between 0 and 1 - y = (voltages - y_min) / (y_max - y_min) - - period = fallback_period(guess_period(x, y)) - pguess = [0.5, 0.5, 2 * np.pi / period, 0, 0] - - try: - popt, _ = curve_fit( - flipping_fit, - x, - y, - p0=pguess, - maxfev=2000000, - bounds=( - [0.4, 0.4, -np.inf, -np.pi / 4, 0], - [0.6, 0.6, np.inf, np.pi / 4, np.inf], - ), - ) - - translated_popt = [ - y_min + (y_max - y_min) * popt[0], - (y_max - y_min) * popt[1] * np.exp(x_min * popt[4] / (x_max - x_min)), - popt[2] / (x_max - x_min), - popt[3] - x_min / (x_max - x_min) * popt[2], - popt[4] / (x_max - x_min), - ] - # TODO: this might be related to the resonator type - signed_correction = translated_popt[2] / 2 - # The amplitude is directly proportional to the rotation angle - corrected_amplitudes[qubit] = (detuned_pi_pulse_amplitude * np.pi) / ( - np.pi + signed_correction - ) - fitted_parameters[qubit] = translated_popt - delta_amplitude_detuned[qubit] = ( - -signed_correction - * detuned_pi_pulse_amplitude - / (np.pi + signed_correction) - ) - delta_amplitude[qubit] = ( - delta_amplitude_detuned[qubit] - data.delta_amplitude - ) - except Exception as e: - log.warning(f"Error in flipping fit for qubit {qubit} due to {e}.") - - return FlippingSignalResults( - corrected_amplitudes, - delta_amplitude, - delta_amplitude_detuned, - fitted_parameters, - ) - - -def _plot(data: FlippingSignalData, target, fit: FlippingSignalResults = None): - """Plotting function for Flipping.""" - - figures = [] - fig = go.Figure() - fitting_report = "" - qubit_data = data[target] - - fig.add_trace( - go.Scatter( - x=qubit_data.flips, - y=qubit_data.signal, - opacity=1, - name="Signal", - showlegend=True, - legendgroup="Signal", - ), - ) - - if fit is not None: - flips_range = np.linspace( - min(qubit_data.flips), - max(qubit_data.flips), - 2 * len(qubit_data), - ) - - fig.add_trace( - go.Scatter( - x=flips_range, - y=flipping_fit( - flips_range, - float(fit.fitted_parameters[target][0]), - float(fit.fitted_parameters[target][1]), - float(fit.fitted_parameters[target][2]), - float(fit.fitted_parameters[target][3]), - float(fit.fitted_parameters[target][4]), - ), - name="Fit", - line=go.scatter.Line(dash="dot"), - ), - ) - fitting_report = table_html( - table_dict( - target, - [ - "Delta amplitude [a.u.]", - "Delta amplitude (with detuning) [a.u.]", - "Corrected amplitude [a.u.]", - ], - [ - np.round(fit.delta_amplitude[target], 4), - np.round(fit.delta_amplitude_detuned[target], 4), - np.round(fit.amplitude[target], 4), - ], - ) - ) - - # last part - fig.update_layout( - showlegend=True, - xaxis_title="Flips", - yaxis_title="Signal [a.u.]", - ) - - figures.append(fig) - - return figures, fitting_report - - -def _update(results: FlippingSignalResults, platform: Platform, qubit: QubitId): - update.drive_amplitude(results.amplitude[qubit], platform, qubit) - - -flipping_signal = Routine(_acquisition, _fit, _plot, _update) -"""Flipping Routine object.""" diff --git a/src/qibocal/protocols/flux_dependence/avoided_crossing.py b/src/qibocal/protocols/flux_dependence/avoided_crossing.py deleted file mode 100644 index f9f9ce796..000000000 --- a/src/qibocal/protocols/flux_dependence/avoided_crossing.py +++ /dev/null @@ -1,364 +0,0 @@ -from copy import deepcopy -from dataclasses import dataclass, field -from enum import Enum -from typing import Optional - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from plotly.subplots import make_subplots -from qibolab.platform import Platform -from qibolab.qubits import QubitId, QubitPairId - -from qibocal.auto.operation import Data, Results, Routine -from qibocal.protocols.two_qubit_interaction.utils import order_pair -from qibocal.protocols.utils import HZ_TO_GHZ, table_dict, table_html - -from .qubit_flux_dependence import QubitFluxParameters, QubitFluxType -from .qubit_flux_dependence import _acquisition as flux_acquisition - -STEP = 60 -POINT_SIZE = 10 - - -@dataclass -class AvoidedCrossingParameters(QubitFluxParameters): - """Avoided Crossing Parameters""" - - -@dataclass -class AvoidedCrossingResults(Results): - """Avoided crossing outputs""" - - parabolas: dict[tuple, list] - """Extracted parabolas""" - fits: dict[tuple, list] - """Fits parameters""" - cz: dict[tuple, list] - """CZ intersection points """ - iswap: dict[tuple, list] - """iSwap intersection points""" - - -@dataclass -class AvoidedCrossingData(Data): - """Avoided crossing acquisition outputs""" - - qubit_pairs: list - """list of qubit pairs ordered following the drive frequency""" - drive_frequency_low: dict = field(default_factory=dict) - """Lowest drive frequency in each qubit pair""" - data: dict[tuple[QubitId, str], npt.NDArray[QubitFluxType]] = field( - default_factory=dict - ) - """Raw data acquired.""" - - -def _acquisition( - params: AvoidedCrossingParameters, - platform: Platform, - targets: list[QubitPairId], # qubit pairs -) -> AvoidedCrossingData: - """ - Data acquisition for avoided crossing. - This routine performs the qubit flux dependency for the "01" and "02" transition - on the qubit pair. It returns the bias and frequency values to perform a CZ - and a iSwap gate. - - Args: - params (AvoidedCrossingParameters): experiment's parameters. - platform (Platform): Qibolab platform object. - qubits (dict): list of targets qubit pairs to perform the action. - """ - order_pairs = np.array([order_pair(pair, platform) for pair in targets]) - data = AvoidedCrossingData(qubit_pairs=order_pairs.tolist()) - # Extract the qubits in the qubits pairs and evaluate their flux dep - unique_qubits = np.unique( - order_pairs[:, 1] - ) # select qubits with high freq in each couple - new_qubits = {key: platform.qubits[key] for key in unique_qubits} - excitations = [Excitations.ge, Excitations.gf] - for transition in excitations: - params.transition = transition - data_transition = flux_acquisition( - params=params, - platform=platform, - targets=new_qubits, - ) - for qubit in unique_qubits: - qubit_data = data_transition.data[qubit] - freq = qubit_data["freq"] - bias = qubit_data["bias"] - signal = qubit_data["signal"] - phase = qubit_data["phase"] - data.register_qubit( - QubitFluxType, - (float(qubit), transition), - dict( - freq=freq.tolist(), - bias=bias.tolist(), - signal=signal.tolist(), - phase=phase.tolist(), - ), - ) - - unique_low_qubits = np.unique(order_pairs[:, 0]) - data.drive_frequency_low = { - str(qubit): float(platform.qubits[qubit].drive_frequency) - for qubit in unique_low_qubits - } - return data - - -def _fit(data: AvoidedCrossingData) -> AvoidedCrossingResults: - """ - Post-Processing for avoided crossing. - """ - qubit_data = data.data - fits = {} - cz = {} - iswap = {} - curves = {tuple(key): find_parabola(val) for key, val in qubit_data.items()} - for qubit_pair in data.qubit_pairs: - qubit_pair = tuple(qubit_pair) - fits[qubit_pair] = {} - low = qubit_pair[0] - high = qubit_pair[1] - # Fit the 02*2 curve - curve_02 = np.array(curves[high, Excitations.gf]) * 2 - x_02 = np.unique(qubit_data[high, Excitations.gf]["bias"]) - fit_02 = np.polyfit(x_02, curve_02, 2) - fits[qubit_pair][Excitations.gf] = fit_02.tolist() - - # Fit the 01+10 curve - curve_01 = np.array(curves[high, Excitations.ge]) - x_01 = np.unique(qubit_data[high, Excitations.ge]["bias"]) - fit_01_10 = np.polyfit(x_01, curve_01 + data.drive_frequency_low[str(low)], 2) - fits[qubit_pair][Excitations.all_ge] = fit_01_10.tolist() - # find the intersection of the two parabolas - delta_fit = fit_02 - fit_01_10 - x1, x2 = solve_eq(delta_fit) - cz[qubit_pair] = [ - [x1, np.polyval(fit_02, x1)], - [x2, np.polyval(fit_02, x2)], - ] - # find the intersection of the 01 parabola and the 10 line - fit_01 = np.polyfit(x_01, curve_01, 2) - fits[qubit_pair][Excitations.ge] = fit_01.tolist() - fit_pars = deepcopy(fit_01) - line_val = data.drive_frequency_low[str(low)] - fit_pars[2] -= line_val - x1, x2 = solve_eq(fit_pars) - iswap[qubit_pair] = [[x1, line_val], [x2, line_val]] - - return AvoidedCrossingResults(curves, fits, cz, iswap) - - -def _plot( - data: AvoidedCrossingData, - fit: Optional[AvoidedCrossingResults], - target: QubitPairId, -): - """Plotting function for avoided crossing""" - fitting_report = "" - figures = [] - order_pair = tuple(index(data.qubit_pairs, target)) - heatmaps = make_subplots( - rows=1, - cols=2, - subplot_titles=[ - f"{i} transition qubit {target[0]}" - for i in [Excitations.ge, Excitations.gf] - ], - ) - parabolas = make_subplots(rows=1, cols=1, subplot_titles=["Parabolas"]) - for i, transition in enumerate([Excitations.ge, Excitations.gf]): - data_high = data.data[order_pair[1], transition] - bias_unique = np.unique(data_high.bias) - min_bias = min(bias_unique) - max_bias = max(bias_unique) - plot_heatmap( - heatmaps, fit, transition, bias_unique, order_pair, data_high, i + 1 - ) - - figures.append(heatmaps) - - if fit is not None: - cz = np.array(fit.cz[order_pair]) - iswap = np.array(fit.iswap[order_pair]) - min_bias = min(min_bias, *cz[:, 0], *iswap[:, 0]) - max_bias = max(max_bias, *cz[:, 0], *iswap[:, 0]) - bias_range = np.linspace(min_bias, max_bias, STEP) - plot_curves(parabolas, fit, data, order_pair, bias_range) - plot_intersections(parabolas, cz, iswap) - - parabolas.update_layout( - xaxis_title="Bias[V]", - yaxis_title="Frequency[GHz]", - ) - heatmaps.update_layout( - coloraxis_colorbar=dict( - yanchor="top", - y=1, - x=-0.08, - ticks="outside", - ), - xaxis_title="Frequency[GHz]", - yaxis_title="Bias[V]", - xaxis2_title="Frequency[GHz]", - yaxis2_title="Bias[V]", - ) - figures.append(parabolas) - fitting_report = table_html( - table_dict( - target, - ["CZ bias", "iSwap bias"], - [np.round(cz[:, 0], 3), np.round(iswap[:, 0], 3)], - ) - ) - return figures, fitting_report - - -avoided_crossing = Routine(_acquisition, _fit, _plot) - - -def find_parabola(data: dict) -> list: - """ - Finds the parabola in `data` - """ - freqs = data["freq"] - currs = data["bias"] - biass = sorted(np.unique(currs)) - frequencies = [] - for bias in biass: - data_bias = data[currs == bias] - index = data_bias["signal"].argmax() - frequencies.append(freqs[index]) - return frequencies - - -def solve_eq(pars: list) -> tuple: - """ - Solver of the quadratic equation - - .. math:: - a x^2 + b x + c = 0 - - `pars` is the list [a, b, c]. - """ - first_term = -1 * pars[1] - second_term = np.sqrt(pars[1] ** 2 - 4 * pars[0] * pars[2]) - x1 = (first_term + second_term) / pars[0] / 2 - x2 = (first_term - second_term) / pars[0] / 2 - return x1, x2 - - -def index(pairs: list, item: list) -> list: - """Find the ordered pair""" - for pair in pairs: - if set(pair) == set(item): - return pair - raise ValueError(f"{item} not in pairs") - - -class Excitations(str, Enum): - """ - Excited two qubits states. - """ - - ge = "01" - """First qubit in ground state, second qubit in excited state""" - gf = "02" - """First qubit in ground state, second qubit in the first excited state out - of the computational basis.""" - all_ge = "01+10" - """One of the qubit in the ground state and the other one in the excited state.""" - - -def plot_heatmap(heatmaps, fit, transition, bias_unique, order_pair, data_high, col): - heatmaps.add_trace( - go.Heatmap( - x=data_high.freq * HZ_TO_GHZ, - y=data_high.bias, - z=data_high.signal, - coloraxis="coloraxis", - ), - row=1, - col=col, - ) - if fit is not None: - # the fit of the parabola in 02 transition was done doubling the frequencies - heatmaps.add_trace( - go.Scatter( - x=np.polyval(fit.fits[order_pair][transition], bias_unique) - / col - * HZ_TO_GHZ, - y=bias_unique, - mode="markers", - marker_color="lime", - showlegend=True, - marker=dict(size=POINT_SIZE), - name=f"Curve estimation {transition}", - ), - row=1, - col=col, - ) - heatmaps.add_trace( - go.Scatter( - x=np.array(fit.parabolas[order_pair[1], transition]) * HZ_TO_GHZ, - y=bias_unique, - mode="markers", - marker_color="black", - showlegend=True, - marker=dict(symbol="cross", size=POINT_SIZE), - name=f"Parabola {transition}", - ), - row=1, - col=col, - ) - - -def plot_curves(parabolas, fit, data, order_pair, bias_range): - for transition in [Excitations.ge, Excitations.gf, Excitations.all_ge]: - parabolas.add_trace( - go.Scatter( - x=bias_range, - y=np.polyval(fit.fits[order_pair][transition], bias_range) * HZ_TO_GHZ, - showlegend=True, - name=transition, - ) - ) - parabolas.add_trace( - go.Scatter( - x=bias_range, - y=np.array([data.drive_frequency_low[str(order_pair[0])]] * STEP) - * HZ_TO_GHZ, - showlegend=True, - name="10", - ) - ) - - -def plot_intersections(parabolas, cz, iswap): - parabolas.add_trace( - go.Scatter( - x=cz[:, 0], - y=cz[:, 1] * HZ_TO_GHZ, - showlegend=True, - name="CZ", - marker_color="black", - mode="markers", - marker=dict(symbol="cross", size=POINT_SIZE), - ) - ) - parabolas.add_trace( - go.Scatter( - x=iswap[:, 0], - y=iswap[:, 1] * HZ_TO_GHZ, - showlegend=True, - name="iswap", - marker_color="blue", - mode="markers", - marker=dict(symbol="cross", size=10), - ) - ) diff --git a/src/qibocal/protocols/flux_dependence/qubit_crosstalk.py b/src/qibocal/protocols/flux_dependence/qubit_crosstalk.py index dac8d8c8c..e7e956318 100644 --- a/src/qibocal/protocols/flux_dependence/qubit_crosstalk.py +++ b/src/qibocal/protocols/flux_dependence/qubit_crosstalk.py @@ -3,19 +3,24 @@ import numpy as np import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import ( + AcquisitionType, + AveragingMode, + Delay, + Parameter, + PulseSequence, + Sweeper, +) from scipy.optimize import curve_fit from qibocal import update -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log -from ..qubit_spectroscopy_ef import DEFAULT_ANHARMONICITY -from ..utils import HZ_TO_GHZ, extract_feature, table_dict, table_html +from ...result import magnitude, phase +from ...update import replace +from ..utils import GHZ_TO_HZ, HZ_TO_GHZ, extract_feature, table_dict, table_html from . import utils from .qubit_flux_dependence import ( QubitFluxData, @@ -23,7 +28,6 @@ QubitFluxResults, QubitFluxType, ) -from .qubit_flux_dependence import _fit as diagonal_fit @dataclass @@ -38,7 +42,6 @@ class QubitCrosstalkParameters(QubitFluxParameters): If given flux will be swept on the given qubits in a sequential fashion (n qubits will result to n different executions). Multiple qubits may be measured in each execution as specified by the ``qubits`` option in the runcard. """ - # TODO: add voltage parameters to bias qubits off sweetspot (absolute) @dataclass @@ -68,28 +71,6 @@ def register_qubit(self, qubit, flux_qubit, freq, bias, signal, phase): else: self.data[qubit, flux_qubit] = ar - @property - def diagonal(self) -> Optional[QubitFluxData]: - instance = QubitFluxData( - resonator_type=self.resonator_type, - charging_energy=self.charging_energy, - qubit_frequency=self.qubit_frequency, - ) - for qubit in self.qubits: - try: - instance.data[qubit] = self.data[qubit, qubit] - except KeyError: - log.info( - f"Diagonal acquisition not found for qubit {qubit}. Runcard values will be used to perform the off-diagonal fit." - ) - - if len(instance.data) > 0: - return instance - return QubitFluxData( - resonator_type=self.resonator_type, - charging_energy=self.charging_energy, - ) - @dataclass class QubitCrosstalkResults(QubitFluxResults): @@ -97,11 +78,11 @@ class QubitCrosstalkResults(QubitFluxResults): Qubit Crosstalk outputs. """ - qubit_frequency_bias_point: dict[QubitId, float] + qubit_frequency_bias_point: dict[QubitId, float] = field(default_factory=dict) """Expected qubit frequency at bias point.""" - crosstalk_matrix: dict[QubitId, dict[QubitId, float]] + crosstalk_matrix: dict[QubitId, dict[QubitId, float]] = field(default_factory=dict) """Crosstalk matrix element.""" - fitted_parameters: dict[tuple[QubitId, QubitId], dict] + fitted_parameters: dict[tuple[QubitId, QubitId], dict] = field(default_factory=dict) """Fitted parameters for each couple target-flux qubit.""" def __contains__(self, key: QubitId): @@ -111,119 +92,120 @@ def __contains__(self, key: QubitId): def _acquisition( params: QubitCrosstalkParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> QubitCrosstalkData: """Data acquisition for Crosstalk Experiment.""" - # TODO: pass voltage as parameter + assert set(targets).isdisjoint( + set(params.flux_qubits) + ), "Flux qubits must be different from targets." + sequence = PulseSequence() ro_pulses = {} qd_pulses = {} offset = {} charging_energy = {} matrix_element = {} - qubit_frequency = {} - bias_point = {} - for qubit in targets: - - charging_energy[qubit] = -platform.qubits[qubit].anharmonicity - qd_pulses[qubit] = platform.create_qubit_drive_pulse( - qubit, start=0, duration=params.drive_duration - ) - try: - qubit_frequency[qubit] = platform.qubits[qubit].drive_frequency - matrix_element[qubit] = platform.qubits[qubit].crosstalk_matrix[qubit] - offset[qubit] = -platform.qubits[qubit].sweetspot * matrix_element[qubit] - bias_point[qubit] = params.bias_point.get( - qubit, platform.qubits[qubit].sweetspot - ) - - except KeyError: - log.warning(f"Missing flux parameters for qubit {qubit}.") + maximum_frequency = {} + freq_sweepers = [] + offset_sweepers = [] - if params.transition == "02": - if platform.qubits[qubit].anharmonicity: - qd_pulses[qubit].frequency -= platform.qubits[qubit].anharmonicity / 2 - else: - qd_pulses[qubit].frequency -= DEFAULT_ANHARMONICITY / 2 + delta_frequency_range = np.arange( + -params.freq_width / 2, params.freq_width / 2, params.freq_step + ) + for qubit in targets: + natives = platform.natives.single_qubit[qubit] + charging_energy[qubit] = platform.calibration.single_qubits[ + qubit + ].qubit.charging_energy + qd_channel, qd_pulse = natives.RX()[0] + ro_channel, ro_pulse = natives.MZ()[0] + + qd_pulse = replace(qd_pulse, duration=params.drive_duration) if params.drive_amplitude is not None: - qd_pulses[qubit].amplitude = params.drive_amplitude - - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish + qd_pulse = replace(qd_pulse, amplitude=params.drive_amplitude) + + qd_pulses[qubit] = qd_pulse + ro_pulses[qubit] = ro_pulse + + # store calibration parameters + maximum_frequency[qubit] = platform.calibration.single_qubits[ + qubit + ].qubit.maximum_frequency + matrix_element[qubit] = platform.calibration.get_crosstalk_element(qubit, qubit) + charging_energy[qubit] = platform.calibration.single_qubits[ + qubit + ].qubit.charging_energy + offset[qubit] = ( + -platform.calibration.single_qubits[qubit].qubit.sweetspot + * matrix_element[qubit] ) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - # define the parameters to sweep and their range: - delta_frequency_range = np.arange( - -params.freq_width / 2, params.freq_width / 2, params.freq_step - ) - freq_sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - # TODO : abstract common lines with qubit flux dep routine - if params.flux_qubits is None: - flux_qubits = list(platform.qubits) - else: - flux_qubits = params.flux_qubits + sequence.append((qd_channel, qd_pulse)) + sequence.append((ro_channel, Delay(duration=qd_pulse.duration))) + sequence.append((ro_channel, ro_pulse)) + + freq_sweepers.append( + Sweeper( + parameter=Parameter.frequency, + values=platform.config(qd_channel).frequency + delta_frequency_range, + channels=[qd_channel], + ) + ) - delta_bias_range = np.arange( + delta_offset_range = np.arange( -params.bias_width / 2, params.bias_width / 2, params.bias_step ) - sequences = [sequence] * len(flux_qubits) - sweepers = [ - Sweeper( - Parameter.bias, - delta_bias_range, - qubits=[platform.qubits[flux_qubit]], - type=SweeperType.OFFSET, + for q in params.flux_qubits: + flux_channel = platform.qubits[q].flux + offset0 = platform.config(flux_channel).offset + offset_sweepers.append( + Sweeper( + parameter=Parameter.offset, + values=offset0 + delta_offset_range, + channels=[flux_channel], + ) ) - for flux_qubit in flux_qubits - ] data = QubitCrosstalkData( resonator_type=platform.resonator_type, matrix_element=matrix_element, offset=offset, - qubit_frequency=qubit_frequency, + qubit_frequency=maximum_frequency, charging_energy=charging_energy, - bias_point=bias_point, + bias_point=params.bias_point, ) - options = ExecutionParameters( + options = dict( nshots=params.nshots, relaxation_time=params.relaxation_time, acquisition_type=AcquisitionType.INTEGRATION, averaging_mode=AveragingMode.CYCLIC, ) - # update bias configuration + + updates = [] for qubit in targets: if qubit in params.bias_point: - platform.qubits[qubit].flux.offset = params.bias_point[qubit] + channel = platform.qubits[qubit].flux + updates.append({channel: {"offset": params.bias_point[qubit]}}) - for flux_qubit, bias_sweeper, sequence in zip(flux_qubits, sweepers, sequences): - results = platform.sweep(sequence, options, bias_sweeper, freq_sweeper) + for flux_qubit, offset_sweeper in zip(params.flux_qubits, offset_sweepers): + results = platform.execute( + [sequence], [[offset_sweeper], freq_sweepers], **options, updates=updates + ) # retrieve the results for every qubit - for qubit in targets: - result = results[ro_pulses[qubit].serial] - if flux_qubit is None: - sweetspot = platform.qubits[qubit].flux.offset - else: - sweetspot = platform.qubits[flux_qubit].flux.offset + for i, qubit in enumerate(targets): + result = results[ro_pulses[qubit].id] data.register_qubit( qubit, flux_qubit, - signal=result.magnitude, - phase=result.phase, - freq=delta_frequency_range + qd_pulses[qubit].frequency, - bias=delta_bias_range + sweetspot, + signal=magnitude(result), + phase=phase(result), + freq=freq_sweepers[i].values, + bias=offset_sweeper.values, ) return data @@ -233,29 +215,11 @@ def _fit(data: QubitCrosstalkData) -> QubitCrosstalkResults: crosstalk_matrix = {qubit: {} for qubit in data.qubit_frequency} fitted_parameters = {} - bias_point = {} - sweetspot = {} matrix_element = {} qubit_frequency = {} qubit_frequency_bias_point = {} offset = {} - diagonal = diagonal_fit(data.diagonal) - for qubit in data.qubits: - condition = qubit in diagonal - bias_point[qubit] = data.bias_point[qubit] - matrix_element[qubit] = ( - diagonal.matrix_element[qubit] if condition else data.matrix_element[qubit] - ) - qubit_frequency[qubit] = ( - diagonal.frequency[qubit] if condition else data.qubit_frequency[qubit] - ) - offset[qubit] = ( - -diagonal.sweetspot[qubit] * diagonal.matrix_element[qubit] - if condition - else data.offset[qubit] - ) - for target_flux_qubit, qubit_data in data.data.items(): frequencies, biases = extract_feature( qubit_data.freq, @@ -265,70 +229,59 @@ def _fit(data: QubitCrosstalkData) -> QubitCrosstalkResults: ) target_qubit, flux_qubit = target_flux_qubit - if target_qubit != flux_qubit: - # fit function needs to be defined here to pass correct parameters - # at runtime - qubit_frequency_bias_point[target_qubit] = utils.transmon_frequency( - xi=bias_point[target_qubit], + qubit_frequency_bias_point[target_qubit] = ( + utils.transmon_frequency( + xi=data.bias_point[target_qubit], xj=0, d=0, - w_max=qubit_frequency[target_qubit] * HZ_TO_GHZ, - offset=offset[qubit], - normalization=matrix_element[target_qubit], + w_max=data.qubit_frequency[target_qubit] * HZ_TO_GHZ, + offset=data.offset[target_qubit], + normalization=data.matrix_element[target_qubit], charging_energy=data.charging_energy[target_qubit] * HZ_TO_GHZ, crosstalk_element=1, ) + * GHZ_TO_HZ + ) - def fit_function(x, crosstalk_element, offset): - return utils.transmon_frequency( - xi=bias_point[target_qubit], - xj=x, - d=0, - w_max=qubit_frequency[target_qubit] * HZ_TO_GHZ, - offset=offset, - normalization=matrix_element[target_qubit], - charging_energy=data.charging_energy[target_qubit] * HZ_TO_GHZ, - crosstalk_element=crosstalk_element, - ) - - try: - popt, _ = curve_fit( - fit_function, - biases, - frequencies * HZ_TO_GHZ, - bounds=((-np.inf, -1), (np.inf, 1)), - maxfev=100000, - ) - fitted_parameters[target_qubit, flux_qubit] = dict( - xi=bias_point[target_qubit], - d=0, - w_max=qubit_frequency[target_qubit] * HZ_TO_GHZ, - offset=popt[1], - normalization=matrix_element[target_qubit], - charging_energy=data.charging_energy[target_qubit] * HZ_TO_GHZ, - crosstalk_element=float(popt[0]), - ) - crosstalk_matrix[target_qubit][flux_qubit] = ( - popt[0] * matrix_element[target_qubit] - ) - except RuntimeError as e: - log.error( - f"Off-diagonal flux fit failed for qubit {flux_qubit} due to {e}." - ) + def fit_function(x, crosstalk_element, offset): + return utils.transmon_frequency( + xi=data.bias_point[target_qubit], + xj=x, + d=0, + w_max=data.qubit_frequency[target_qubit] * HZ_TO_GHZ, + offset=offset, + normalization=data.matrix_element[target_qubit], + charging_energy=data.charging_energy[target_qubit] * HZ_TO_GHZ, + crosstalk_element=crosstalk_element, + ) - else: - fitted_parameters[target_qubit, flux_qubit] = diagonal.fitted_parameters[ - target_qubit - ] - crosstalk_matrix[target_qubit][flux_qubit] = diagonal.matrix_element[ - target_qubit - ] + try: + popt, _ = curve_fit( + fit_function, + biases, + frequencies * HZ_TO_GHZ, + bounds=((-np.inf, -1), (np.inf, 1)), + maxfev=100000, + ) + fitted_parameters[target_qubit, flux_qubit] = dict( + xi=data.bias_point[target_qubit], + d=0, + w_max=data.qubit_frequency[target_qubit] * HZ_TO_GHZ, + offset=popt[1], + normalization=data.matrix_element[target_qubit], + charging_energy=data.charging_energy[target_qubit] * HZ_TO_GHZ, + crosstalk_element=float(popt[0]), + ) + crosstalk_matrix[target_qubit][flux_qubit] = ( + popt[0] * data.matrix_element[target_qubit] + ) + except RuntimeError as e: # pragma: no cover + log.error( + f"Off-diagonal flux fit failed for qubit {flux_qubit} due to {e}." + ) return QubitCrosstalkResults( - frequency=qubit_frequency, qubit_frequency_bias_point=qubit_frequency_bias_point, - sweetspot=sweetspot, - matrix_element=matrix_element, crosstalk_matrix=crosstalk_matrix, fitted_parameters=fitted_parameters, ) @@ -341,11 +294,9 @@ def _plot(data: QubitCrosstalkData, fit: QubitCrosstalkResults, target: QubitId) ) if fit is not None: labels = [ - "Qubit Frequency at Sweetspot [Hz]", "Qubit Frequency at Bias point [Hz]", ] values = [ - np.round(fit.frequency[target], 4), np.round(fit.qubit_frequency_bias_point[target], 4), ] for flux_qubit in fit.crosstalk_matrix[target]: @@ -364,7 +315,9 @@ def _plot(data: QubitCrosstalkData, fit: QubitCrosstalkResults, target: QubitId) return figures, fitting_report -def _update(results: QubitCrosstalkResults, platform: Platform, qubit: QubitId): +def _update( + results: QubitCrosstalkResults, platform: CalibrationPlatform, qubit: QubitId +): """Update crosstalk matrix.""" for flux_qubit, element in results.crosstalk_matrix[qubit].items(): diff --git a/src/qibocal/protocols/flux_dependence/qubit_flux_dependence.py b/src/qibocal/protocols/flux_dependence/qubit_flux_dependence.py index d784eb35a..458d3fabe 100644 --- a/src/qibocal/protocols/flux_dependence/qubit_flux_dependence.py +++ b/src/qibocal/protocols/flux_dependence/qubit_flux_dependence.py @@ -3,18 +3,23 @@ import numpy as np import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import ( + AcquisitionType, + AveragingMode, + Delay, + Parameter, + PulseSequence, + Sweeper, +) from scipy.optimize import curve_fit -from qibocal import update -from qibocal.auto.operation import Data, Results, Routine +from qibocal.auto.operation import Data, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log -from qibocal.protocols.qubit_spectroscopy_ef import DEFAULT_ANHARMONICITY +from qibocal.result import magnitude, phase +from qibocal.update import replace +from ... import update from ..utils import GHZ_TO_HZ, HZ_TO_GHZ, extract_feature, table_dict, table_html from . import utils from .resonator_flux_dependence import ResonatorFluxParameters @@ -27,8 +32,6 @@ class QubitFluxParameters(ResonatorFluxParameters): drive_amplitude: Optional[float] = None """Drive amplitude (optional). If defined, same amplitude will be used in all qubits. Otherwise the default amplitude defined on the platform runcard will be used""" - transition: Optional[str] = "01" - """Flux spectroscopy transition type ("01" or "02"). Default value is 01""" drive_duration: int = 2000 """Duration of the drive pulse.""" @@ -37,13 +40,13 @@ class QubitFluxParameters(ResonatorFluxParameters): class QubitFluxResults(Results): """QubitFlux outputs.""" - sweetspot: dict[QubitId, float] + sweetspot: dict[QubitId, float] = field(default_factory=dict) """Sweetspot for each qubit.""" - frequency: dict[QubitId, float] + frequency: dict[QubitId, float] = field(default_factory=dict) """Drive frequency for each qubit.""" - fitted_parameters: dict[QubitId, dict[str, float]] + fitted_parameters: dict[QubitId, dict[str, float]] = field(default_factory=dict) """Raw fitting output.""" - matrix_element: dict[QubitId, float] + matrix_element: dict[QubitId, float] = field(default_factory=dict) """V_ii coefficient.""" @@ -80,86 +83,86 @@ def register_qubit(self, qubit, freq, bias, signal, phase): def _acquisition( params: QubitFluxParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> QubitFluxData: """Data acquisition for QubitFlux Experiment.""" - # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel + delta_frequency_range = np.arange( + -params.freq_width / 2, params.freq_width / 2, params.freq_step + ) + delta_offset_range = np.arange( + -params.bias_width / 2, params.bias_width / 2, params.bias_step + ) + sequence = PulseSequence() ro_pulses = {} qd_pulses = {} qubit_frequency = {} - for qubit in targets: - qd_pulses[qubit] = platform.create_qubit_drive_pulse( - qubit, start=0, duration=params.drive_duration - ) - qubit_frequency[qubit] = platform.qubits[qubit].drive_frequency - - if params.transition == "02": - if platform.qubits[qubit].anharmonicity: - qd_pulses[qubit].frequency -= platform.qubits[qubit].anharmonicity / 2 - else: - qd_pulses[qubit].frequency -= DEFAULT_ANHARMONICITY / 2 - + freq_sweepers = [] + offset_sweepers = [] + for q in targets: + natives = platform.natives.single_qubit[q] + qd_channel, qd_pulse = natives.RX()[0] + ro_channel, ro_pulse = natives.MZ()[0] + + qd_pulse = replace(qd_pulse, duration=params.drive_duration) if params.drive_amplitude is not None: - qd_pulses[qubit].amplitude = params.drive_amplitude - - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish + qd_pulse = replace(qd_pulse, amplitude=params.drive_amplitude) + + qd_pulses[q] = qd_pulse + ro_pulses[q] = ro_pulse + qubit_frequency[q] = frequency0 = platform.config(qd_channel).frequency + + sequence.append((qd_channel, qd_pulse)) + sequence.append((ro_channel, Delay(duration=qd_pulse.duration))) + sequence.append((ro_channel, ro_pulse)) + + # define the parameters to sweep and their range: + freq_sweepers.append( + Sweeper( + parameter=Parameter.frequency, + values=frequency0 + delta_frequency_range, + channels=[qd_channel], + ) ) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - # define the parameters to sweep and their range: - delta_frequency_range = np.arange( - -params.freq_width / 2, params.freq_width / 2, params.freq_step - ) - freq_sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - - delta_bias_range = np.arange( - -params.bias_width / 2, params.bias_width / 2, params.bias_step - ) - sweepers = [ - Sweeper( - Parameter.bias, - delta_bias_range, - qubits=[platform.qubits[qubit] for qubit in targets], - type=SweeperType.OFFSET, + flux_channel = platform.qubits[q].flux + offset0 = platform.config(flux_channel).offset + offset_sweepers.append( + Sweeper( + parameter=Parameter.offset, + values=offset0 + delta_offset_range, + channels=[flux_channel], + ) ) - ] data = QubitFluxData( resonator_type=platform.resonator_type, charging_energy={ - qubit: -platform.qubits[qubit].anharmonicity for qubit in targets + qubit: platform.calibration.single_qubits[qubit].qubit.charging_energy + for qubit in targets }, qubit_frequency=qubit_frequency, ) - options = ExecutionParameters( + results = platform.execute( + [sequence], + [offset_sweepers, freq_sweepers], nshots=params.nshots, relaxation_time=params.relaxation_time, acquisition_type=AcquisitionType.INTEGRATION, averaging_mode=AveragingMode.CYCLIC, ) - for bias_sweeper in sweepers: - results = platform.sweep(sequence, options, bias_sweeper, freq_sweeper) - # retrieve the results for every qubit - for qubit in targets: - result = results[ro_pulses[qubit].serial] - sweetspot = platform.qubits[qubit].sweetspot - data.register_qubit( - qubit, - signal=result.magnitude, - phase=result.phase, - freq=delta_frequency_range + qd_pulses[qubit].frequency, - bias=delta_bias_range + sweetspot, - ) + + for i, qubit in enumerate(targets): + result = results[ro_pulses[qubit].id] + data.register_qubit( + qubit, + signal=magnitude(result), + phase=phase(result), + freq=freq_sweepers[i].values, + bias=offset_sweepers[i].values, + ) return data @@ -277,9 +280,13 @@ def _plot(data: QubitFluxData, fit: QubitFluxResults, target: QubitId): return figures, "" -def _update(results: QubitFluxResults, platform: Platform, qubit: QubitId): +def _update(results: QubitFluxResults, platform: CalibrationPlatform, qubit: QubitId): update.drive_frequency(results.frequency[qubit], platform, qubit) update.sweetspot(results.sweetspot[qubit], platform, qubit) + update.flux_offset(results.sweetspot[qubit], platform, qubit) + platform.calibration.single_qubits[qubit].qubit.maximum_frequency = int( + results.frequency[qubit] + ) update.crosstalk_matrix(results.matrix_element[qubit], platform, qubit, qubit) diff --git a/src/qibocal/protocols/flux_dependence/qubit_flux_tracking.py b/src/qibocal/protocols/flux_dependence/qubit_flux_tracking.py deleted file mode 100644 index a4f2ef407..000000000 --- a/src/qibocal/protocols/flux_dependence/qubit_flux_tracking.py +++ /dev/null @@ -1,164 +0,0 @@ -from dataclasses import dataclass - -import numpy as np -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal.auto.operation import Routine -from qibocal.config import raise_error - -from ..qubit_spectroscopy_ef import DEFAULT_ANHARMONICITY -from . import qubit_flux_dependence, utils - - -@dataclass -class QubitFluxTrackParameters(qubit_flux_dependence.QubitFluxParameters): - """QubitFluxTrack runcard inputs.""" - - -@dataclass -class QubitFluxTrackResults(qubit_flux_dependence.QubitFluxParameters): - """QubitFluxTrack outputs.""" - - -@dataclass -class QubitFluxTrackData(qubit_flux_dependence.QubitFluxData): - """QubitFluxTrack acquisition outputs.""" - - def register_qubit_track(self, qubit, freq, bias, signal, phase): - """Store output for single qubit.""" - # to be able to handle the 1D sweeper case - size = len(freq) - ar = np.empty(size, dtype=qubit_flux_dependence.QubitFluxType) - ar["freq"] = freq - ar["bias"] = [bias] * size - ar["signal"] = signal - ar["phase"] = phase - if qubit in self.data: - self.data[qubit] = np.rec.array(np.concatenate((self.data[qubit], ar))) - else: - self.data[qubit] = np.rec.array(ar) - - -def _acquisition( - params: QubitFluxTrackResults, - platform: Platform, - targets: list[QubitId], -) -> QubitFluxTrackData: - """Data acquisition for QubitFlux Experiment.""" - # create a sequence of pulses for the experiment: - # MZ - - # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel - sequence = PulseSequence() - ro_pulses = {} - qd_pulses = {} - qubit_frequency = {} - for qubit in targets: - qd_pulses[qubit] = platform.create_qubit_drive_pulse( - qubit, start=0, duration=params.drive_duration - ) - qubit_frequency[qubit] = platform.qubits[qubit].drive_frequency - if params.transition == "02": - if platform.qubits[qubit].anharmonicity != 0: - qd_pulses[qubit].frequency -= platform.qubits[qubit].anharmonicity / 2 - else: - qd_pulses[qubit].frequency -= DEFAULT_ANHARMONICITY / 2 - - if params.drive_amplitude is not None: - qd_pulses[qubit].amplitude = params.drive_amplitude - - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish - ) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - - # define the parameters to sweep and their range: - delta_frequency_range = np.arange( - -params.freq_width / 2, params.freq_width / 2, params.freq_step - ) - - delta_bias_range = np.arange( - -params.bias_width / 2, params.bias_width / 2, params.bias_step - ) - - freq_sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - - data = QubitFluxTrackData( - resonator_type=platform.resonator_type, - qubit_frequency=qubit_frequency, - charging_energy={ - qubit: -platform.qubits[qubit].anharmonicity for qubit in targets - }, - ) - - for bias in delta_bias_range: - for qubit in targets: - try: - freq_resonator = utils.transmon_readout_frequency( - xi=bias, - xj=0, - w_max=platform.qubits[qubit].drive_frequency, - d=0, - normalization=platform.qubits[qubit].normalization, - crosstalk_element=1, - offset=-platform.qubits[qubit].sweetspot - * platform.qubits[qubit].normalization, - resonator_freq=platform.qubits[qubit].bare_resonator_frequency, - g=platform.qubits[qubit].coupling, - charging_energy=data.charging_energy[qubit], - ) - # modify qubit resonator frequency - platform.qubits[qubit].readout_frequency = freq_resonator - except: - raise_error - ( - RuntimeError, - "qubit_flux_track: Not enough parameters to estimate the resonator freq for the given bias. Please run resonator spectroscopy flux and update the runcard", - ) - - # modify qubit flux - platform.qubits[qubit].flux.offset = bias - - # execute pulse sequence sweeping only qubit resonator - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - freq_sweeper, - ) - - # retrieve the results for every qubit - for qubit in targets: - result = results[ro_pulses[qubit].serial] - data.register_qubit_track( - qubit, - signal=result.magnitude, - phase=result.phase, - freq=delta_frequency_range + qd_pulses[qubit].frequency, - bias=bias + platform.qubits[qubit].sweetspot, - ) - - return data - - -qubit_flux_tracking = Routine( - _acquisition, - qubit_flux_dependence._fit, - qubit_flux_dependence._plot, - qubit_flux_dependence._update, -) -"""QubitFluxTrack Routine object.""" diff --git a/src/qibocal/protocols/flux_dependence/resonator_crosstalk.py b/src/qibocal/protocols/flux_dependence/resonator_crosstalk.py deleted file mode 100644 index 790d61a55..000000000 --- a/src/qibocal/protocols/flux_dependence/resonator_crosstalk.py +++ /dev/null @@ -1,380 +0,0 @@ -from dataclasses import dataclass, field -from typing import Optional - -import numpy as np -import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType -from scipy.optimize import curve_fit - -from ... import update -from ...auto.operation import Routine -from ...config import log -from ..utils import HZ_TO_GHZ, extract_feature, table_dict, table_html -from . import utils -from .resonator_flux_dependence import ( - ResFluxType, - ResonatorFluxData, - ResonatorFluxParameters, - ResonatorFluxResults, -) -from .resonator_flux_dependence import _fit as diagonal_fit - - -@dataclass -class ResCrosstalkParameters(ResonatorFluxParameters): - """ResonatorFlux runcard inputs.""" - - bias_point: Optional[dict[QubitId, float]] = field(default_factory=dict) - """Dictionary with {qubit_id: bias_point_qubit_id}.""" - flux_qubits: Optional[list[QubitId]] = None - """IDs of the qubits that we will sweep the flux on. - If ``None`` flux will be swept on all qubits that we are running the routine on in a multiplex fashion. - If given flux will be swept on the given qubits in a sequential fashion (n qubits will result to n different executions). - Multiple qubits may be measured in each execution as specified by the ``qubits`` option in the runcard. - """ - - -@dataclass -class ResCrosstalkResults(ResonatorFluxResults): - """ResCrosstalk outputs.""" - - resonator_frequency_bias_point: dict[QubitId, dict[QubitId, float]] = field( - default_factory=dict - ) - """Resonator frequency at bias point.""" - crosstalk_matrix: dict[QubitId, dict[QubitId, float]] = field(default_factory=dict) - """Crosstalk matrix element.""" - fitted_parameters: dict[tuple[QubitId, QubitId], dict] = field(default_factory=dict) - """Fitted parameters for each couple target-flux qubit.""" - - def __contains__(self, key: QubitId): - """Checking if qubit is in crosstalk_matrix attribute.""" - return key in self.crosstalk_matrix - - -@dataclass -class ResCrosstalkData(ResonatorFluxData): - """ResFlux acquisition outputs when ``flux_qubits`` are given.""" - - coupling: dict[QubitId, float] = field(default_factory=dict) - """Coupling parameter g for each qubit.""" - bias_point: dict[QubitId, float] = field(default_factory=dict) - """Voltage provided to each qubit.""" - bare_resonator_frequency: dict[QubitId, float] = field(default_factory=dict) - """Readout resonator frequency for each qubit.""" - resonator_frequency: dict[QubitId, float] = field(default_factory=dict) - """Readout resonator frequency for each qubit.""" - matrix_element: dict[QubitId, float] = field(default_factory=dict) - """Diagonal crosstalk matrix element.""" - offset: dict[QubitId, float] = field(default_factory=dict) - """Diagonal offset.""" - asymmetry: dict[QubitId, float] = field(default_factory=dict) - """Diagonal asymmetry.""" - data: dict[tuple[QubitId, QubitId], npt.NDArray[ResFluxType]] = field( - default_factory=dict - ) - """Raw data acquired for (qubit, qubit_flux) pairs saved in nested dictionaries.""" - - def register_qubit(self, qubit, flux_qubit, freq, bias, signal, phase): - """Store output for single qubit.""" - ar = utils.create_data_array(freq, bias, signal, phase, dtype=ResFluxType) - if (qubit, flux_qubit) in self.data: - self.data[qubit, flux_qubit] = np.rec.array( - np.concatenate((self.data[qubit, flux_qubit], ar)) - ) - else: - self.data[qubit, flux_qubit] = ar - - @property - def diagonal(self) -> ResonatorFluxData: - """Returns diagonal data acquired.""" - instance = ResonatorFluxData( - resonator_type=self.resonator_type, - qubit_frequency=self.qubit_frequency, - bare_resonator_frequency=self.bare_resonator_frequency, - charging_energy=self.charging_energy, - ) - for qubit in self.qubits: - try: - instance.data[qubit] = self.data[qubit, qubit] - except KeyError: - log.info( - f"Diagonal acquisition not found for qubit {qubit}. Runcard values will be used to perform the off-diagonal fit." - ) - - return instance - - -def _acquisition( - params: ResCrosstalkParameters, platform: Platform, targets: list[QubitId] -) -> ResCrosstalkData: - """Data acquisition for ResonatorFlux experiment.""" - sequence = PulseSequence() - ro_pulses = {} - bare_resonator_frequency = {} - resonator_frequency = {} - qubit_frequency = {} - coupling = {} - asymmetry = {} - charging_energy = {} - bias_point = {} - offset = {} - matrix_element = {} - for qubit in targets: - charging_energy[qubit] = -platform.qubits[qubit].anharmonicity - bias_point[qubit] = params.bias_point.get( - qubit, platform.qubits[qubit].sweetspot - ) - coupling[qubit] = platform.qubits[qubit].g - asymmetry[qubit] = platform.qubits[qubit].asymmetry - matrix_element[qubit] = platform.qubits[qubit].crosstalk_matrix[qubit] - offset[qubit] = -platform.qubits[qubit].sweetspot * matrix_element[qubit] - bare_resonator_frequency[qubit] = platform.qubits[ - qubit - ].bare_resonator_frequency - qubit_frequency[qubit] = platform.qubits[qubit].drive_frequency - resonator_frequency[qubit] = platform.qubits[qubit].readout_frequency - ro_pulses[qubit] = platform.create_qubit_readout_pulse(qubit, start=0) - sequence.add(ro_pulses[qubit]) - - # define the parameters to sweep and their range: - delta_frequency_range = np.arange( - -params.freq_width / 2, params.freq_width / 2, params.freq_step - ) - freq_sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - [ro_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - - if params.flux_qubits is None: - flux_qubits = list(platform.qubits) - - else: - flux_qubits = params.flux_qubits - - delta_bias_range = np.arange( - -params.bias_width / 2, params.bias_width / 2, params.bias_step - ) - sequences = [sequence] * len(flux_qubits) - sweepers = [ - Sweeper( - Parameter.bias, - delta_bias_range, - qubits=[platform.qubits[flux_qubit]], - type=SweeperType.OFFSET, - ) - for flux_qubit in flux_qubits - ] - data = ResCrosstalkData( - resonator_type=platform.resonator_type, - qubit_frequency=qubit_frequency, - offset=offset, - asymmetry=asymmetry, - resonator_frequency=resonator_frequency, - charging_energy=charging_energy, - bias_point=bias_point, - matrix_element=matrix_element, - coupling=coupling, - bare_resonator_frequency=bare_resonator_frequency, - ) - options = ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ) - for qubit in targets: - if qubit in params.bias_point: - platform.qubits[qubit].flux.offset = params.bias_point[qubit] - - for flux_qubit, bias_sweeper, sequence in zip(flux_qubits, sweepers, sequences): - results = platform.sweep(sequence, options, bias_sweeper, freq_sweeper) - # retrieve the results for every qubit - for qubit in targets: - result = results[ro_pulses[qubit].serial] - if flux_qubit is None: - sweetspot = platform.qubits[qubit].flux.offset - else: - sweetspot = platform.qubits[flux_qubit].flux.offset - data.register_qubit( - qubit, - flux_qubit, - signal=result.magnitude, - phase=result.phase, - freq=delta_frequency_range + ro_pulses[qubit].frequency, - bias=delta_bias_range + sweetspot, - ) - return data - - -def _fit(data: ResCrosstalkData) -> ResCrosstalkResults: - """ "PostProcessing for resonator crosstalk protocol.""" - - # perform first fit where corresponding qubit is moved - diagonal = diagonal_fit(data.diagonal) - - fitted_parameters = {} - crosstalk_matrix = {qubit: {} for qubit in data.qubit_frequency} - offset = {} - coupling = {} - matrix_element = {} - asymmetry = {} - resonator_frequency = {} - resonator_frequency_bias_point = {} - - for qubit in data.qubits: - - # retrieve parameters from diagonal fit if performed - condition = qubit in diagonal - coupling[qubit] = ( - diagonal.coupling[qubit] if condition else data.coupling[qubit] - ) - asymmetry[qubit] = ( - diagonal.asymmetry[qubit] if condition else data.asymmetry[qubit] - ) - matrix_element[qubit] = ( - diagonal.matrix_element[qubit] if condition else data.matrix_element[qubit] - ) - resonator_frequency[qubit] = ( - diagonal.frequency[qubit] if condition else data.resonator_frequency[qubit] - ) - offset[qubit] = ( - diagonal.fitted_parameters[qubit]["offset"] - if condition - else data.offset[qubit] - ) - - for target_flux_qubit, qubit_data in data.data.items(): - target_qubit, flux_qubit = target_flux_qubit - frequencies, biases = extract_feature( - qubit_data.freq, - qubit_data.bias, - qubit_data.signal, - "min" if data.resonator_type == "2D" else "max", - ) - - # fit valid only for non-diagonal case - # (the diagonal case was handled before) - if target_qubit != flux_qubit: - resonator_frequency_bias_point[target_qubit] = ( - utils.transmon_readout_frequency( - xi=data.bias_point[target_qubit], - xj=0, - d=asymmetry[target_qubit], - w_max=data.qubit_frequency[target_qubit] * HZ_TO_GHZ, - offset=data.offset[target_qubit], - normalization=matrix_element[target_qubit], - charging_energy=data.charging_energy[target_qubit] * HZ_TO_GHZ, - g=coupling[target_qubit], - resonator_freq=data.bare_resonator_frequency[target_qubit] - * HZ_TO_GHZ, - crosstalk_element=1, - ) - ) - - def fit_function(x, crosstalk_element): - return utils.transmon_readout_frequency( - xi=data.bias_point[target_qubit], - xj=x, - d=0, - w_max=data.qubit_frequency[target_qubit] * HZ_TO_GHZ, - offset=offset[target_qubit], - normalization=data.matrix_element[target_qubit], - charging_energy=data.charging_energy[target_qubit] * HZ_TO_GHZ, - g=coupling[target_qubit], - resonator_freq=data.bare_resonator_frequency[target_qubit] - * HZ_TO_GHZ, - crosstalk_element=crosstalk_element, - ) - - try: - popt, _ = curve_fit( - fit_function, - biases, - frequencies * HZ_TO_GHZ, - bounds=(-1, 1), - ) - fitted_parameters[target_qubit, flux_qubit] = dict( - xi=data.bias_point[qubit], - d=asymmetry[qubit], - w_max=data.qubit_frequency[target_qubit] * HZ_TO_GHZ, - offset=offset[qubit], - normalization=data.matrix_element[target_qubit], - charging_energy=data.charging_energy[target_qubit] * HZ_TO_GHZ, - g=coupling[target_qubit], - resonator_freq=data.bare_resonator_frequency[target_qubit] - * HZ_TO_GHZ, - crosstalk_element=float(popt[0]), - ) - crosstalk_matrix[target_qubit][flux_qubit] = ( - popt[0] * data.matrix_element[target_qubit] - ) - except (ValueError, RuntimeError) as e: - log.error( - f"Off-diagonal flux fit failed for qubit {flux_qubit} due to {e}." - ) - else: - fitted_parameters[target_qubit, flux_qubit] = diagonal.fitted_parameters[ - target_qubit - ] - crosstalk_matrix[target_qubit][flux_qubit] = matrix_element[qubit] - - return ResCrosstalkResults( - frequency=resonator_frequency, - asymmetry=asymmetry, - resonator_frequency_bias_point=resonator_frequency_bias_point, - coupling=coupling, - crosstalk_matrix=crosstalk_matrix, - fitted_parameters=fitted_parameters, - ) - - -def _plot(data: ResCrosstalkData, fit: ResCrosstalkResults, target: QubitId): - """Plotting function for ResonatorFlux Experiment.""" - figures, fitting_report = utils.flux_crosstalk_plot( - data, target, fit, fit_function=utils.transmon_readout_frequency - ) - if fit is not None: - labels = [ - "Resonator Frequency at Sweetspot [Hz]", - "Coupling g [MHz]", - "Asymmetry d", - "Resonator Frequency at Bias point [Hz]", - ] - values = [ - np.round(fit.frequency[target], 4), - np.round(fit.coupling[target] * 1e3, 2), - np.round(fit.asymmetry[target], 2), - np.round(fit.resonator_frequency_bias_point[target], 4), - ] - for flux_qubit in fit.crosstalk_matrix[target]: - if flux_qubit != target: - labels.append(f"Crosstalk with qubit {flux_qubit}") - else: - labels.append(f"Flux dependence") - values.append(np.round(fit.crosstalk_matrix[target][flux_qubit], 4)) - - fitting_report = table_html( - table_dict( - target, - labels, - values, - ) - ) - return figures, fitting_report - - -def _update(results: ResCrosstalkResults, platform: Platform, qubit: QubitId): - """Update crosstalk matrix.""" - for flux_qubit, element in results.crosstalk_matrix[qubit].items(): - update.crosstalk_matrix(element, platform, qubit, flux_qubit) - - -resonator_crosstalk = Routine(_acquisition, _fit, _plot, _update) -"""Resonator crosstalk Routine object""" diff --git a/src/qibocal/protocols/flux_dependence/resonator_flux_dependence.py b/src/qibocal/protocols/flux_dependence/resonator_flux_dependence.py index f560409de..5be9e1472 100644 --- a/src/qibocal/protocols/flux_dependence/resonator_flux_dependence.py +++ b/src/qibocal/protocols/flux_dependence/resonator_flux_dependence.py @@ -3,16 +3,15 @@ import numpy as np import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, PulseSequence, Sweeper from scipy.optimize import curve_fit +from qibocal.calibration import CalibrationPlatform + from ... import update -from ...auto.operation import Data, Parameters, Results, Routine +from ...auto.operation import Data, Parameters, QubitId, Results, Routine from ...config import log +from ...result import magnitude, phase from ..utils import GHZ_TO_HZ, HZ_TO_GHZ, extract_feature, table_dict, table_html from . import utils @@ -85,46 +84,59 @@ def register_qubit(self, qubit, freq, bias, signal, phase): def _acquisition( - params: ResonatorFluxParameters, platform: Platform, targets: list[QubitId] + params: ResonatorFluxParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> ResonatorFluxData: """Data acquisition for ResonatorFlux experiment.""" - sequence = PulseSequence() - ro_pulses = {} - qubit_frequency = {} - bare_resonator_frequency = {} - charging_energy = {} - for qubit in targets: - qubit_frequency[qubit] = platform.qubits[qubit].drive_frequency - bare_resonator_frequency[qubit] = platform.qubits[ - qubit - ].bare_resonator_frequency - charging_energy[qubit] = -platform.qubits[qubit].anharmonicity - ro_pulses[qubit] = platform.create_qubit_readout_pulse(qubit, start=0) - sequence.add(ro_pulses[qubit]) - - # define the parameters to sweep and their range: delta_frequency_range = np.arange( -params.freq_width / 2, params.freq_width / 2, params.freq_step ) - freq_sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - [ro_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - - delta_bias_range = np.arange( + delta_offset_range = np.arange( -params.bias_width / 2, params.bias_width / 2, params.bias_step ) - sweepers = [ - Sweeper( - Parameter.bias, - delta_bias_range, - qubits=[platform.qubits[qubit] for qubit in targets], - type=SweeperType.OFFSET, + # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel + sequence = PulseSequence() + ro_pulses = {} + qubit_frequency = {} + bare_resonator_frequency = {} + charging_energy = {} + matrix_element = {} + offset = {} + freq_sweepers = [] + offset_sweepers = [] + for q in targets: + ro_sequence = platform.natives.single_qubit[q].MZ() + ro_pulses[q] = ro_sequence[0][1] + sequence += ro_sequence + + qubit = platform.qubits[q] + offset0 = platform.config(qubit.flux).offset + freq0 = platform.config(qubit.probe).frequency + + freq_sweepers.append( + Sweeper( + parameter=Parameter.frequency, + values=freq0 + delta_frequency_range, + channels=[qubit.probe], + ) ) - ] + offset_sweepers.append( + Sweeper( + parameter=Parameter.offset, + values=offset0 + delta_offset_range, + channels=[qubit.flux], + ) + ) + + qubit_frequency[q] = platform.config(qubit.drive).frequency + bare_resonator_frequency[q] = platform.calibration.single_qubits[ + q + ].resonator.bare_frequency + matrix_element[q] = platform.calibration.get_crosstalk_element(q, q) + offset[q] = -offset0 * matrix_element[q] + charging_energy[q] = platform.calibration.single_qubits[q].qubit.charging_energy data = ResonatorFluxData( resonator_type=platform.resonator_type, @@ -132,34 +144,24 @@ def _acquisition( bare_resonator_frequency=bare_resonator_frequency, charging_energy=charging_energy, ) - options = ExecutionParameters( + results = platform.execute( + [sequence], + [offset_sweepers, freq_sweepers], nshots=params.nshots, relaxation_time=params.relaxation_time, acquisition_type=AcquisitionType.INTEGRATION, averaging_mode=AveragingMode.CYCLIC, ) - for bias_sweeper in sweepers: - results = platform.sweep(sequence, options, bias_sweeper, freq_sweeper) - # retrieve the results for every qubit - for qubit in targets: - result = results[ro_pulses[qubit].serial] - sweetspot = platform.qubits[qubit].sweetspot - - frequency =delta_frequency_range + ro_pulses[qubit].frequency - - if params.phase_delay is not None: - phase = result.average.phase - phase = np.unwrap(phase)-(frequency-frequency[0])*1e-6*params.phase_delay - else: - phase = result.average.phase - - data.register_qubit( - qubit, - signal=result.magnitude, - phase=phase, - freq=frequency, - bias=delta_bias_range + sweetspot, - ) + # retrieve the results for every qubit + for i, qubit in enumerate(targets): + result = results[ro_pulses[qubit].id] + data.register_qubit( + qubit, + signal=magnitude(result), + phase=phase(result), + freq=freq_sweepers[i].values, + bias=offset_sweepers[i].values, + ) return data @@ -291,12 +293,14 @@ def _plot(data: ResonatorFluxData, fit: ResonatorFluxResults, target: QubitId): return figures, "" -def _update(results: ResonatorFluxResults, platform: Platform, qubit: QubitId): +def _update( + results: ResonatorFluxResults, platform: CalibrationPlatform, qubit: QubitId +): + update.dressed_resonator_frequency(results.frequency[qubit], platform, qubit) update.readout_frequency(results.frequency[qubit], platform, qubit) update.coupling(results.coupling[qubit], platform, qubit) - update.asymmetry(results.coupling[qubit], platform, qubit) + update.flux_offset(results.sweetspot[qubit], platform, qubit) update.sweetspot(results.sweetspot[qubit], platform, qubit) - update.crosstalk_matrix(results.matrix_element[qubit], platform, qubit, qubit) resonator_flux = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/flux_dependence/utils.py b/src/qibocal/protocols/flux_dependence/utils.py index 5e56f7733..cf4395446 100644 --- a/src/qibocal/protocols/flux_dependence/utils.py +++ b/src/qibocal/protocols/flux_dependence/utils.py @@ -1,8 +1,6 @@ import numpy as np import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab.platform import Platform -from qibolab.qubits import QubitId from ..utils import HZ_TO_GHZ @@ -174,25 +172,6 @@ def flux_crosstalk_plot(data, qubit, fit, fit_function): row=1, col=col + 1, ) - elif flux_qubit in fit.fitted_parameters: - diagonal_params = fit.fitted_parameters[qubit, qubit] - fig.add_trace( - go.Scatter( - x=fit_function( - qubit_data.bias, - **diagonal_params, - ), - y=qubit_data.bias, - showlegend=not any( - isinstance(trace, go.Scatter) for trace in fig.data - ), - legendgroup="Fit", - name="Fit", - marker=dict(color="green"), - ), - row=1, - col=col + 1, - ) fig.update_xaxes( title_text="Frequency [GHz]", @@ -346,73 +325,3 @@ def qubit_flux_dependence_fit_bounds(qubit_frequency: float): 1, ], ) - - -def crosstalk_matrix(platform: Platform, qubits: list[QubitId]) -> np.ndarray: - """Computing crosstalk matrix for number of qubits selected. - The matrix returns has the following matrix element: - (M)ij = qubits[i].crosstalk_matrix[qubits[j]] - """ - size = len(qubits) - matrix = np.ones((size, size)) - for i in range(size): - for j in range(size): - matrix[i, j] = platform.qubits[qubits[i]].crosstalk_matrix[qubits[j]] - - return matrix - - -def compensation_matrix(platform: Platform, qubits: list[QubitId]) -> np.ndarray: - """Compensation matrix C computed as M C = diag(M') where M is the - crosstalk matrix. - For more details check: https://web.physics.ucsb.edu/~martinisgroup/theses/Chen2018.pdf - 8.2.3 - """ - size = len(qubits) - matrix = np.ones((size, size)) - crosstalk = crosstalk_matrix(platform, qubits) - for i in range(size): - for j in range(size): - if i == j: - matrix[i, j] = 1 - else: - matrix[i, j] = -crosstalk[i, j] / crosstalk[i, i] - - return matrix - - -def invert_transmon_freq(target_freq: float, platform: Platform, qubit: QubitId): - """Return right side of equation matrix * total_flux = f(target_freq). - Target frequency shoudl be expressed in GHz. - """ - charging_energy = -platform.qubits[qubit].anharmonicity * HZ_TO_GHZ - offset = ( - -platform.qubits[qubit].sweetspot - * platform.qubits[qubit].crosstalk_matrix[qubit] - ) - w_max = platform.qubits[qubit].drive_frequency * HZ_TO_GHZ - d = platform.qubits[qubit].asymmetry - angle = np.sqrt( - 1 - / (1 - d**2) - * (((target_freq + charging_energy) / (w_max + charging_energy)) ** 4 - d**2) - ) - return 1 / np.pi * np.arccos(angle) - offset - - -def frequency_to_bias( - target_freqs: dict[QubitId, float], platform: Platform -) -> np.ndarray: - """Starting from set of target_freqs computes bias points using the compensation matrix.""" - qubits = list(target_freqs) - inverted_crosstalk_matrix = np.linalg.inv( - crosstalk_matrix(platform, qubits) @ compensation_matrix(platform, qubits) - ) - transmon_freq = np.array( - [ - invert_transmon_freq(freq, platform, qubit) - for qubit, freq in target_freqs.items() - ] - ) - bias_array = inverted_crosstalk_matrix @ transmon_freq - return {qubit: bias_array[index] for index, qubit in enumerate(qubits)} diff --git a/src/qibocal/protocols/qubit_power_spectroscopy.py b/src/qibocal/protocols/qubit_power_spectroscopy.py index 5b77172bb..0380d9295 100644 --- a/src/qibocal/protocols/qubit_power_spectroscopy.py +++ b/src/qibocal/protocols/qubit_power_spectroscopy.py @@ -4,14 +4,20 @@ import numpy as np import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal.auto.operation import Parameters, Results, Routine - +from qibolab import ( + AcquisitionType, + AveragingMode, + Delay, + Parameter, + PulseSequence, + Sweeper, +) + +from qibocal.auto.operation import Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform + +from ..result import magnitude, phase +from ..update import replace from .qubit_spectroscopy import QubitSpectroscopyResults from .resonator_punchout import ResonatorPunchoutData from .utils import HZ_TO_GHZ @@ -25,16 +31,14 @@ class QubitPowerSpectroscopyParameters(Parameters): """Width for frequency sweep relative to the drive frequency [Hz].""" freq_step: int """Frequency step for sweep [Hz].""" - min_amp_factor: float - """Minimum amplitude multiplicative factor.""" - max_amp_factor: float - """Maximum amplitude multiplicative factor.""" - step_amp_factor: float - """Step amplitude multiplicative factor.""" + min_amp: float + """Minimum amplitude.""" + max_amp: float + """Maximum amplitude.""" + step_amp: float + """Step amplitude.""" duration: int """Drive duration.""" - amplitude: Optional[float] = None - """Initial drive amplitude.""" @dataclass @@ -44,7 +48,7 @@ class QubitPowerSpectroscopyData(ResonatorPunchoutData): def _acquisition( params: QubitPowerSpectroscopyParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> QubitPowerSpectroscopyData: """Perform a qubit spectroscopy experiment with different amplitudes. @@ -58,71 +62,61 @@ def _acquisition( sequence = PulseSequence() ro_pulses = {} qd_pulses = {} - amplitudes = {} - for qubit in targets: - qd_pulses[qubit] = platform.create_qubit_drive_pulse( - qubit, start=0, duration=params.duration - ) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish - ) - if params.amplitude is not None: - qd_pulses[qubit].amplitude = params.amplitude - amplitudes[qubit] = qd_pulses[qubit].amplitude - - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - - # define the parameters to sweep and their range: - # drive frequency + freq_sweepers = {} delta_frequency_range = np.arange( -params.freq_width / 2, params.freq_width / 2, params.freq_step ) - freq_sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - # drive amplitude - amplitude_range = np.arange( - params.min_amp_factor, params.max_amp_factor, params.step_amp_factor - ) + for qubit in targets: + natives = platform.natives.single_qubit[qubit] + qd_channel, qd_pulse = natives.RX()[0] + ro_channel, ro_pulse = natives.MZ()[0] + + qd_pulse = replace(qd_pulse, duration=params.duration) + + qd_pulses[qubit] = qd_pulse + ro_pulses[qubit] = ro_pulse + + sequence.append((qd_channel, qd_pulse)) + sequence.append((ro_channel, Delay(duration=qd_pulse.duration))) + sequence.append((ro_channel, ro_pulse)) + + f0 = platform.config(qd_channel).frequency + freq_sweepers[qubit] = Sweeper( + parameter=Parameter.frequency, + values=f0 + delta_frequency_range, + channels=[qd_channel], + ) + amp_sweeper = Sweeper( - Parameter.amplitude, - amplitude_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.FACTOR, + parameter=Parameter.amplitude, + range=(params.min_amp, params.max_amp, params.step_amp), + pulses=[qd_pulses[qubit] for qubit in targets], ) # data data = QubitPowerSpectroscopyData( - amplitudes=amplitudes, resonator_type=platform.resonator_type, ) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - amp_sweeper, - freq_sweeper, + results = platform.execute( + [sequence], + [[amp_sweeper], [freq_sweepers[q] for q in targets]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, ) # retrieve the results for every qubit for qubit, ro_pulse in ro_pulses.items(): # average signal, phase, i and q over the number of shots defined in the runcard - result = results[ro_pulse.serial] + result = results[ro_pulse.id] data.register_qubit( qubit, - signal=result.magnitude, - phase=result.phase, - freq=delta_frequency_range + qd_pulses[qubit].frequency, - amp=amplitude_range * amplitudes[qubit], + signal=magnitude(result), + phase=phase(result), + freq=freq_sweepers[qubit].values, + amp=amp_sweeper.values, ) return data diff --git a/src/qibocal/protocols/qubit_spectroscopy.py b/src/qibocal/protocols/qubit_spectroscopy.py index ae60f93f7..7362de178 100644 --- a/src/qibocal/protocols/qubit_spectroscopy.py +++ b/src/qibocal/protocols/qubit_spectroscopy.py @@ -2,14 +2,14 @@ from typing import Optional import numpy as np -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import Delay, Parameter, PulseSequence, Sweeper -from qibocal import update -from qibocal.auto.operation import Parameters, Results, Routine +from qibocal.auto.operation import Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.result import magnitude, phase +from qibocal.update import replace +from .. import update from .resonator_spectroscopy import ResonatorSpectroscopyData, ResSpecType from .utils import chi2_reduced, lorentzian, lorentzian_fit, spectroscopy_plot @@ -53,67 +53,84 @@ class QubitSpectroscopyData(ResonatorSpectroscopyData): def _acquisition( - params: QubitSpectroscopyParameters, platform: Platform, targets: list[QubitId] + params: QubitSpectroscopyParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> QubitSpectroscopyData: """Data acquisition for qubit spectroscopy.""" # create a sequence of pulses for the experiment: # long drive probing pulse - MZ + delta_frequency_range = np.arange( + -params.freq_width / 2, params.freq_width / 2, params.freq_step + ) + # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel sequence = PulseSequence() ro_pulses = {} qd_pulses = {} amplitudes = {} + sweepers = [] for qubit in targets: - qd_pulses[qubit] = platform.create_qubit_drive_pulse( - qubit, start=0, duration=params.drive_duration - ) - if params.drive_amplitude is not None: - qd_pulses[qubit].amplitude = params.drive_amplitude - - amplitudes[qubit] = qd_pulses[qubit].amplitude + natives = platform.natives.single_qubit[qubit] + qd_channel, qd_pulse = natives.RX()[0] + ro_channel, ro_pulse = natives.MZ()[0] - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish + qd_pulse = replace(qd_pulse, duration=params.drive_duration) + if params.drive_amplitude is not None: + qd_pulse = replace(qd_pulse, amplitude=params.drive_amplitude) + + amplitudes[qubit] = qd_pulse.amplitude + qd_pulses[qubit] = qd_pulse + ro_pulses[qubit] = ro_pulse + + sequence.append((qd_channel, qd_pulse)) + sequence.append((ro_channel, Delay(duration=qd_pulse.duration))) + sequence.append((ro_channel, ro_pulse)) + + f0 = platform.config(qd_channel).frequency + sweepers.append( + Sweeper( + parameter=Parameter.frequency, + values=f0 + delta_frequency_range, + channels=[qd_channel], + ) ) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - - # define the parameter to sweep and its range: - delta_frequency_range = np.arange( - -params.freq_width / 2, params.freq_width / 2, params.freq_step - ) - sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) # Create data structure for data acquisition. data = QubitSpectroscopyData( resonator_type=platform.resonator_type, amplitudes=amplitudes ) - results = platform.sweep( - sequence, - params.execution_parameters, - sweeper, + results = platform.execute( + [sequence], + [sweepers], + **params.execution_parameters, ) # retrieve the results for every qubit for qubit, ro_pulse in ro_pulses.items(): - result = results[ro_pulse.serial] + result = results[ro_pulse.id] # store the results + f0 = platform.config(platform.qubits[qubit].drive).frequency + signal = magnitude(result) + _phase = phase(result) + if len(signal.shape) > 1: + error_signal = np.std(signal, axis=0, ddof=1) / np.sqrt(signal.shape[0]) + signal = np.mean(signal, axis=0) + error_phase = np.std(_phase, axis=0, ddof=1) / np.sqrt(_phase.shape[0]) + _phase = np.mean(_phase, axis=0) + else: + error_signal, error_phase = None, None data.register_qubit( ResSpecType, (qubit), dict( - signal=result.average.magnitude, - phase=result.average.phase, - freq=delta_frequency_range + qd_pulses[qubit].frequency, - error_signal=result.average.std, - error_phase=result.phase_std, + signal=signal, + phase=_phase, + freq=delta_frequency_range + f0, + error_signal=error_signal, + error_phase=error_phase, ), ) return data @@ -156,7 +173,12 @@ def _plot(data: QubitSpectroscopyData, target: QubitId, fit: QubitSpectroscopyRe return spectroscopy_plot(data, target, fit) -def _update(results: QubitSpectroscopyResults, platform: Platform, target: QubitId): +def _update( + results: QubitSpectroscopyResults, platform: CalibrationPlatform, target: QubitId +): + platform.calibration.single_qubits[target].qubit.frequency_01 = results.frequency[ + target + ] update.drive_frequency(results.frequency[target], platform, target) diff --git a/src/qibocal/protocols/qubit_spectroscopy_ef.py b/src/qibocal/protocols/qubit_spectroscopy_ef.py index 72ac82f86..c43473f2f 100644 --- a/src/qibocal/protocols/qubit_spectroscopy_ef.py +++ b/src/qibocal/protocols/qubit_spectroscopy_ef.py @@ -1,14 +1,14 @@ from dataclasses import asdict, dataclass, field import numpy as np -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import Delay, Parameter, PulseSequence, Sweeper -from qibocal import update -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.update import replace +from .. import update +from ..result import magnitude, phase from .qubit_spectroscopy import ( QubitSpectroscopyData, QubitSpectroscopyParameters, @@ -18,9 +18,6 @@ from .resonator_spectroscopy import ResSpecType from .utils import spectroscopy_plot, table_dict, table_html -DEFAULT_ANHARMONICITY = 300e6 -"""Initial guess for anharmonicity.""" - @dataclass class QubitSpectroscopyEFParameters(QubitSpectroscopyParameters): @@ -53,7 +50,9 @@ def fit_ef(data: QubitSpectroscopyEFData) -> QubitSpectroscopyEFResults: def _acquisition( - params: QubitSpectroscopyEFParameters, platform: Platform, targets: list[QubitId] + params: QubitSpectroscopyEFParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> QubitSpectroscopyEFData: """Data acquisition for qubit spectroscopy ef protocol. @@ -71,77 +70,81 @@ def _acquisition( # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel sequence = PulseSequence() ro_pulses = {} - qd_pulses = {} - rx_pulses = {} amplitudes = {} + sweepers = [] drive_frequencies = {} - for qubit in targets: - rx_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - drive_frequencies[qubit] = rx_pulses[qubit].frequency - qd_pulses[qubit] = platform.create_qubit_drive_pulse( - qubit, start=rx_pulses[qubit].finish, duration=params.drive_duration - ) - if platform.qubits[qubit].native_gates.RX12.frequency is None: + delta_frequency_range = np.arange( + -params.freq_width, params.freq_width, params.freq_step + ) + for qubit in targets: + natives = platform.natives.single_qubit[qubit] - qd_pulses[qubit].frequency = ( - rx_pulses[qubit].frequency + DEFAULT_ANHARMONICITY - ) - else: - qd_pulses[qubit].frequency = platform.qubits[ - qubit - ].native_gates.RX12.frequency + qd_channel, qd_pulse = natives.RX()[0] + qd12_channel, qd12_pulse = natives.RX12()[0] + ro_channel, ro_pulse = natives.MZ()[0] + qd12_pulse = replace(qd12_pulse, duration=params.drive_duration) if params.drive_amplitude is not None: - qd_pulses[qubit].amplitude = params.drive_amplitude + qd12_pulse = replace(qd12_pulse, amplitude=params.drive_amplitude) - amplitudes[qubit] = qd_pulses[qubit].amplitude + amplitudes[qubit] = qd12_pulse.amplitude + ro_pulses[qubit] = ro_pulse - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish + sequence.append((qd_channel, qd_pulse)) + sequence.append((qd12_channel, Delay(duration=qd_pulse.duration))) + sequence.append((qd12_channel, qd12_pulse)) + sequence.append( + (ro_channel, Delay(duration=qd_pulse.duration + qd12_pulse.duration)) + ) + sequence.append((ro_channel, ro_pulse)) + + drive_frequencies[qubit] = platform.config(qd_channel).frequency + sweepers.append( + Sweeper( + parameter=Parameter.frequency, + values=platform.config(qd12_channel).frequency + delta_frequency_range, + channels=[qd12_channel], + ) ) - sequence.add(rx_pulses[qubit]) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - - # define the parameter to sweep and its range: - # sweep only before qubit frequency - delta_frequency_range = np.arange( - -params.freq_width, params.freq_width, params.freq_step - ) - sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - # Create data structure for data acquisition. data = QubitSpectroscopyEFData( resonator_type=platform.resonator_type, amplitudes=amplitudes, drive_frequencies=drive_frequencies, ) - results = platform.sweep( - sequence, - params.execution_parameters, - sweeper, + results = platform.execute( + [sequence], + [sweepers], + **params.execution_parameters, ) # retrieve the results for every qubit for qubit, ro_pulse in ro_pulses.items(): - result = results[ro_pulse.serial] - # store the results + result = results[ro_pulse.id] + + f0 = platform.config(platform.qubits[qubit].drive_qudits[1, 2]).frequency + + signal = magnitude(result) + _phase = phase(result) + if len(signal.shape) > 1: + error_signal = np.std(signal, axis=0, ddof=1) / np.sqrt(signal.shape[0]) + signal = np.mean(signal, axis=0) + error_phase = np.std(_phase, axis=0, ddof=1) / np.sqrt(_phase.shape[0]) + _phase = np.mean(_phase, axis=0) + else: + error_signal, error_phase = None, None + data.register_qubit( ResSpecType, (qubit), dict( - signal=result.average.magnitude, - phase=result.average.phase, - freq=delta_frequency_range + qd_pulses[qubit].frequency, - error_signal=result.average.std, - error_phase=result.phase_std, + signal=signal, + phase=_phase, + freq=delta_frequency_range + f0, + error_signal=error_signal, + error_phase=error_phase, ), ) return data @@ -194,10 +197,14 @@ def _plot( return figures, report -def _update(results: QubitSpectroscopyEFResults, platform: Platform, target: QubitId): +def _update( + results: QubitSpectroscopyEFResults, platform: CalibrationPlatform, target: QubitId +): """Update w12 frequency""" update.frequency_12_transition(results.frequency[target], platform, target) - update.anharmonicity(results.anharmonicity[target], platform, target) + platform.calibration.single_qubits[target].qubit.frequency_12 = results.frequency[ + target + ] qubit_spectroscopy_ef = Routine(_acquisition, fit_ef, _plot, _update) diff --git a/src/qibocal/protocols/qutrit_classification.py b/src/qibocal/protocols/qutrit_classification.py index fdb3fecaa..45a223d32 100644 --- a/src/qibocal/protocols/qutrit_classification.py +++ b/src/qibocal/protocols/qutrit_classification.py @@ -1,12 +1,10 @@ from dataclasses import dataclass, field from typing import Optional -from qibolab import AcquisitionType, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, PulseSequence -from qibocal.auto.operation import Results, Routine +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.protocols.classification import ( ClassificationType, SingleShotClassificationData, @@ -14,6 +12,9 @@ ) from qibocal.protocols.utils import plot_results +from ..auto.operation import Results +from ..config import log + COLUMNWIDTH = 600 LEGEND_FONT_SIZE = 20 TITLE_SIZE = 25 @@ -41,7 +42,7 @@ class QutritClassificationResults(Results): def _acquisition( params: QutritClassificationParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> QutritClassificationData: """ @@ -62,49 +63,96 @@ def _acquisition( """ # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel - states_sequences = [PulseSequence() for _ in range(3)] - ro_pulses = {} + states = [0, 1, 2] + sequences, all_ro_pulses = [], [] + native = platform.natives.single_qubit + + updates = [] for qubit in targets: - rx_pulse = platform.create_RX_pulse(qubit, start=0) - rx12_pulse = platform.create_RX12_pulse(qubit, start=rx_pulse.finish) - drive_pulses = [rx_pulse, rx12_pulse] - ro_pulses[qubit] = [] - for i, sequence in enumerate(states_sequences): - sequence.add(*drive_pulses[:i]) - start = drive_pulses[i - 1].finish if i != 0 else 0 - ro_pulses[qubit].append( - platform.create_qubit_readout_pulse(qubit, start=start) + channel = platform.qubits[qubit].probe + try: + updates.append( + { + channel: { + "frequency": platform.calibration.single_qubits[ + qubit + ].readout.qudits_frequency[1] + } + } ) - sequence.add(ro_pulses[qubit][-1]) + except KeyError: + log.warning(f"No readout frequency for state 1 for qubit {qubit}.") + + for state in states: + ro_pulses = {} + sequence = PulseSequence() + for q in targets: + ro_sequence = native[q].MZ() + ro_pulses[q] = ro_sequence[0][1].id + sequence += ro_sequence + + if state == 1: + rx_sequence = PulseSequence() + for q in targets: + rx_sequence += native[q].RX() + sequence = rx_sequence | sequence + + if state == 2: + rx12_sequence = PulseSequence() + for q in targets: + rx12_sequence += native[q].RX() | native[q].RX12() + sequence = rx12_sequence | sequence + + sequences.append(sequence) + all_ro_pulses.append(ro_pulses) data = QutritClassificationData( nshots=params.nshots, classifiers_list=params.classifiers_list, savedir=params.savedir, ) - states_results = [] - for sequence in states_sequences: - states_results.append( - platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - ), - ) - ) + options = dict( + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + ) + + updates = [] for qubit in targets: - for state, state_result in enumerate(states_results): - result = state_result[ro_pulses[qubit][state].serial] + channel = platform.qubits[qubit].probe + try: + # we readout at the readout frequency of |1> for better discrimination + updates.append( + { + channel: { + "frequency": platform.calibration.single_qubits[ + qubit + ].readout.qudits_frequency[1] + } + } + ) + except KeyError: + log.warning(f"No readout frequency for state 1 for qubit {qubit}.") + + if params.unrolling: + results = platform.execute(sequences, **options, updates=updates) + else: + results = {} + for sequence in sequences: + results.update(platform.execute([sequence], **options, updates=updates)) + + for state, ro_pulses in zip(states, all_ro_pulses): + for qubit in targets: + serial = ro_pulses[qubit] + result = results[serial] data.register_qubit( ClassificationType, (qubit), dict( + i=result[..., 0], + q=result[..., 1], state=[state] * params.nshots, - i=result.voltage_i, - q=result.voltage_q, ), ) @@ -120,7 +168,7 @@ def _plot( target: QubitId, fit: QutritClassificationResults, ): - figures = plot_results(data, target, 3, fit) + figures = plot_results(data, target, 3, None) fitting_report = "" return figures, fitting_report diff --git a/src/qibocal/protocols/rabi/amplitude.py b/src/qibocal/protocols/rabi/amplitude.py index 4a3d4b209..bf38d443c 100644 --- a/src/qibocal/protocols/rabi/amplitude.py +++ b/src/qibocal/protocols/rabi/amplitude.py @@ -2,14 +2,13 @@ import numpy as np import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper from qibocal import update -from qibocal.auto.operation import Data, Routine +from qibocal.auto.operation import Data, QubitId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log +from qibocal.result import probability from ..utils import chi2_reduced, fallback_period, guess_period from . import utils @@ -38,6 +37,8 @@ class RabiAmplitudeResults(RabiAmplitudeSignalResults): class RabiAmplitudeData(Data): """RabiAmplitude data acquisition.""" + rx90: bool + """Pi or Pi_half calibration""" durations: dict[QubitId, float] = field(default_factory=dict) """Pulse durations provided by the user.""" data: dict[QubitId, npt.NDArray[RabiAmpType]] = field(default_factory=dict) @@ -45,7 +46,9 @@ class RabiAmplitudeData(Data): def _acquisition( - params: RabiAmplitudeParameters, platform: Platform, targets: list[QubitId] + params: RabiAmplitudeParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> RabiAmplitudeData: r""" Data acquisition for Rabi experiment sweeping amplitude. @@ -53,43 +56,34 @@ def _acquisition( to find the drive pulse amplitude that creates a rotation of a desired angle. """ - sequence, qd_pulses, _, durations = utils.sequence_amplitude( - targets, params, platform - ) - # define the parameter to sweep and its range: - # qubit drive pulse amplitude - qd_pulse_amplitude_range = np.arange( - params.min_amp_factor, - params.max_amp_factor, - params.step_amp_factor, + sequence, qd_pulses, ro_pulses, durations = utils.sequence_amplitude( + targets, params, platform, params.rx90 ) + sweeper = Sweeper( - Parameter.amplitude, - qd_pulse_amplitude_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.FACTOR, + parameter=Parameter.amplitude, + range=(params.min_amp, params.max_amp, params.step_amp), + pulses=[qd_pulses[qubit] for qubit in targets], ) - data = RabiAmplitudeData(durations=durations) + data = RabiAmplitudeData(durations=durations, rx90=params.rx90) # sweep the parameter - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ), - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, ) for qubit in targets: - prob = results[qubit].probability(state=1) + prob = probability(results[ro_pulses[qubit].id], state=1) data.register_qubit( RabiAmpType, (qubit), dict( - amp=qd_pulses[qubit].amplitude * qd_pulse_amplitude_range, + amp=sweeper.values, prob=prob.tolist(), error=np.sqrt(prob * (1 - prob) / params.nshots).tolist(), ), @@ -136,17 +130,21 @@ def _fit(data: RabiAmplitudeData) -> RabiAmplitudeResults: except Exception as e: log.warning(f"Rabi fit failed for qubit {qubit} due to {e}.") - return RabiAmplitudeResults(pi_pulse_amplitudes, durations, fitted_parameters, chi2) + return RabiAmplitudeResults( + pi_pulse_amplitudes, durations, fitted_parameters, data.rx90, chi2 + ) def _plot(data: RabiAmplitudeData, target: QubitId, fit: RabiAmplitudeResults = None): """Plotting function for RabiAmplitude.""" - return utils.plot_probabilities(data, target, fit) + return utils.plot_probabilities(data, target, fit, data.rx90) -def _update(results: RabiAmplitudeResults, platform: Platform, target: QubitId): - update.drive_amplitude(results.amplitude[target], platform, target) - update.drive_duration(results.length[target], platform, target) +def _update( + results: RabiAmplitudeResults, platform: CalibrationPlatform, target: QubitId +): + update.drive_amplitude(results.amplitude[target], results.rx90, platform, target) + update.drive_duration(results.length[target], results.rx90, platform, target) rabi_amplitude = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/rabi/amplitude_frequency.py b/src/qibocal/protocols/rabi/amplitude_frequency.py index 1de63c3f2..ec7f03b05 100644 --- a/src/qibocal/protocols/rabi/amplitude_frequency.py +++ b/src/qibocal/protocols/rabi/amplitude_frequency.py @@ -6,12 +6,10 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import ( HZ_TO_GHZ, @@ -22,6 +20,7 @@ table_html, ) +from ...result import probability from .amplitude_frequency_signal import ( RabiAmplitudeFreqSignalData, RabiAmplitudeFrequencySignalParameters, @@ -74,60 +73,52 @@ def register_qubit(self, qubit, freq, amp, prob, error): def _acquisition( - params: RabiAmplitudeFrequencyParameters, platform: Platform, targets: list[QubitId] + params: RabiAmplitudeFrequencyParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> RabiAmplitudeFreqData: """Data acquisition for Rabi experiment sweeping amplitude.""" sequence, qd_pulses, ro_pulses, durations = sequence_amplitude( - targets, params, platform + targets, params, platform, params.rx90 ) - - # qubit drive pulse amplitude - amplitude_range = np.arange( - params.min_amp_factor, - params.max_amp_factor, - params.step_amp_factor, - ) - sweeper_amp = Sweeper( - Parameter.amplitude, - amplitude_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.FACTOR, - ) - - # qubit drive pulse amplitude frequency_range = np.arange( params.min_freq, params.max_freq, params.step_freq, ) - sweeper_freq = Sweeper( - Parameter.frequency, - frequency_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, + freq_sweepers = {} + for qubit in targets: + channel = platform.qubits[qubit].drive + freq_sweepers[qubit] = Sweeper( + parameter=Parameter.frequency, + values=platform.config(channel).frequency + frequency_range, + channels=[channel], + ) + amp_sweeper = Sweeper( + parameter=Parameter.amplitude, + range=(params.min_amp, params.max_amp, params.step_amp), + pulses=[qd_pulses[qubit] for qubit in targets], ) - data = RabiAmplitudeFreqData(durations=durations) + data = RabiAmplitudeFreqData(durations=durations, rx90=params.rx90) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ), - sweeper_amp, - sweeper_freq, + results = platform.execute( + [sequence], + [[amp_sweeper], [freq_sweepers[q] for q in targets]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, ) + for qubit in targets: - result = results[ro_pulses[qubit].serial] - prob = result.probability(state=1) + result = results[ro_pulses[qubit].id] + prob = probability(result, state=1) data.register_qubit( qubit=qubit, - freq=qd_pulses[qubit].frequency + frequency_range, - amp=qd_pulses[qubit].amplitude * amplitude_range, + freq=freq_sweepers[qubit].values, + amp=amp_sweeper.values, prob=prob.tolist(), error=np.sqrt(prob * (1 - prob) / params.nshots).tolist(), ) @@ -171,11 +162,12 @@ def _fit(data: RabiAmplitudeFreqData) -> RabiAmplitudeFrequencyResults: pguess, sigma=error, signal=False, + x_limits=(x_min, x_max), + y_limits=(y_min, y_max), ) - fitted_frequencies[qubit] = frequency fitted_amplitudes[qubit] = [pi_pulse_parameter, perr[2] / 2] - fitted_parameters[qubit] = popt.tolist() + fitted_parameters[qubit] = popt if isinstance(popt, list) else popt.tolist() chi2[qubit] = ( chi2_reduced( @@ -194,6 +186,7 @@ def _fit(data: RabiAmplitudeFreqData) -> RabiAmplitudeFrequencyResults: fitted_parameters=fitted_parameters, frequency=fitted_frequencies, chi2=chi2, + rx90=data.rx90, ) @@ -221,16 +214,17 @@ def _plot( figures.append(fig) + fig.add_trace( + go.Heatmap( + x=amplitudes, + y=frequencies, + z=qubit_data.prob, + ), + row=1, + col=1, + ) + if fit is not None: - fig.add_trace( - go.Heatmap( - x=amplitudes, - y=frequencies, - z=qubit_data.prob, - ), - row=1, - col=1, - ) fig.add_trace( go.Scatter( x=[min(amplitudes), max(amplitudes)], @@ -241,10 +235,12 @@ def _plot( row=1, col=1, ) + pulse_name = "Pi-half pulse" if data.rx90 else "Pi pulse" + fitting_report = table_html( table_dict( target, - ["Optimal rabi frequency", "Pi-pulse amplitude"], + ["Optimal rabi frequency", f"{pulse_name} amplitude"], [ fit.frequency[target], f"{fit.amplitude[target][0]:.6f} +- {fit.amplitude[target][1]:.6f} [a.u.]", diff --git a/src/qibocal/protocols/rabi/amplitude_frequency_signal.py b/src/qibocal/protocols/rabi/amplitude_frequency_signal.py index 5bd24ed6e..a03b30658 100644 --- a/src/qibocal/protocols/rabi/amplitude_frequency_signal.py +++ b/src/qibocal/protocols/rabi/amplitude_frequency_signal.py @@ -7,13 +7,11 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper from qibocal import update -from qibocal.auto.operation import Data, Parameters, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import ( HZ_TO_GHZ, @@ -23,6 +21,7 @@ table_html, ) +from ...result import magnitude, phase from .amplitude_signal import RabiAmplitudeSignalResults from .utils import fit_amplitude_function, sequence_amplitude @@ -31,18 +30,20 @@ class RabiAmplitudeFrequencySignalParameters(Parameters): """RabiAmplitudeFrequency runcard inputs.""" - min_amp_factor: float - """Minimum amplitude multiplicative factor.""" - max_amp_factor: float - """Maximum amplitude multiplicative factor.""" - step_amp_factor: float - """Step amplitude multiplicative factor.""" + min_amp: float + """Minimum amplitude.""" + max_amp: float + """Maximum amplitude.""" + step_amp: float + """Step amplitude.""" min_freq: int """Minimum frequency as an offset.""" max_freq: int """Maximum frequency as an offset.""" step_freq: int """Frequency to use as step for the scan.""" + rx90: bool = False + """Calibration of native pi pulse, if true calibrates pi/2 pulse""" pulse_length: Optional[float] = None """RX pulse duration [ns].""" @@ -53,6 +54,8 @@ class RabiAmplitudeFrequencySignalResults(RabiAmplitudeSignalResults): frequency: dict[QubitId, Union[float, list[float]]] """Drive frequency for each qubit.""" + rx90: bool + """Pi or Pi_half calibration""" RabiAmpFreqSignalType = np.dtype( @@ -70,6 +73,8 @@ class RabiAmplitudeFrequencySignalResults(RabiAmplitudeSignalResults): class RabiAmplitudeFreqSignalData(Data): """RabiAmplitudeFreqSignal data acquisition.""" + rx90: bool + """Pi or Pi_half calibration""" durations: dict[QubitId, float] = field(default_factory=dict) """Pulse durations provided by the user.""" data: dict[QubitId, npt.NDArray[RabiAmpFreqSignalType]] = field( @@ -99,62 +104,52 @@ def frequencies(self, qubit): def _acquisition( params: RabiAmplitudeFrequencySignalParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> RabiAmplitudeFreqSignalData: """Data acquisition for Rabi experiment sweeping amplitude.""" sequence, qd_pulses, ro_pulses, durations = sequence_amplitude( - targets, params, platform + targets, params, platform, params.rx90 ) - # qubit drive pulse amplitude - amplitude_range = np.arange( - params.min_amp_factor, - params.max_amp_factor, - params.step_amp_factor, - ) - sweeper_amp = Sweeper( - Parameter.amplitude, - amplitude_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.FACTOR, - ) - - # qubit drive pulse amplitude frequency_range = np.arange( params.min_freq, params.max_freq, params.step_freq, ) - sweeper_freq = Sweeper( - Parameter.frequency, - frequency_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, + freq_sweepers = {} + for qubit in targets: + channel = platform.qubits[qubit].drive + freq_sweepers[qubit] = Sweeper( + parameter=Parameter.frequency, + values=platform.config(channel).frequency + frequency_range, + channels=[channel], + ) + amp_sweeper = Sweeper( + parameter=Parameter.amplitude, + range=(params.min_amp, params.max_amp, params.step_amp), + pulses=[qd_pulses[qubit] for qubit in targets], ) - data = RabiAmplitudeFreqSignalData(durations=durations) + data = RabiAmplitudeFreqSignalData(durations=durations, rx90=params.rx90) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper_amp, - sweeper_freq, + results = platform.execute( + [sequence], + [[amp_sweeper], [freq_sweepers[q] for q in targets]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, ) for qubit in targets: - result = results[ro_pulses[qubit].serial] + result = results[ro_pulses[qubit].id] data.register_qubit( qubit=qubit, - freq=qd_pulses[qubit].frequency + frequency_range, - amp=qd_pulses[qubit].amplitude * amplitude_range, - signal=result.magnitude, - phase=result.phase, + freq=freq_sweepers[qubit].values, + amp=amp_sweeper.values, + signal=magnitude(result), + phase=phase(result), ) return data @@ -209,6 +204,7 @@ def _fit(data: RabiAmplitudeFreqSignalData) -> RabiAmplitudeFrequencySignalResul length=data.durations, fitted_parameters=fitted_parameters, frequency=fitted_frequencies, + rx90=data.rx90, ) @@ -283,10 +279,12 @@ def _plot( row=1, col=2, ) + pulse_name = "Pi-half pulse" if data.rx90 else "Pi pulse" + fitting_report = table_html( table_dict( target, - ["Optimal rabi frequency", "Pi-pulse amplitude"], + ["Optimal rabi frequency", f"{pulse_name} amplitude"], [ fit.frequency[target], f"{fit.amplitude[target]:.6f} [a.u]", @@ -302,10 +300,12 @@ def _plot( def _update( - results: RabiAmplitudeFrequencySignalResults, platform: Platform, target: QubitId + results: RabiAmplitudeFrequencySignalResults, + platform: CalibrationPlatform, + target: QubitId, ): - update.drive_duration(results.length[target], platform, target) - update.drive_amplitude(results.amplitude[target], platform, target) + update.drive_duration(results.length[target], results.rx90, platform, target) + update.drive_amplitude(results.amplitude[target], results.rx90, platform, target) update.drive_frequency(results.frequency[target], platform, target) diff --git a/src/qibocal/protocols/rabi/amplitude_signal.py b/src/qibocal/protocols/rabi/amplitude_signal.py index 31a8eb04a..587e0e19c 100644 --- a/src/qibocal/protocols/rabi/amplitude_signal.py +++ b/src/qibocal/protocols/rabi/amplitude_signal.py @@ -3,15 +3,14 @@ import numpy as np import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import fallback_period, guess_period +from qibocal.result import magnitude, phase from . import utils @@ -20,14 +19,16 @@ class RabiAmplitudeSignalParameters(Parameters): """RabiAmplitude runcard inputs.""" - min_amp_factor: float - """Minimum amplitude multiplicative factor.""" - max_amp_factor: float - """Maximum amplitude multiplicative factor.""" - step_amp_factor: float - """Step amplitude multiplicative factor.""" + min_amp: float + """Minimum amplitude.""" + max_amp: float + """Maximum amplitude.""" + step_amp: float + """Step amplitude.""" pulse_length: Optional[float] = None """RX pulse duration [ns].""" + rx90: bool = False + """Calibration of native pi pulse, if true calibrates pi/2 pulse""" @dataclass @@ -40,6 +41,8 @@ class RabiAmplitudeSignalResults(Results): """Drive pulse duration. Same for all qubits.""" fitted_parameters: dict[QubitId, dict[str, float]] """Raw fitted parameters.""" + rx90: bool + """Pi or Pi_half calibration""" RabiAmpSignalType = np.dtype( @@ -52,6 +55,8 @@ class RabiAmplitudeSignalResults(Results): class RabiAmplitudeSignalData(Data): """RabiAmplitudeSignal data acquisition.""" + rx90: bool + """Pi or Pi_half calibration""" durations: dict[QubitId, float] = field(default_factory=dict) """Pulse durations provided by the user.""" data: dict[QubitId, npt.NDArray[RabiAmpSignalType]] = field(default_factory=dict) @@ -59,7 +64,9 @@ class RabiAmplitudeSignalData(Data): def _acquisition( - params: RabiAmplitudeSignalParameters, platform: Platform, targets: list[QubitId] + params: RabiAmplitudeSignalParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> RabiAmplitudeSignalData: r""" Data acquisition for Rabi experiment sweeping amplitude. @@ -69,45 +76,35 @@ def _acquisition( # create a sequence of pulses for the experiment sequence, qd_pulses, ro_pulses, durations = utils.sequence_amplitude( - targets, params, platform + targets, params, platform, params.rx90 ) - # define the parameter to sweep and its range: - # qubit drive pulse amplitude - qd_pulse_amplitude_range = np.arange( - params.min_amp_factor, - params.max_amp_factor, - params.step_amp_factor, - ) sweeper = Sweeper( - Parameter.amplitude, - qd_pulse_amplitude_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.FACTOR, + parameter=Parameter.amplitude, + range=(params.min_amp, params.max_amp, params.step_amp), + pulses=[qd_pulses[qubit] for qubit in targets], ) - data = RabiAmplitudeSignalData(durations=durations) + data = RabiAmplitudeSignalData(durations=durations, rx90=params.rx90) # sweep the parameter - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, ) for qubit in targets: - result = results[ro_pulses[qubit].serial] + result = results[ro_pulses[qubit].id] data.register_qubit( RabiAmpSignalType, (qubit), dict( - amp=qd_pulses[qubit].amplitude * qd_pulse_amplitude_range, - signal=result.magnitude, - phase=result.phase, + amp=sweeper.values, + signal=magnitude(result), + phase=phase(result), ), ) return data @@ -151,7 +148,7 @@ def _fit(data: RabiAmplitudeSignalData) -> RabiAmplitudeSignalResults: log.warning(f"Rabi fit failed for qubit {qubit} due to {e}.") return RabiAmplitudeSignalResults( - pi_pulse_amplitudes, data.durations, fitted_parameters + pi_pulse_amplitudes, data.durations, fitted_parameters, data.rx90 ) @@ -161,12 +158,14 @@ def _plot( fit: RabiAmplitudeSignalResults = None, ): """Plotting function for RabiAmplitude.""" - return utils.plot(data, target, fit) + return utils.plot(data, target, fit, data.rx90) -def _update(results: RabiAmplitudeSignalResults, platform: Platform, target: QubitId): - update.drive_amplitude(results.amplitude[target], platform, target) - update.drive_duration(results.length[target], platform, target) +def _update( + results: RabiAmplitudeSignalResults, platform: CalibrationPlatform, target: QubitId +): + update.drive_amplitude(results.amplitude[target], results.rx90, platform, target) + update.drive_duration(results.length[target], results.rx90, platform, target) rabi_amplitude_signal = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/rabi/ef.py b/src/qibocal/protocols/rabi/ef.py index 5797daf7c..541a0f16a 100644 --- a/src/qibocal/protocols/rabi/ef.py +++ b/src/qibocal/protocols/rabi/ef.py @@ -1,15 +1,20 @@ from dataclasses import dataclass -import numpy as np -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal import update -from qibocal.auto.operation import Routine - +from qibolab import ( + AcquisitionType, + AveragingMode, + Delay, + Parameter, + PulseSequence, + Sweeper, +) + +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.update import replace + +from ... import update +from ...result import magnitude, phase from . import amplitude_signal, utils @@ -29,7 +34,9 @@ class RabiAmplitudeEFData(amplitude_signal.RabiAmplitudeSignalData): def _acquisition( - params: RabiAmplitudeEFParameters, platform: Platform, targets: list[QubitId] + params: RabiAmplitudeEFParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> RabiAmplitudeEFData: r""" Data acquisition for Rabi EF experiment sweeping amplitude. @@ -46,58 +53,59 @@ def _acquisition( ro_pulses = {} rx_pulses = {} durations = {} - for qubit in targets: - rx_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - qd_pulses[qubit] = platform.create_RX_pulse( - qubit, start=rx_pulses[qubit].finish - ) + for q in targets: + natives = platform.natives.single_qubit[q] + qd_channel, qd_pulse = natives.RX()[0] + qd12_channel, qd12_pulse = natives.RX12()[0] + ro_channel, ro_pulse = natives.MZ()[0] + if params.pulse_length is not None: - qd_pulses[qubit].duration = params.pulse_length + qd12_pulse = replace(qd_pulse, duration=params.pulse_length) + + durations[q] = qd12_pulse.duration + qd_pulses[q] = qd12_pulse + ro_pulses[q] = ro_pulse - durations[qubit] = qd_pulses[qubit].duration - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish + sequence.append((qd_channel, qd_pulse)) + sequence.append((qd12_channel, Delay(duration=qd_pulse.duration))) + sequence.append((qd12_channel, qd12_pulse)) + sequence.append( + (qd_channel, Delay(duration=qd_pulse.duration + qd12_pulse.duration)) ) - sequence.add(rx_pulses[qubit]) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - - # define the parameter to sweep and its range: - # qubit drive pulse amplitude - qd_pulse_amplitude_range = np.arange( - params.min_amp_factor, - params.max_amp_factor, - params.step_amp_factor, - ) + sequence.append((qd_channel, qd_pulse)) + sequence.append( + (ro_channel, Delay(duration=2 * qd_pulse.duration + qd12_pulse.duration)) + ) + sequence.append((ro_channel, ro_pulse)) + sweeper = Sweeper( - Parameter.amplitude, - qd_pulse_amplitude_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.FACTOR, + parameter=Parameter.amplitude, + range=(params.min_amp, params.max_amp, params.step_amp), + pulses=[qd_pulses[qubit] for qubit in targets], ) - data = RabiAmplitudeEFData(durations=durations) + assert not params.rx90, "Rabi ef available only for RX pulses." + + data = RabiAmplitudeEFData(durations=durations, rx90=False) # sweep the parameter - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, ) for qubit in targets: - result = results[ro_pulses[qubit].serial] + result = results[ro_pulses[qubit].id] data.register_qubit( amplitude_signal.RabiAmpSignalType, (qubit), dict( - amp=qd_pulses[qubit].amplitude * qd_pulse_amplitude_range, - signal=result.magnitude, - phase=result.phase, + amp=sweeper.values, + signal=magnitude(result), + phase=phase(result), ), ) return data @@ -107,13 +115,15 @@ def _plot( data: RabiAmplitudeEFData, target: QubitId, fit: RabiAmplitudeEFResults = None ): """Plotting function for RabiAmplitude.""" - figures, report = utils.plot(data, target, fit) + figures, report = utils.plot(data, target, fit, data.rx90) if report is not None: report = report.replace("Pi pulse", "Pi pulse 12") return figures, report -def _update(results: RabiAmplitudeEFResults, platform: Platform, target: QubitId): +def _update( + results: RabiAmplitudeEFResults, platform: CalibrationPlatform, target: QubitId +): """Update RX2 amplitude_signal""" update.drive_12_amplitude(results.amplitude[target], platform, target) update.drive_12_duration(results.length[target], platform, target) diff --git a/src/qibocal/protocols/rabi/length.py b/src/qibocal/protocols/rabi/length.py index 1b529322b..7f64770d6 100644 --- a/src/qibocal/protocols/rabi/length.py +++ b/src/qibocal/protocols/rabi/length.py @@ -3,18 +3,17 @@ import numpy as np import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper from qibocal import update -from qibocal.auto.operation import Parameters, Routine +from qibocal.auto.operation import Parameters, QubitId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.rabi.length_signal import ( RabiLengthSignalData, RabiLengthSignalResults, ) +from qibocal.result import probability from ..utils import chi2_reduced, fallback_period, guess_period from . import utils @@ -32,6 +31,10 @@ class RabiLengthParameters(Parameters): """Step pi pulse duration [ns].""" pulse_amplitude: Optional[float] = None """Pi pulse amplitude. Same for all qubits.""" + rx90: bool = False + """Calibration of native pi pulse, if true calibrates pi/2 pulse""" + interpolated_sweeper: bool = False + """Use real-time interpolation if supported by instruments.""" @dataclass @@ -56,7 +59,7 @@ class RabiLengthData(RabiLengthSignalData): def _acquisition( - params: RabiLengthParameters, platform: Platform, targets: list[QubitId] + params: RabiLengthParameters, platform: CalibrationPlatform, targets: list[QubitId] ) -> RabiLengthData: r""" Data acquisition for RabiLength Experiment. @@ -64,45 +67,46 @@ def _acquisition( to find the drive pulse length that creates a rotation of a desired angle. """ - sequence, qd_pulses, _, amplitudes = utils.sequence_length( - targets, params, platform + sequence, qd_pulses, delays, ro_pulses, amplitudes = utils.sequence_length( + targets, params, platform, params.rx90, use_align=params.interpolated_sweeper ) - # define the parameter to sweep and its range: - # qubit drive pulse duration time - qd_pulse_duration_range = np.arange( + sweep_range = ( params.pulse_duration_start, params.pulse_duration_end, params.pulse_duration_step, ) + if params.interpolated_sweeper: + sweeper = Sweeper( + parameter=Parameter.duration_interpolated, + range=sweep_range, + pulses=[qd_pulses[q] for q in targets], + ) + else: + sweeper = Sweeper( + parameter=Parameter.duration, + range=sweep_range, + pulses=[qd_pulses[q] for q in targets] + [delays[q] for q in targets], + ) - sweeper = Sweeper( - Parameter.duration, - qd_pulse_duration_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.ABSOLUTE, - ) - - data = RabiLengthData(amplitudes=amplitudes) + data = RabiLengthData(amplitudes=amplitudes, rx90=params.rx90) # execute the sweep - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ), - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, ) - for qubit in targets: - prob = results[qubit].probability(state=1) + for q in targets: + prob = probability(results[ro_pulses[q].id], state=1) data.register_qubit( RabiLenType, - (qubit), + (q), dict( - length=qd_pulse_duration_range, + length=sweeper.values, prob=prob, error=np.sqrt(prob * (1 - prob) / params.nshots).tolist(), ), @@ -153,17 +157,17 @@ def _fit(data: RabiLengthData) -> RabiLengthResults: except Exception as e: log.warning(f"Rabi fit failed for qubit {qubit} due to {e}.") - return RabiLengthResults(durations, amplitudes, fitted_parameters, chi2) + return RabiLengthResults(durations, amplitudes, fitted_parameters, data.rx90, chi2) -def _update(results: RabiLengthResults, platform: Platform, target: QubitId): - update.drive_duration(results.length[target], platform, target) - update.drive_amplitude(results.amplitude[target], platform, target) +def _update(results: RabiLengthResults, platform: CalibrationPlatform, target: QubitId): + update.drive_duration(results.length[target], results.rx90, platform, target) + update.drive_amplitude(results.amplitude[target], results.rx90, platform, target) def _plot(data: RabiLengthData, fit: RabiLengthResults, target: QubitId): """Plotting function for RabiLength experiment.""" - return utils.plot_probabilities(data, target, fit) + return utils.plot_probabilities(data, target, fit, data.rx90) rabi_length = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/rabi/length_frequency.py b/src/qibocal/protocols/rabi/length_frequency.py index 28ac4715c..5e2871bf0 100644 --- a/src/qibocal/protocols/rabi/length_frequency.py +++ b/src/qibocal/protocols/rabi/length_frequency.py @@ -6,15 +6,14 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import table_dict, table_html +from ...result import probability from ..utils import HZ_TO_GHZ, chi2_reduced, fallback_period, guess_period from .length_frequency_signal import ( RabiLengthFreqSignalData, @@ -68,60 +67,66 @@ def register_qubit(self, qubit, freq, lens, prob, error): def _acquisition( - params: RabiLengthFrequencyParameters, platform: Platform, targets: list[QubitId] + params: RabiLengthFrequencyParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> RabiLengthFreqData: """Data acquisition for Rabi experiment sweeping length.""" - sequence, qd_pulses, ro_pulses, amplitudes = sequence_length( - targets, params, platform + sequence, qd_pulses, delays, ro_pulses, amplitudes = sequence_length( + targets, params, platform, params.rx90 ) - # qubit drive pulse length - length_range = np.arange( + sweep_range = ( params.pulse_duration_start, params.pulse_duration_end, params.pulse_duration_step, ) - sweeper_len = Sweeper( - Parameter.duration, - length_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.ABSOLUTE, - ) + if params.interpolated_sweeper: + len_sweeper = Sweeper( + parameter=Parameter.duration_interpolated, + range=sweep_range, + pulses=[qd_pulses[q] for q in targets], + ) + else: + len_sweeper = Sweeper( + parameter=Parameter.duration, + range=sweep_range, + pulses=[qd_pulses[q] for q in targets] + [delays[q] for q in targets], + ) - # qubit drive pulse amplitude frequency_range = np.arange( params.min_freq, params.max_freq, params.step_freq, ) - sweeper_freq = Sweeper( - Parameter.frequency, - frequency_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) + freq_sweepers = {} + for qubit in targets: + channel = platform.qubits[qubit].drive + freq_sweepers[qubit] = Sweeper( + parameter=Parameter.frequency, + values=platform.config(channel).frequency + frequency_range, + channels=[channel], + ) - data = RabiLengthFreqData(amplitudes=amplitudes) + data = RabiLengthFreqData(amplitudes=amplitudes, rx90=params.rx90) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ), - sweeper_len, - sweeper_freq, + results = platform.execute( + [sequence], + [[len_sweeper], [freq_sweepers[q] for q in targets]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, ) + for qubit in targets: - result = results[ro_pulses[qubit].serial] - prob = result.probability(state=1) + result = results[ro_pulses[qubit].id] + prob = probability(result, state=1) data.register_qubit( qubit=qubit, - freq=qd_pulses[qubit].frequency + frequency_range, - lens=length_range, + freq=freq_sweepers[qubit].values, + lens=len_sweeper.values, prob=prob.tolist(), error=np.sqrt(prob * (1 - prob) / params.nshots).tolist(), ) @@ -192,6 +197,7 @@ def _fit(data: RabiLengthFreqData) -> RabiLengthFrequencyResults: fitted_parameters=fitted_parameters, frequency=fitted_frequencies, chi2=chi2, + rx90=data.rx90, ) @@ -240,10 +246,12 @@ def _plot( row=1, col=1, ) + pulse_name = "Pi-half pulse" if data.rx90 else "Pi pulse" + fitting_report = table_html( table_dict( target, - ["Optimal rabi frequency", "Pi-pulse duration"], + ["Optimal rabi frequency", f"{pulse_name} duration"], [ fit.frequency[target], f"{fit.length[target][0]:.2f} +- {fit.length[target][1]:.2f} ns", diff --git a/src/qibocal/protocols/rabi/length_frequency_signal.py b/src/qibocal/protocols/rabi/length_frequency_signal.py index abf73caa3..00fe5b80b 100644 --- a/src/qibocal/protocols/rabi/length_frequency_signal.py +++ b/src/qibocal/protocols/rabi/length_frequency_signal.py @@ -7,16 +7,15 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper from qibocal import update -from qibocal.auto.operation import Data, Parameters, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import table_dict, table_html +from ...result import magnitude, phase from ..utils import HZ_TO_GHZ, fallback_period, guess_period from .length_signal import RabiLengthSignalResults from .utils import fit_length_function, sequence_length @@ -40,12 +39,18 @@ class RabiLengthFrequencySignalParameters(Parameters): """Frequency to use as step for the scan.""" pulse_amplitude: Optional[float] = None """Pi pulse amplitude. Same for all qubits.""" + rx90: bool = False + """Calibration of native pi pulse, if true calibrates pi/2 pulse""" + interpolated_sweeper: bool = False + """Use real-time interpolation if supported by instruments.""" @dataclass class RabiLengthFrequencySignalResults(RabiLengthSignalResults): """RabiLengthFrequency outputs.""" + rx90: bool + """Pi or Pi_half calibration""" frequency: dict[QubitId, Union[float, list[float]]] """Drive frequency for each qubit.""" @@ -65,6 +70,8 @@ class RabiLengthFrequencySignalResults(RabiLengthSignalResults): class RabiLengthFreqSignalData(Data): """RabiLengthFreqSignal data acquisition.""" + rx90: bool + """Pi or Pi_half calibration""" amplitudes: dict[QubitId, float] = field(default_factory=dict) """Pulse amplitudes provided by the user.""" data: dict[QubitId, npt.NDArray[RabiLenFreqSignalType]] = field( @@ -94,62 +101,65 @@ def frequencies(self, qubit): def _acquisition( params: RabiLengthFrequencySignalParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> RabiLengthFreqSignalData: """Data acquisition for Rabi experiment sweeping length.""" - sequence, qd_pulses, ro_pulses, amplitudes = sequence_length( - targets, params, platform + sequence, qd_pulses, delays, ro_pulses, amplitudes = sequence_length( + targets, params, platform, params.rx90 ) - # qubit drive pulse length - length_range = np.arange( + sweep_range = ( params.pulse_duration_start, params.pulse_duration_end, params.pulse_duration_step, ) - sweeper_len = Sweeper( - Parameter.duration, - length_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.ABSOLUTE, - ) + if params.interpolated_sweeper: + len_sweeper = Sweeper( + parameter=Parameter.duration_interpolated, + range=sweep_range, + pulses=[qd_pulses[q] for q in targets], + ) + else: + len_sweeper = Sweeper( + parameter=Parameter.duration, + range=sweep_range, + pulses=[qd_pulses[q] for q in targets] + [delays[q] for q in targets], + ) - # qubit drive pulse amplitude frequency_range = np.arange( params.min_freq, params.max_freq, params.step_freq, ) - sweeper_freq = Sweeper( - Parameter.frequency, - frequency_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) + freq_sweepers = {} + for qubit in targets: + channel = platform.qubits[qubit].drive + freq_sweepers[qubit] = Sweeper( + parameter=Parameter.frequency, + values=platform.config(channel).frequency + frequency_range, + channels=[channel], + ) - data = RabiLengthFreqSignalData(amplitudes=amplitudes) + data = RabiLengthFreqSignalData(amplitudes=amplitudes, rx90=params.rx90) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper_len, - sweeper_freq, + results = platform.execute( + [sequence], + [[len_sweeper], [freq_sweepers[q] for q in targets]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, ) for qubit in targets: - result = results[ro_pulses[qubit].serial] + result = results[ro_pulses[qubit].id] data.register_qubit( qubit=qubit, - freq=qd_pulses[qubit].frequency + frequency_range, - lens=length_range, - signal=result.magnitude, - phase=result.phase, + freq=freq_sweepers[qubit].values, + lens=len_sweeper.values, + signal=magnitude(result), + phase=phase(result), ) return data @@ -203,6 +213,7 @@ def _fit(data: RabiLengthFreqSignalData) -> RabiLengthFrequencySignalResults: amplitude=data.amplitudes, fitted_parameters=fitted_parameters, frequency=fitted_frequencies, + rx90=data.rx90, ) @@ -277,10 +288,12 @@ def _plot( row=1, col=2, ) + pulse_name = "Pi-half pulse" if data.rx90 else "Pi pulse" + fitting_report = table_html( table_dict( target, - ["Optimal rabi frequency", "Pi-pulse duration"], + ["Optimal rabi frequency", f"{pulse_name} duration"], [ fit.frequency[target], f"{fit.length[target]:.2f} ns", @@ -297,10 +310,12 @@ def _plot( def _update( - results: RabiLengthFrequencySignalResults, platform: Platform, target: QubitId + results: RabiLengthFrequencySignalResults, + platform: CalibrationPlatform, + target: QubitId, ): - update.drive_amplitude(results.amplitude[target], platform, target) - update.drive_duration(results.length[target], platform, target) + update.drive_amplitude(results.amplitude[target], results.rx90, platform, target) + update.drive_duration(results.length[target], results.rx90, platform, target) update.drive_frequency(results.frequency[target], platform, target) diff --git a/src/qibocal/protocols/rabi/length_sequences.py b/src/qibocal/protocols/rabi/length_sequences.py deleted file mode 100644 index 3b6259d20..000000000 --- a/src/qibocal/protocols/rabi/length_sequences.py +++ /dev/null @@ -1,75 +0,0 @@ -import numpy as np -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId - -from qibocal.auto.operation import Routine - -from .length_signal import ( - RabiLengthSignalData, - RabiLengthSignalParameters, - RabiLenSignalType, - _fit, - _plot, - _update, -) -from .utils import sequence_length - - -def _acquisition( - params: RabiLengthSignalParameters, platform: Platform, targets: list[QubitId] -) -> RabiLengthSignalData: - r""" - Data acquisition for RabiLength Experiment. - In the Rabi experiment we apply a pulse at the frequency of the qubit and scan the drive pulse length - to find the drive pulse length that creates a rotation of a desired angle. - """ - - sequence, qd_pulses, ro_pulses, amplitudes = sequence_length( - targets, params, platform - ) - - # define the parameter to sweep and its range: - # qubit drive pulse duration time - qd_pulse_duration_range = np.arange( - params.pulse_duration_start, - params.pulse_duration_end, - params.pulse_duration_step, - ) - - data = RabiLengthSignalData(amplitudes=amplitudes) - - # sweep the parameter - for duration in qd_pulse_duration_range: - for qubit in targets: - qd_pulses[qubit].duration = duration - ro_pulses[qubit].start = qd_pulses[qubit].finish - - # execute the pulse sequence - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - ) - - for qubit in targets: - result = results[ro_pulses[qubit].serial] - data.register_qubit( - RabiLenSignalType, - (qubit), - dict( - length=np.array([duration]), - signal=np.array([result.magnitude]), - phase=np.array([result.phase]), - ), - ) - - return data - - -rabi_length_sequences = Routine(_acquisition, _fit, _plot, _update) -"""RabiLength Routine object.""" diff --git a/src/qibocal/protocols/rabi/length_signal.py b/src/qibocal/protocols/rabi/length_signal.py index fc139197d..3e7db1afa 100644 --- a/src/qibocal/protocols/rabi/length_signal.py +++ b/src/qibocal/protocols/rabi/length_signal.py @@ -3,15 +3,14 @@ import numpy as np import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import fallback_period, guess_period +from qibocal.result import magnitude, phase from . import utils @@ -28,6 +27,10 @@ class RabiLengthSignalParameters(Parameters): """Step pi pulse duration [ns].""" pulse_amplitude: Optional[float] = None """Pi pulse amplitude. Same for all qubits.""" + rx90: bool = False + """Calibration of native pi pulse, if true calibrates pi/2 pulse""" + interpolated_sweeper: bool = False + """Use real-time interpolation if supported by instruments.""" @dataclass @@ -40,6 +43,8 @@ class RabiLengthSignalResults(Results): """Pi pulse amplitude. Same for all qubits.""" fitted_parameters: dict[QubitId, dict[str, float]] """Raw fitting output.""" + rx90: bool + """Pi or Pi_half calibration""" RabiLenSignalType = np.dtype( @@ -52,6 +57,8 @@ class RabiLengthSignalResults(Results): class RabiLengthSignalData(Data): """RabiLength acquisition outputs.""" + rx90: bool + """Pi or Pi_half calibration""" amplitudes: dict[QubitId, float] = field(default_factory=dict) """Pulse durations provided by the user.""" data: dict[QubitId, npt.NDArray[RabiLenSignalType]] = field(default_factory=dict) @@ -59,7 +66,9 @@ class RabiLengthSignalData(Data): def _acquisition( - params: RabiLengthSignalParameters, platform: Platform, targets: list[QubitId] + params: RabiLengthSignalParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> RabiLengthSignalData: r""" Data acquisition for RabiLength Experiment. @@ -67,47 +76,47 @@ def _acquisition( to find the drive pulse length that creates a rotation of a desired angle. """ - sequence, qd_pulses, ro_pulses, amplitudes = utils.sequence_length( - targets, params, platform + sequence, qd_pulses, delays, ro_pulses, amplitudes = utils.sequence_length( + targets, params, platform, params.rx90, use_align=params.interpolated_sweeper ) - - # define the parameter to sweep and its range: - # qubit drive pulse duration time - qd_pulse_duration_range = np.arange( + sweep_range = ( params.pulse_duration_start, params.pulse_duration_end, params.pulse_duration_step, ) + if params.interpolated_sweeper: + sweeper = Sweeper( + parameter=Parameter.duration_interpolated, + range=sweep_range, + pulses=[qd_pulses[q] for q in targets], + ) + else: + sweeper = Sweeper( + parameter=Parameter.duration, + range=sweep_range, + pulses=[qd_pulses[q] for q in targets] + [delays[q] for q in targets], + ) - sweeper = Sweeper( - Parameter.duration, - qd_pulse_duration_range, - [qd_pulses[qubit] for qubit in targets], - type=SweeperType.ABSOLUTE, - ) - data = RabiLengthSignalData(amplitudes=amplitudes) - - # execute the sweep - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper, + data = RabiLengthSignalData(amplitudes=amplitudes, rx90=params.rx90) + + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, ) - for qubit in targets: - result = results[ro_pulses[qubit].serial] + for q in targets: + result = results[ro_pulses[q].id] data.register_qubit( RabiLenSignalType, - (qubit), + (q), dict( - length=qd_pulse_duration_range, - signal=result.magnitude, - phase=result.phase, + length=sweeper.values, + signal=magnitude(result), + phase=phase(result), ), ) return data @@ -149,17 +158,21 @@ def _fit(data: RabiLengthSignalData) -> RabiLengthSignalResults: except Exception as e: log.warning(f"Rabi fit failed for qubit {qubit} due to {e}.") - return RabiLengthSignalResults(durations, data.amplitudes, fitted_parameters) + return RabiLengthSignalResults( + durations, data.amplitudes, fitted_parameters, data.rx90 + ) -def _update(results: RabiLengthSignalResults, platform: Platform, target: QubitId): - update.drive_duration(results.length[target], platform, target) - update.drive_amplitude(results.amplitude[target], platform, target) +def _update( + results: RabiLengthSignalResults, platform: CalibrationPlatform, target: QubitId +): + update.drive_duration(results.length[target], results.rx90, platform, target) + update.drive_amplitude(results.amplitude[target], results.rx90, platform, target) def _plot(data: RabiLengthSignalData, fit: RabiLengthSignalResults, target: QubitId): """Plotting function for RabiLength experiment.""" - return utils.plot(data, target, fit) + return utils.plot(data, target, fit, data.rx90) rabi_length_signal = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/rabi/utils.py b/src/qibocal/protocols/rabi/utils.py index d31a40679..dc609e8c1 100644 --- a/src/qibocal/protocols/rabi/utils.py +++ b/src/qibocal/protocols/rabi/utils.py @@ -1,12 +1,11 @@ import numpy as np import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import Delay, Platform, PulseSequence from scipy.optimize import curve_fit -from qibocal.auto.operation import Parameters +from qibocal.auto.operation import Parameters, QubitId +from qibocal.update import replace from ..utils import COLORBAND, COLORBAND_LINE, table_dict, table_html @@ -33,7 +32,7 @@ def rabi_length_function(x, offset, amplitude, period, phase, t2_inv): ) -def plot(data, qubit, fit): +def plot(data, qubit, fit, rx90): quantity, title, fitting = extract_rabi(data) figures = [] fitting_report = "" @@ -95,11 +94,12 @@ def plot(data, qubit, fit): row=1, col=1, ) + pulse_name = "Pi-half pulse" if rx90 else "Pi pulse" fitting_report = table_html( table_dict( qubit, - ["Pi pulse amplitude [a.u.]", "Pi pulse length [ns]"], + [f"{pulse_name} amplitude [a.u.]", f"{pulse_name} length [ns]"], [np.round(fit.amplitude[qubit], 3), np.round(fit.length[qubit], 3)], ) ) @@ -117,7 +117,7 @@ def plot(data, qubit, fit): return figures, fitting_report -def plot_probabilities(data, qubit, fit): +def plot_probabilities(data, qubit, fit, rx90): quantity, title, fitting = extract_rabi(data) figures = [] fitting_report = "" @@ -166,11 +166,16 @@ def plot_probabilities(data, qubit, fit): marker_color="rgb(255, 130, 67)", ), ) + pulse_name = "Pi-half pulse" if rx90 else "Pi pulse" fitting_report = table_html( table_dict( qubit, - ["Pi pulse amplitude [a.u.]", "Pi pulse length [ns]", "chi2 reduced"], + [ + f"{pulse_name} amplitude [a.u.]", + f"{pulse_name} length [ns]", + "chi2 reduced", + ], [fit.amplitude[qubit], fit.length[qubit], fit.chi2[qubit]], display_error=True, ) @@ -224,49 +229,78 @@ def period_correction_factor(phase: float): def sequence_amplitude( - targets: list[QubitId], params: Parameters, platform: Platform + targets: list[QubitId], + params: Parameters, + platform: Platform, + rx90: bool, ) -> tuple[PulseSequence, dict, dict, dict]: """Return sequence for rabi amplitude.""" + sequence = PulseSequence() qd_pulses = {} ro_pulses = {} durations = {} - for qubit in targets: - qd_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) + for q in targets: + natives = platform.natives.single_qubit[q] + + qd_channel, qd_pulse = natives.RX90()[0] if rx90 else natives.RX()[0] + ro_channel, ro_pulse = natives.MZ()[0] + if params.pulse_length is not None: - qd_pulses[qubit].duration = params.pulse_length + qd_pulse = replace(qd_pulse, duration=params.pulse_length) - durations[qubit] = qd_pulses[qubit].duration - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish - ) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) + durations[q] = qd_pulse.duration + qd_pulses[q] = qd_pulse + ro_pulses[q] = ro_pulse + + if rx90: + sequence.append((qd_channel, qd_pulses[q])) + + sequence.append((qd_channel, qd_pulses[q])) + sequence.append((ro_channel, Delay(duration=durations[q]))) + sequence.append((ro_channel, ro_pulse)) return sequence, qd_pulses, ro_pulses, durations def sequence_length( - targets: list[QubitId], params: Parameters, platform: Platform + targets: list[QubitId], + params: Parameters, + platform: Platform, + rx90: bool, + use_align: bool = False, ) -> tuple[PulseSequence, dict, dict, dict]: """Return sequence for rabi length.""" + sequence = PulseSequence() qd_pulses = {} + delays = {} ro_pulses = {} amplitudes = {} - for qubit in targets: - qd_pulses[qubit] = platform.create_qubit_drive_pulse( - qubit, start=0, duration=params.pulse_duration_start - ) + for q in targets: + natives = platform.natives.single_qubit[q] + + qd_channel, qd_pulse = natives.RX90()[0] if rx90 else natives.RX()[0] + ro_channel, ro_pulse = natives.MZ()[0] + if params.pulse_amplitude is not None: - qd_pulses[qubit].amplitude = params.pulse_amplitude - amplitudes[qubit] = qd_pulses[qubit].amplitude + qd_pulse = replace(qd_pulse, amplitude=params.pulse_amplitude) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish - ) - sequence.add(qd_pulses[qubit]) - sequence.add(ro_pulses[qubit]) - return sequence, qd_pulses, ro_pulses, amplitudes + amplitudes[q] = qd_pulse.amplitude + ro_pulses[q] = ro_pulse + qd_pulses[q] = qd_pulse + + if rx90: + sequence.append((qd_channel, qd_pulse)) + + sequence.append((qd_channel, qd_pulse)) + if use_align: + sequence.align([qd_channel, ro_channel]) + else: + delays[q] = Delay(duration=16) + sequence.append((ro_channel, delays[q])) + sequence.append((ro_channel, ro_pulse)) + + return sequence, qd_pulses, delays, ro_pulses, amplitudes def fit_length_function( @@ -328,13 +362,12 @@ def fit_amplitude_function( ) if signal is False: perr = np.sqrt(np.diag(perr)) - else: - popt = [ # Change it according to fit function changes + if None not in y_limits and None not in x_limits: + popt = [ y_limits[0] + (y_limits[1] - y_limits[0]) * popt[0], (y_limits[1] - y_limits[0]) * popt[1], popt[2] * (x_limits[1] - x_limits[0]), popt[3] - 2 * np.pi * x_limits[0] / (x_limits[1] - x_limits[0]) / popt[2], ] pi_pulse_parameter = popt[2] / 2 * period_correction_factor(phase=popt[3]) - return popt, perr, pi_pulse_parameter diff --git a/src/qibocal/protocols/ramsey/ramsey.py b/src/qibocal/protocols/ramsey/ramsey.py index c74d42b56..0b9ca57bc 100644 --- a/src/qibocal/protocols/ramsey/ramsey.py +++ b/src/qibocal/protocols/ramsey/ramsey.py @@ -4,14 +4,12 @@ import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Readout, Sweeper -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log +from qibocal.result import probability from ..utils import chi2_reduced, table_dict, table_html from .ramsey_signal import ( @@ -55,7 +53,7 @@ class RamseyData(RamseySignalData): def _acquisition( params: RamseyParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> RamseyData: """Data acquisition for Ramsey Experiment (detuned). @@ -78,50 +76,47 @@ def _acquisition( """ waits = np.arange( - # wait time between RX90 pulses params.delay_between_pulses_start, params.delay_between_pulses_end, params.delay_between_pulses_step, ) - options = ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ) - - sequence = PulseSequence() - data = RamseyData( detuning=params.detuning, qubit_freqs={ - qubit: platform.qubits[qubit].native_gates.RX.frequency for qubit in targets + qubit: platform.config(platform.qubits[qubit].drive).frequency + for qubit in targets }, ) - if not params.unrolling: - sequence = PulseSequence() + updates = [] + if params.detuning is not None: for qubit in targets: - sequence += ramsey_sequence( - platform=platform, qubit=qubit, detuning=params.detuning - ) + channel = platform.qubits[qubit].drive + f0 = platform.config(channel).frequency + updates.append({channel: {"frequency": f0 + params.detuning}}) + if not params.unrolling: + sequence, delays = ramsey_sequence(platform, targets) sweeper = Sweeper( - Parameter.start, - waits, - [sequence.get_qubit_pulses(qubit).qd_pulses[-1] for qubit in targets], - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + values=waits, + pulses=delays, ) # execute the sweep - results = platform.sweep( - sequence, - options, - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, + updates=updates, ) for qubit in targets: - probs = results[qubit].probability(state=1) + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[-1] + probs = probability(results[ro_pulse.id], state=1) # The probability errors are the standard errors of the binomial distribution errors = [np.sqrt(prob * (1 - prob) / params.nshots) for prob in probs] data.register_qubit( @@ -133,30 +128,37 @@ def _acquisition( errors=errors, ), ) - - if params.unrolling: + else: sequences, all_ro_pulses = [], [] for wait in waits: - sequence = PulseSequence() - for qubit in targets: - sequence += ramsey_sequence( - platform=platform, qubit=qubit, wait=wait, detuning=params.detuning - ) - + sequence, _ = ramsey_sequence(platform, targets, wait) sequences.append(sequence) - all_ro_pulses.append(sequence.ro_pulses) + all_ro_pulses.append( + { + qubit: [ + pulse + for pulse in list( + sequence.channel(platform.qubits[qubit].acquisition) + ) + if isinstance(pulse, Readout) + ][0] + for qubit in targets + } + ) - results = platform.execute_pulse_sequences(sequences, options) + results = platform.execute( + sequences, + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, + updates=updates, + ) - # We dont need ig as every serial is different - for ig, (wait, ro_pulses) in enumerate(zip(waits, all_ro_pulses)): + for wait, ro_pulses in zip(waits, all_ro_pulses): for qubit in targets: - serial = ro_pulses[qubit].serial - if params.unrolling: - result = results[serial][0] - else: - result = results[ig][serial] - prob = result.probability() + result = results[ro_pulses[qubit].id] + prob = probability(result, state=1) error = np.sqrt(prob * (1 - prob) / params.nshots) data.register_qubit( RamseyType, diff --git a/src/qibocal/protocols/ramsey/ramsey_signal.py b/src/qibocal/protocols/ramsey/ramsey_signal.py index 07bb695c4..58dd26ba3 100644 --- a/src/qibocal/protocols/ramsey/ramsey_signal.py +++ b/src/qibocal/protocols/ramsey/ramsey_signal.py @@ -4,16 +4,14 @@ import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibolab import AcquisitionType, AveragingMode, Parameter, Readout, Sweeper + +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log +from qibocal.result import magnitude +from ... import update from ..utils import table_dict, table_html from .utils import fitting, process_fit, ramsey_fit, ramsey_sequence @@ -81,7 +79,7 @@ def waits(self): def _acquisition( params: RamseySignalParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> RamseySignalData: """Data acquisition for Ramsey Experiment (detuned).""" @@ -96,81 +94,88 @@ def _acquisition( params.delay_between_pulses_step, ) - options = ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ) - data = RamseySignalData( detuning=params.detuning, qubit_freqs={ - qubit: platform.qubits[qubit].native_gates.RX.frequency for qubit in targets + qubit: platform.config(platform.qubits[qubit].drive).frequency + for qubit in targets }, ) - if not params.unrolling: - sequence = PulseSequence() + updates = [] + if params.detuning is not None: for qubit in targets: - sequence += ramsey_sequence( - platform=platform, qubit=qubit, detuning=params.detuning - ) + channel = platform.qubits[qubit].drive + f0 = platform.config(channel).frequency + updates.append({channel: {"frequency": f0 + params.detuning}}) + + if not params.unrolling: + sequence, delays = ramsey_sequence(platform, targets) sweeper = Sweeper( - Parameter.start, - waits, - [ - sequence.get_qubit_pulses(qubit).qd_pulses[-1] for qubit in targets - ], # TODO: check if it is correct - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + values=waits, + pulses=delays, ) # execute the sweep - results = platform.sweep( - sequence, - options, - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, + updates=updates, ) for qubit in targets: - result = results[sequence.get_qubit_pulses(qubit).ro_pulses[0].serial] + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[-1] + result = results[ro_pulse.id] # The probability errors are the standard errors of the binomial distribution data.register_qubit( RamseySignalType, (qubit), dict( wait=waits, - signal=result.magnitude, + signal=magnitude(result), ), ) else: sequences, all_ro_pulses = [], [] for wait in waits: - sequence = PulseSequence() - for qubit in targets: - sequence += ramsey_sequence( - platform=platform, qubit=qubit, wait=wait, detuning=params.detuning - ) - + sequence, _ = ramsey_sequence(platform, targets, wait) sequences.append(sequence) - all_ro_pulses.append(sequence.ro_pulses) + all_ro_pulses.append( + { + qubit: [ + pulse + for pulse in list( + sequence.channel(platform.qubits[qubit].acquisition) + ) + if isinstance(pulse, Readout) + ][0] + for qubit in targets + } + ) - results = platform.execute_pulse_sequences(sequences, options) + results = platform.execute( + sequences, + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, + updates=updates, + ) - # We dont need ig as everty serial is different - for ig, (wait, ro_pulses) in enumerate(zip(waits, all_ro_pulses)): + for wait, ro_pulses in zip(waits, all_ro_pulses): for qubit in targets: - serial = ro_pulses[qubit].serial - if params.unrolling: - result = results[serial][0] - else: - result = results[ig][serial] + result = results[ro_pulses[qubit].id] data.register_qubit( RamseySignalType, (qubit), dict( wait=np.array([wait]), - signal=np.array([result.magnitude]), + signal=np.array([magnitude(result)]), ), ) @@ -285,11 +290,13 @@ def _plot(data: RamseySignalData, target: QubitId, fit: RamseySignalResults = No return figures, fitting_report -def _update(results: RamseySignalResults, platform: Platform, target: QubitId): +def _update( + results: RamseySignalResults, platform: CalibrationPlatform, target: QubitId +): if results.detuning is not None: update.drive_frequency(results.frequency[target][0], platform, target) else: - update.t2(results.t2[target][0], platform, target) + update.t2(results.t2[target], platform, target) ramsey_signal = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/ramsey/ramsey_zz.py b/src/qibocal/protocols/ramsey/ramsey_zz.py index 90ebe871d..021951e26 100644 --- a/src/qibocal/protocols/ramsey/ramsey_zz.py +++ b/src/qibocal/protocols/ramsey/ramsey_zz.py @@ -4,14 +4,13 @@ import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Readout, Sweeper -from ...auto.operation import Routine +from qibocal.calibration import CalibrationPlatform + +from ...auto.operation import QubitId, Routine from ...config import log +from ...result import probability from ..utils import table_dict, table_html from .ramsey import ( COLORBAND, @@ -60,7 +59,7 @@ class RamseyZZData(RamseySignalData): def _acquisition( params: RamseyZZParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> RamseyZZData: """Data acquisition for RamseyZZ Experiment. @@ -75,72 +74,91 @@ def _acquisition( params.delay_between_pulses_step, ) - options = ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.SINGLESHOT, - ) - data = RamseyZZData( detuning=params.detuning, qubit_freqs={ - qubit: platform.qubits[qubit].native_gates.RX.frequency for qubit in targets + qubit: platform.config(platform.qubits[qubit].drive).frequency + for qubit in targets }, target_qubit=params.target_qubit, ) + updates = [] + if params.detuning is not None: + for qubit in targets: + channel = platform.qubits[qubit].drive + f0 = platform.config(channel).frequency + updates.append({channel: {"frequency": f0 + params.detuning}}) + for setup in ["I", "X"]: if not params.unrolling: - sequence = PulseSequence() - for qubit in targets: - sequence += ramsey_sequence( - platform=platform, - qubit=qubit, - detuning=params.detuning, - target_qubit=params.target_qubit if setup == "X" else None, - ) + sequence, delays = ramsey_sequence( + platform=platform, + targets=targets, + target_qubit=params.target_qubit if setup == "X" else None, + ) sweeper = Sweeper( - Parameter.start, - waits, - [sequence.get_qubit_pulses(qubit).qd_pulses[-1] for qubit in targets], - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + values=waits, + pulses=delays, ) # execute the sweep - results = platform.sweep( - sequence, - options, - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, + updates=updates, ) for qubit in targets: - probs = results[qubit].probability(state=1) + ro_pulse = list(sequence.channel(platform.qubits[qubit].acquisition))[ + -1 + ] + probs = probability(results[ro_pulse.id], state=1) errors = [np.sqrt(prob * (1 - prob) / params.nshots) for prob in probs] else: sequences, all_ro_pulses = [], [] probs, errors = [], [] for wait in waits: - sequence = PulseSequence() - for qubit in targets: - sequence += ramsey_sequence( - platform=platform, - qubit=qubit, - wait=wait, - detuning=params.detuning, - target_qubit=params.target_qubit if setup == "X" else None, - ) - + sequence, _ = ramsey_sequence( + platform=platform, + targets=targets, + wait=wait, + target_qubit=params.target_qubit if setup == "X" else None, + ) sequences.append(sequence) - all_ro_pulses.append(sequence.ro_pulses) + all_ro_pulses.append( + { + qubit: [ + readout + for readout in sequence.channel( + platform.qubits[qubit].acquisition + ) + if isinstance(readout, Readout) + ][0] + for qubit in targets + } + ) - results = platform.execute_pulse_sequences(sequences, options) + results = platform.execute( + sequences, + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.SINGLESHOT, + updates=updates, + ) for wait, ro_pulses in zip(waits, all_ro_pulses): for qubit in targets: - prob = results[ro_pulses[qubit].serial][0].probability(state=1) + result = results[ro_pulses[qubit].id] + prob = probability(result, state=1) probs.append(prob) errors.append(np.sqrt(prob * (1 - prob) / params.nshots)) diff --git a/src/qibocal/protocols/ramsey/utils.py b/src/qibocal/protocols/ramsey/utils.py index f24eff751..0acc78b20 100644 --- a/src/qibocal/protocols/ramsey/utils.py +++ b/src/qibocal/protocols/ramsey/utils.py @@ -1,11 +1,10 @@ from typing import Optional import numpy as np -from qibolab import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import Delay, Platform, PulseSequence from scipy.optimize import curve_fit +from qibocal.auto.operation import QubitId from qibocal.protocols.utils import GHZ_TO_HZ, fallback_period, guess_period POPT_EXCEPTION = [0, 0, 0, 0, 1] @@ -20,9 +19,8 @@ def ramsey_sequence( platform: Platform, - qubit: QubitId, + targets: list[QubitId], wait: int = 0, - detuning: Optional[int] = 0, target_qubit: Optional[QubitId] = None, ): """Pulse sequence used in Ramsey (detuned) experiments. @@ -30,30 +28,38 @@ def ramsey_sequence( The pulse sequence is the following: RX90 -- wait -- RX90 -- MZ - - If detuning is specified the RX90 pulses will be sent to - frequency = drive_frequency + detuning """ - + delays = [] sequence = PulseSequence() - first_pi_half_pulse = platform.create_RX90_pulse(qubit, start=0) - second_pi_half_pulse = platform.create_RX90_pulse( - qubit, start=first_pi_half_pulse.finish + wait - ) - - # apply detuning: - if detuning is not None: - first_pi_half_pulse.frequency += detuning - second_pi_half_pulse.frequency += detuning - readout_pulse = platform.create_qubit_readout_pulse( - qubit, start=second_pi_half_pulse.finish - ) - - sequence.add(first_pi_half_pulse, second_pi_half_pulse, readout_pulse) - if target_qubit is not None: - x_pulse_target_qubit = platform.create_RX_pulse(target_qubit, start=0) - sequence.add(x_pulse_target_qubit) - return sequence + for qubit in targets: + natives = platform.natives.single_qubit[qubit] + + qd_channel, qd_pulse = natives.R(theta=np.pi / 2)[0] + ro_channel, ro_pulse = natives.MZ()[0] + + qd_delay = Delay(duration=wait) + ro_delay = Delay(duration=wait) + + sequence.extend( + [ + (qd_channel, qd_pulse), + (qd_channel, qd_delay), + (qd_channel, qd_pulse), + (ro_channel, Delay(duration=2 * qd_pulse.duration)), + (ro_channel, ro_delay), + (ro_channel, ro_pulse), + ] + ) + + delays.extend([qd_delay, ro_delay]) + if target_qubit is not None: + assert ( + target_qubit not in targets + ), f"Cannot run Ramsey experiment on qubit {target_qubit} if it is already in Ramsey sequence." + natives = platform.natives.single_qubit[target_qubit] + sequence += natives.RX() + + return sequence, delays def ramsey_fit(x, offset, amplitude, delta, phase, decay): diff --git a/src/qibocal/protocols/randomized_benchmarking/filtered_rb.py b/src/qibocal/protocols/randomized_benchmarking/filtered_rb.py index 6c949bb73..4bc1b35b2 100644 --- a/src/qibocal/protocols/randomized_benchmarking/filtered_rb.py +++ b/src/qibocal/protocols/randomized_benchmarking/filtered_rb.py @@ -2,10 +2,9 @@ import numpy as np import plotly.graph_objects as go -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibocal.auto.operation import Results, Routine +from qibocal.auto.operation import QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.protocols.randomized_benchmarking.utils import rb_acquisition from qibocal.protocols.utils import table_dict, table_html @@ -24,7 +23,7 @@ class FilteredRBResult(Results): def _acquisition( params: FilteredRBParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> RBData: """The data acquisition stage of Filtered Randomized Benchmarking. @@ -35,7 +34,7 @@ def _acquisition( Args: params : All parameters in one object. - platform : Platform the experiment is executed on. + platform : CalibrationPlatform the experiment is executed on. target : list of qubits the experiment is executed on. Returns: @@ -123,4 +122,6 @@ def _plot( return [fig], fitting_report +# TODO: add update function (?) + filtered_rb = Routine(_acquisition, _fit, _plot) diff --git a/src/qibocal/protocols/randomized_benchmarking/standard_rb.py b/src/qibocal/protocols/randomized_benchmarking/standard_rb.py index c001b07a5..37833bd0a 100644 --- a/src/qibocal/protocols/randomized_benchmarking/standard_rb.py +++ b/src/qibocal/protocols/randomized_benchmarking/standard_rb.py @@ -3,10 +3,9 @@ import numpy as np import plotly.graph_objects as go -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibocal.auto.operation import Parameters, Results, Routine +from qibocal.auto.operation import Parameters, QubitId, Routine +from qibocal.calibration import CalibrationPlatform from ..utils import table_dict, table_html from .fitting import exp1B_func, fit_exp1B_func @@ -143,7 +142,7 @@ def random_circuits( def _acquisition( params: StandardRBParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> RBData: """The data acquisition stage of Standard Randomized Benchmarking. @@ -154,7 +153,7 @@ def _acquisition( Args: params: All parameters in one object. - platform: Platform the experiment is executed on. + platform: CalibrationPlatform the experiment is executed on. target: list of qubits the experiment is executed on. Returns: @@ -226,7 +225,7 @@ def _plot( Returns: tuple[list[go.Figure], str]: """ - + target = tuple(target) if isinstance(target, list) else target qubit = target fig = go.Figure() fitting_report = "" @@ -331,4 +330,14 @@ def _plot( return [fig], fitting_report -standard_rb = Routine(_acquisition, _fit, _plot) +def _update(results: StandardRBResult, platform: CalibrationPlatform, target: QubitId): + """Write rb fidelity in calibration.""" + + # TODO: shall we use the gate fidelity or the pulse fidelity + platform.calibration.single_qubits[target].rb_fidelity = ( + results.fidelity[target], + results.fit_uncertainties[target][1] / 2, + ) + + +standard_rb = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/randomized_benchmarking/standard_rb_2q.py b/src/qibocal/protocols/randomized_benchmarking/standard_rb_2q.py index d76aa59ec..2160e53a1 100644 --- a/src/qibocal/protocols/randomized_benchmarking/standard_rb_2q.py +++ b/src/qibocal/protocols/randomized_benchmarking/standard_rb_2q.py @@ -1,14 +1,13 @@ from dataclasses import dataclass -from qibolab.platform import Platform -from qibolab.qubits import QubitPairId - -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitPairId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.protocols.randomized_benchmarking.standard_rb import ( StandardRBParameters, _plot, ) +from ...calibration.calibration import TwoQubitCalibration from .utils import RB2QData, StandardRBResult, fit, twoq_rb_acquisition FILE_CLIFFORDS = "2qubitCliffs.json" @@ -27,7 +26,7 @@ class StandardRB2QParameters(StandardRBParameters): def _acquisition( params: StandardRB2QParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitPairId], ) -> RB2QData: """Data acquisition for two qubit Standard Randomized Benchmarking.""" @@ -42,4 +41,21 @@ def _fit(data: RB2QData) -> StandardRBResult: return results -standard_rb_2q = Routine(_acquisition, _fit, _plot) +def _update( + results: StandardRBResult, platform: CalibrationPlatform, target: QubitPairId +): + """Write rb fidelity in calibration.""" + # FIXME: error raised by qq fit + if isinstance(target, list): + target = tuple(target) + + if target not in platform.calibration.two_qubits: + platform.calibration.two_qubits[target] = TwoQubitCalibration() + + platform.calibration.two_qubits[target].rb_fidelity = ( + results.fidelity[target], + results.fit_uncertainties[target][1] / 2, + ) + + +standard_rb_2q = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/randomized_benchmarking/standard_rb_2q_inter.py b/src/qibocal/protocols/randomized_benchmarking/standard_rb_2q_inter.py index c6a657e05..332e306f8 100644 --- a/src/qibocal/protocols/randomized_benchmarking/standard_rb_2q_inter.py +++ b/src/qibocal/protocols/randomized_benchmarking/standard_rb_2q_inter.py @@ -1,10 +1,9 @@ from dataclasses import dataclass, fields import numpy as np -from qibolab.platform import Platform -from qibolab.qubits import QubitPairId -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitPairId, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.protocols.randomized_benchmarking.standard_rb import _plot from qibocal.protocols.randomized_benchmarking.standard_rb_2q import ( StandardRB2QParameters, @@ -41,18 +40,18 @@ def __contains__(self, value: QubitPairId): def _acquisition( params: StandardRB2QInterParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitPairId], ) -> RB2QInterData: """Data acquisition for two qubit Interleaved Randomized Benchmarking.""" - data = twoq_rb_acquisition(params, platform, targets, interleave=params.interleave) - fidelity = {} for target in targets: - fidelity[target] = platform.pairs[target].gate_fidelity + assert ( + target in platform.calibration.two_qubits + ), "Pair not calibrated, run standard 2q rb before interleaved version" + fidelity[target] = platform.calibration.two_qubits[target].rb_fidelity data.fidelity = fidelity - return data @@ -69,19 +68,16 @@ def _fit(data: RB2QInterData) -> StandardRB2QInterResult: qubits = data.pairs results = fit(qubits, data) - fidelity_cz = {} for qubit in qubits: - if qubit in data.fidelity and data.fidelity[qubit] is not None: - fid_cz = results.fidelity[qubit] / data.fidelity[qubit][0] - uncertainty_cz = np.sqrt( - 1 - / data.fidelity[qubit][0] ** 2 - * results.fit_uncertainties[qubit][1] ** 2 - + (results.fidelity[qubit] / data.fidelity[qubit][0] ** 2) ** 2 - * data.fidelity[qubit][1] ** 2 - ) - fidelity_cz[qubit] = [fid_cz, uncertainty_cz] + fid_cz = results.fidelity[qubit] / data.fidelity[qubit][0] + # TODO: check this error formula + uncertainty_cz = np.sqrt( + 1 / data.fidelity[qubit][0] ** 2 * results.fit_uncertainties[qubit][1] ** 2 + + (results.fidelity[qubit] / data.fidelity[qubit][0] ** 2) ** 2 + * data.fidelity[qubit][1] ** 2 + ) + fidelity_cz[qubit] = [fid_cz, uncertainty_cz] return StandardRB2QInterResult( results.fidelity, @@ -93,4 +89,15 @@ def _fit(data: RB2QInterData) -> StandardRB2QInterResult: ) -standard_rb_2q_inter = Routine(_acquisition, _fit, _plot) +def _update( + results: StandardRBResult, platform: CalibrationPlatform, target: QubitPairId +): + """Write cz fidelity in calibration.""" + # TODO: shall we use the gate fidelity or the pulse fidelity + target = tuple(target) + platform.calibration.two_qubits[target].cz_fidelity = tuple( + results.fidelity_cz[target] + ) + + +standard_rb_2q_inter = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/randomized_benchmarking/utils.py b/src/qibocal/protocols/randomized_benchmarking/utils.py index ef85ba829..0a6541aaa 100644 --- a/src/qibocal/protocols/randomized_benchmarking/utils.py +++ b/src/qibocal/protocols/randomized_benchmarking/utils.py @@ -9,15 +9,14 @@ from qibo import gates from qibo.backends import construct_backend from qibo.models import Circuit -from qibolab.platform import Platform -from qibolab.qubits import QubitId, QubitPairId -from qibocal.auto.operation import Data, Parameters, Results +from qibocal.auto.operation import Data, Parameters, QubitId, QubitPairId, Results from qibocal.auto.transpile import ( dummy_transpiler, execute_transpiled_circuit, execute_transpiled_circuits, ) +from qibocal.calibration import CalibrationPlatform from qibocal.protocols.randomized_benchmarking.dict_utils import ( SINGLE_QUBIT_CLIFFORDS_NAMES, calculate_pulses_clifford, @@ -330,7 +329,7 @@ class StandardRBResult(Results): def setup( params: Parameters, - platform: Platform, + platform: CalibrationPlatform, single_qubit: bool = True, interleave: Optional[str] = None, ): @@ -463,7 +462,7 @@ def execute_circuits(circuits, targets, params, backend, single_qubit=True): def rb_acquisition( params: Parameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], add_inverse_layer: bool = True, interleave: str = None, @@ -510,7 +509,7 @@ def rb_acquisition( def twoq_rb_acquisition( params: Parameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitPairId], add_inverse_layer: bool = True, interleave: str = None, @@ -528,7 +527,7 @@ def twoq_rb_acquisition( RB2QData: The acquired data for two qubit randomized benchmarking. """ targets = [tuple(pair) if isinstance(pair, list) else pair for pair in targets] - data, backend = setup(params, platform, single_qubit=False) + data, backend = setup(params, platform, single_qubit=False, interleave=interleave) circuits, indexes, npulses_per_clifford = get_circuits( params, targets, add_inverse_layer, interleave, single_qubit=False ) diff --git a/src/qibocal/protocols/readout_characterization.py b/src/qibocal/protocols/readout_characterization.py index 04b5928eb..d2f32befd 100644 --- a/src/qibocal/protocols/readout_characterization.py +++ b/src/qibocal/protocols/readout_characterization.py @@ -4,13 +4,11 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, Delay, PulseSequence, Readout from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.protocols.utils import ( effective_qubit_temperature, format_error_single_cell, @@ -19,6 +17,8 @@ table_html, ) +from ..result import unpack + @dataclass class ReadoutCharacterizationParameters(Parameters): @@ -74,14 +74,16 @@ class ReadoutCharacterizationData(Data): def _acquisition( params: ReadoutCharacterizationParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> ReadoutCharacterizationData: """Data acquisition for resonator spectroscopy.""" data = ReadoutCharacterizationData( qubit_frequencies={ - qubit: platform.qubits[qubit].drive_frequency for qubit in targets + # TODO: should this be the drive frequency instead? + qubit: float(platform.calibration.single_qubits[qubit].qubit.frequency_01) + for qubit in targets }, delay=float(params.delay), ) @@ -89,55 +91,46 @@ def _acquisition( # FIXME: ADD 1st measurament and post_selection for accurate state preparation ? for state in [0, 1]: - # Define the pulse sequences - if state == 1: - RX_pulses = {} - ro_pulses = {} sequence = PulseSequence() for qubit in targets: - start = 0 + natives = platform.natives.single_qubit[qubit] + ro_channel = natives.MZ()[0][0] if state == 1: - RX_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - sequence.add(RX_pulses[qubit]) - start = RX_pulses[qubit].finish - ro_pulses[qubit] = [] - for _ in range(2): - ro_pulse = platform.create_qubit_readout_pulse(qubit, start=start) - start += ro_pulse.duration + int( - params.delay - ) # device required conversion - sequence.add(ro_pulse) - ro_pulses[qubit].append(ro_pulse) + sequence += natives.RX() + sequence.append((ro_channel, Delay(duration=natives.RX()[0][1].duration))) + sequence += natives.MZ() + sequence.append((ro_channel, Delay(duration=params.delay))) + sequence += natives.MZ() # execute the pulse sequence - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - ), + results = platform.execute( + [sequence], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, ) - results_samples = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - ), + results_samples = platform.execute( + [sequence], + acquisition_type=AcquisitionType.DISCRIMINATION, + nshots=params.nshots, + relaxation_time=params.relaxation_time, ) # Save the data for qubit in targets: - for i, ro_pulse in enumerate(ro_pulses[qubit]): - result = results[ro_pulse.serial] + readouts = [ + pulse + for pulse in sequence.channel(platform.qubits[qubit].acquisition) + if isinstance(pulse, Readout) + ] + for j, ro_pulse in enumerate(readouts): + i, q = unpack(results[ro_pulse.id]) data.register_qubit( ReadoutCharacterizationType, - (qubit, state, i), - dict(i=result.voltage_i, q=result.voltage_q), + (qubit, state, j), + dict(i=i, q=q), ) - result_samples = results_samples[ro_pulse.serial] - data.samples[qubit, state, i] = result_samples.samples.tolist() - + data.samples[qubit, state, j] = results_samples[ro_pulse.id].tolist() return data @@ -321,10 +314,14 @@ def _plot( def _update( - results: ReadoutCharacterizationResults, platform: Platform, target: QubitId + results: ReadoutCharacterizationResults, + platform: CalibrationPlatform, + target: QubitId, ): update.readout_fidelity(results.fidelity[target], platform, target) - update.assignment_fidelity(results.assignment_fidelity[target], platform, target) + platform.calibration.single_qubits[target].readout.effective_temperature = ( + results.effective_temperature[target][0] + ) readout_characterization = Routine(_acquisition, _fit, _plot, _update) diff --git a/src/qibocal/protocols/readout_mitigation_matrix.py b/src/qibocal/protocols/readout_mitigation_matrix.py index 9d12b3f7e..d894b3bd9 100644 --- a/src/qibocal/protocols/readout_mitigation_matrix.py +++ b/src/qibocal/protocols/readout_mitigation_matrix.py @@ -1,5 +1,5 @@ from dataclasses import dataclass, field -from typing import Optional +from typing import Optional, Tuple import numpy as np import numpy.typing as npt @@ -7,11 +7,11 @@ from qibo import gates from qibo.backends import construct_backend from qibo.models import Circuit -from qibolab.platform import Platform -from qibolab.qubits import QubitId +from scipy.sparse import lil_matrix -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine from qibocal.auto.transpile import dummy_transpiler, execute_transpiled_circuit +from qibocal.calibration import CalibrationPlatform from qibocal.config import log @@ -41,6 +41,14 @@ class ReadoutMitigationMatrixResults(Results): ) +ReadoutMitigationMatrixId = tuple[Tuple[QubitId, ...], str, str] +"""Data identifier for single list of qubits. + +Tuple[QubitId, ...] is the qubits which have been passed on as parameters. +The two strings represents the expected state and the measured state. +""" + + @dataclass class ReadoutMitigationMatrixData(Data): """ReadoutMitigationMatrix acquisition outputs.""" @@ -49,13 +57,13 @@ class ReadoutMitigationMatrixData(Data): """List of qubit ids""" nshots: int """Number of shots""" - data: dict = field(default_factory=dict) + data: dict[ReadoutMitigationMatrixId, float] = field(default_factory=dict) """Raw data acquited.""" def _acquisition( params: ReadoutMitigationMatrixParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[list[QubitId]], ) -> ReadoutMitigationMatrixData: data = ReadoutMitigationMatrixData( @@ -63,7 +71,7 @@ def _acquisition( ) backend = construct_backend("qibolab", platform=platform) transpiler = dummy_transpiler(backend) - qubit_map = [i for i in range(platform.nqubits)] + for qubits in targets: nqubits = len(qubits) for i in range(2**nqubits): @@ -84,7 +92,7 @@ def _acquisition( for freq in frequencies: data.register_qubit( ReadoutMitigationMatrixType, - (qubits), + (tuple(qubits)), dict( state=np.array([int(state, 2)]), frequency=freq, @@ -151,5 +159,26 @@ def _plot( return figs, fitting_report -readout_mitigation_matrix = Routine(_acquisition, _fit, _plot) +def _update( + results: ReadoutMitigationMatrixData, + platform: CalibrationPlatform, + target: list[QubitId], +): + # create empty matrix if it doesn't exist + if platform.calibration.readout_mitigation_matrix is None: + platform.calibration.readout_mitigation_matrix = lil_matrix( + (2**platform.calibration.nqubits, 2**platform.calibration.nqubits) + ) + + # compute indices + mask = sum(1 << platform.calibration.qubit_index(i) for i in target) + indices = [i for i in range(2**platform.calibration.nqubits) if (i & mask) == i] + + # update matrix + platform.calibration.readout_mitigation_matrix[np.ix_(indices, indices)] = ( + results.readout_mitigation_matrix[tuple(target)] + ) + + +readout_mitigation_matrix = Routine(_acquisition, _fit, _plot, _update) """Readout mitigation matrix protocol.""" diff --git a/src/qibocal/protocols/readout_optimization/resonator_amplitude.py b/src/qibocal/protocols/readout_optimization/resonator_amplitude.py index 6826d2757..ab054220d 100644 --- a/src/qibocal/protocols/readout_optimization/resonator_amplitude.py +++ b/src/qibocal/protocols/readout_optimization/resonator_amplitude.py @@ -5,15 +5,14 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, Delay, PulseSequence from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.fitting.classifier.qubit_fit import QubitFit from qibocal.protocols.utils import table_dict, table_html +from qibocal.update import replace @dataclass @@ -64,7 +63,7 @@ class ResonatorAmplitudeResults(Results): def _acquisition( params: ResonatorAmplitudeParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> ResonatorAmplitudeData: r""" @@ -75,7 +74,7 @@ def _acquisition( Args: params (:class:`ResonatorAmplitudeParameters`): input parameters - platform (:class:`Platform`): Qibolab's platform + platform (:class:`CalibrationPlatform`): Qibolab's platform targets (list): list of QubitIds to be characterized Returns: @@ -85,45 +84,42 @@ def _acquisition( data = ResonatorAmplitudeData() for qubit in targets: error = 1 - old_amp = platform.qubits[qubit].native_gates.MZ.amplitude + natives = platform.natives.single_qubit[qubit] + + ro_channel, ro_pulse = natives.MZ()[0] new_amp = params.amplitude_start while error > params.error_threshold and new_amp <= params.amplitude_stop: - platform.qubits[qubit].native_gates.MZ.amplitude = new_amp + + new_ro = replace(ro_pulse, amplitude=new_amp) sequence_0 = PulseSequence() sequence_1 = PulseSequence() - qd_pulses = platform.create_RX_pulse(qubit, start=0) - ro_pulses = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses.finish - ) - sequence_0.add(ro_pulses) - sequence_1.add(qd_pulses) - sequence_1.add(ro_pulses) - - state0_results = platform.execute_pulse_sequence( - sequence_0, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - ), + qd_channel, qd_pulse = natives.RX()[0] + + sequence_1.append((qd_channel, qd_pulse)) + sequence_1.append((ro_channel, Delay(duration=qd_pulse.duration))) + sequence_1.append((ro_channel, new_ro)) + + sequence_0.append((ro_channel, new_ro)) + + state0_results = platform.execute( + [sequence_0], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, ) - state1_results = platform.execute_pulse_sequence( - sequence_1, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - ), + state1_results = platform.execute( + [sequence_1], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, ) - result0 = state0_results[ro_pulses.serial] - result1 = state1_results[ro_pulses.serial] + result0 = state0_results[new_ro.id] + result1 = state1_results[new_ro.id] - i_values = np.concatenate((result0.voltage_i, result1.voltage_i)) - q_values = np.concatenate((result0.voltage_q, result1.voltage_q)) - iq_values = np.stack((i_values, q_values), axis=-1) - nshots = int(len(i_values) / 2) + iq_values = np.concatenate((result0, result1)) + nshots = params.nshots states = [0] * nshots + [1] * nshots model = QubitFit() model.fit(iq_values, np.array(states)) @@ -138,7 +134,6 @@ def _acquisition( threshold=np.array([model.threshold]), ), ) - platform.qubits[qubit].native_gates.MZ.amplitude = old_amp new_amp += params.amplitude_step return data @@ -203,7 +198,9 @@ def _plot( return figures, fitting_report -def _update(results: ResonatorAmplitudeResults, platform: Platform, target: QubitId): +def _update( + results: ResonatorAmplitudeResults, platform: CalibrationPlatform, target: QubitId +): update.readout_amplitude(results.best_amp[target], platform, target) update.iq_angle(results.best_angle[target], platform, target) update.threshold(results.best_threshold[target], platform, target) diff --git a/src/qibocal/protocols/readout_optimization/resonator_frequency.py b/src/qibocal/protocols/readout_optimization/resonator_frequency.py deleted file mode 100644 index c9a27609f..000000000 --- a/src/qibocal/protocols/readout_optimization/resonator_frequency.py +++ /dev/null @@ -1,236 +0,0 @@ -from dataclasses import dataclass, field - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from plotly.subplots import make_subplots -from qibolab import AcquisitionType, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine -from qibocal.fitting.classifier.qubit_fit import QubitFit -from qibocal.protocols.utils import table_dict, table_html - - -@dataclass -class ResonatorFrequencyParameters(Parameters): - """Optimization RO frequency inputs.""" - - freq_width: int - """Width [Hz] for frequency sweep relative to the readout frequency [Hz].""" - freq_step: int - """Frequency step for sweep [Hz].""" - - -@dataclass -class ResonatorFrequencyResults(Results): - """Optimization Resonator frequency outputs.""" - - fidelities: dict[QubitId, list] - """Assignment fidelities.""" - best_freq: dict[QubitId, float] - """Resonator Frequency with the highest assignment fidelity.""" - best_angle: dict[QubitId, float] - """IQ angle that maximes assignment fidelity""" - best_threshold: dict[QubitId, float] - """Threshold that maximes assignment fidelity""" - - -ResonatorFrequencyType = np.dtype( - [ - ("freq", np.float64), - ("assignment_fidelity", np.float64), - ("angle", np.float64), - ("threshold", np.float64), - ] -) -"""Custom dtype for Optimization RO frequency.""" - - -@dataclass -class ResonatorFrequencyData(Data): - """ "Optimization RO frequency acquisition outputs.""" - - resonator_type: str - """Resonator type.""" - data: dict[QubitId, npt.NDArray[ResonatorFrequencyType]] = field( - default_factory=dict - ) - - def unique_freqs(self, qubit: QubitId) -> np.ndarray: - return np.unique(self.data[qubit]["freq"]) - - -def _acquisition( - params: ResonatorFrequencyParameters, platform: Platform, targets: list[QubitId] -) -> ResonatorFrequencyData: - r""" - Data acquisition for readout frequency optimization. - While sweeping the readout frequency, the routine performs a single shot - classification and evaluates the assignement fidelity. - At the end, the readout frequency is updated, choosing the one that has - the highest assignment fidelity. - - Args: - params (ResonatorFrequencyParameters): experiment's parameters - platform (Platform): Qibolab platform object - qubits (list): list of target qubits to perform the action - - """ - - # create 2 sequences of pulses for the experiment: - # sequence_0: I - MZ - # sequence_1: RX - MZ - - # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel - sequence_0 = PulseSequence() - sequence_1 = PulseSequence() - ro_pulses = {} - qd_pulses = {} - for qubit in targets: - qd_pulses[qubit] = platform.create_RX_pulse(qubit, start=0) - ro_pulses[qubit] = platform.create_qubit_readout_pulse( - qubit, start=qd_pulses[qubit].finish - ) - sequence_0.add(ro_pulses[qubit]) - sequence_1.add(qd_pulses[qubit]) - sequence_1.add(ro_pulses[qubit]) - - # define the parameter to sweep and its range: - delta_frequency_range = np.arange( - -params.freq_width / 2, params.freq_width / 2, params.freq_step - ) - - data = ResonatorFrequencyData(resonator_type=platform.resonator_type) - sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[ro_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - - results_0 = platform.sweep( - sequence_0, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - ), - sweeper, - ) - - results_1 = platform.sweep( - sequence_1, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - ), - sweeper, - ) - - # retrieve the results for every qubit - for qubit in targets: - for k, freq in enumerate(delta_frequency_range): - i_values = [] - q_values = [] - states = [] - for i, results in enumerate([results_0, results_1]): - result = results[ro_pulses[qubit].serial] - i_values.extend(result.voltage_i[:, k]) - q_values.extend(result.voltage_q[:, k]) - states.extend([i] * len(result.voltage_i[:, k])) - - model = QubitFit() - model.fit(np.stack((i_values, q_values), axis=-1), np.array(states)) - data.register_qubit( - ResonatorFrequencyType, - (qubit), - dict( - freq=np.array([ro_pulses[qubit].frequency + freq]), - assignment_fidelity=np.array([model.assignment_fidelity]), - angle=np.array([model.angle]), - threshold=np.array([model.threshold]), - ), - ) - return data - - -def _fit(data: ResonatorFrequencyData) -> ResonatorFrequencyResults: - """Post-Processing for Optimization RO frequency""" - qubits = data.qubits - best_freq = {} - best_angle = {} - best_threshold = {} - highest_fidelity = {} - for qubit in qubits: - data_qubit = data[qubit] - index_best_fid = np.argmax(data_qubit["assignment_fidelity"]) - highest_fidelity[qubit] = data_qubit["assignment_fidelity"][index_best_fid] - best_freq[qubit] = data_qubit["freq"][index_best_fid] - best_angle[qubit] = data_qubit["angle"][index_best_fid] - best_threshold[qubit] = data_qubit["threshold"][index_best_fid] - - return ResonatorFrequencyResults( - fidelities=highest_fidelity, - best_freq=best_freq, - best_angle=best_angle, - best_threshold=best_threshold, - ) - - -def _plot( - data: ResonatorFrequencyData, fit: ResonatorFrequencyResults, target: QubitId -): - """Plotting function for Optimization RO frequency.""" - figures = [] - freqs = data[target]["freq"] - opacity = 1 - fitting_report = "" - fig = make_subplots( - rows=1, - cols=1, - ) - if fit is not None: - fig.add_trace( - go.Scatter( - x=freqs, - y=data[target]["assignment_fidelity"], - opacity=opacity, - showlegend=True, - ), - row=1, - col=1, - ) - - fitting_report = table_html( - table_dict( - target, - "Best Resonator Frequency [Hz]", - np.round(fit.best_freq[target], 4), - ) - ) - - fig.update_layout( - showlegend=True, - xaxis_title="Resonator Frequencies [GHz]", - yaxis_title="Assignment Fidelities", - ) - - figures.append(fig) - - return figures, fitting_report - - -def _update(results: ResonatorFrequencyResults, platform: Platform, target: QubitId): - update.readout_frequency(results.best_freq[target], platform, target) - update.threshold(results.best_threshold[target], platform, target) - update.iq_angle(results.best_angle[target], platform, target) - - -resonator_frequency = Routine(_acquisition, _fit, _plot, _update) -""""Optimization RO frequency Routine object.""" diff --git a/src/qibocal/protocols/readout_optimization/twpa_calibration/__init__.py b/src/qibocal/protocols/readout_optimization/twpa_calibration/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/src/qibocal/protocols/readout_optimization/twpa_calibration/frequency.py b/src/qibocal/protocols/readout_optimization/twpa_calibration/frequency.py deleted file mode 100644 index f35c5e1e3..000000000 --- a/src/qibocal/protocols/readout_optimization/twpa_calibration/frequency.py +++ /dev/null @@ -1,182 +0,0 @@ -from dataclasses import dataclass, field - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from qibolab.platform import Platform -from qibolab.qubits import QubitId - -from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine -from qibocal.protocols import classification -from qibocal.protocols.readout_optimization.resonator_frequency import ( - ResonatorFrequencyType, -) -from qibocal.protocols.utils import HZ_TO_GHZ, table_dict, table_html - - -@dataclass -class TwpaFrequencyParameters(Parameters): - """TwpaFrequency runcard inputs.""" - - frequency_width: float - """Relative frequency width [Hz]""" - frequency_step: float - """Frequency step [Hz]""" - - -@dataclass -class TwpaFrequencyData(Data): - """TwpaFrequency acquisition outputs.""" - - data: dict[ - tuple[QubitId, float], npt.NDArray[classification.ClassificationType] - ] = field(default_factory=dict) - """Raw data acquired.""" - frequencies: dict[QubitId, float] = field(default_factory=dict) - """Frequencies for each qubit.""" - - -@dataclass -class TwpaFrequencyResults(Results): - """TwpaFrequency outputs.""" - - best_freqs: dict[QubitId, float] = field(default_factory=dict) - best_fidelities: dict[QubitId, float] = field(default_factory=dict) - best_angles: dict[QubitId, float] = field(default_factory=dict) - best_thresholds: dict[QubitId, float] = field(default_factory=dict) - - -def _acquisition( - params: TwpaFrequencyParameters, - platform: Platform, - targets: list[QubitId], -) -> TwpaFrequencyData: - r""" - Data acquisition for TWPA power optmization. - This protocol perform a classification protocol for twpa frequencies - in the range [twpa_frequency - frequency_width / 2, twpa_frequency + frequency_width / 2] - with step frequency_step. - - Args: - params (:class:`TwpaFrequencyParameters`): input parameters - platform (:class:`Platform`): Qibolab's platform - qubits (dict): dict of target :class:`Qubit` objects to be characterized - - Returns: - data (:class:`TwpaFrequencyData`) - """ - - data = TwpaFrequencyData() - - freq_range = np.arange( - -params.frequency_width / 2, params.frequency_width / 2, params.frequency_step - ).astype(int) - - initial_twpa_freq = {} - for qubit in targets: - initial_twpa_freq[qubit] = float( - platform.qubits[qubit].twpa.local_oscillator.frequency - ) - data.frequencies[qubit] = list( - float(platform.qubits[qubit].twpa.local_oscillator.frequency) + freq_range - ) - - for freq in freq_range: - for qubit in targets: - platform.qubits[qubit].twpa.local_oscillator.frequency = ( - initial_twpa_freq[qubit] + freq - ) - - classification_data = classification._acquisition( - classification.SingleShotClassificationParameters.load( - {"nshots": params.nshots} - ), - platform, - targets, - ) - classification_result = classification._fit(classification_data) - for qubit in targets: - data.register_qubit( - ResonatorFrequencyType, - (qubit), - dict( - freq=np.array( - [platform.qubits[qubit].twpa.local_oscillator.frequency], - dtype=np.float64, - ), - assignment_fidelity=np.array( - [classification_result.assignment_fidelity[qubit]], - ), - angle=np.array([classification_result.rotation_angle[qubit]]), - threshold=np.array([classification_result.threshold[qubit]]), - ), - ) - return data - - -def _fit(data: TwpaFrequencyData) -> TwpaFrequencyResults: - """Extract fidelity for each configuration qubit / param. - Where param can be either frequency or power.""" - - qubits = data.qubits - best_freq = {} - best_fidelity = {} - best_angle = {} - best_threshold = {} - for qubit in qubits: - data_qubit = data[qubit] - index_best_err = np.argmax(data_qubit["assignment_fidelity"]) - best_fidelity[qubit] = data_qubit["assignment_fidelity"][index_best_err] - best_freq[qubit] = data_qubit["freq"][index_best_err] - best_angle[qubit] = data_qubit["angle"][index_best_err] - best_threshold[qubit] = data_qubit["threshold"][index_best_err] - - return TwpaFrequencyResults( - best_freq, best_fidelity, best_thresholds=best_threshold, best_angles=best_angle - ) - - -def _plot(data: TwpaFrequencyData, fit: TwpaFrequencyResults, target: QubitId): - """Plotting function that shows the assignment fidelity - for different values of the twpa frequency for a single qubit""" - - figures = [] - fitting_report = "" - if fit is not None: - qubit_data = data.data[target] - fidelities = qubit_data["assignment_fidelity"] - frequencies = qubit_data["freq"] - fitting_report = table_html( - table_dict( - target, - ["Best assignment fidelity", "TWPA Frequency [Hz]"], - [ - np.round(fit.best_fidelities[target], 3), - fit.best_freqs[target], - ], - ) - ) - fig = go.Figure( - [go.Scatter(x=frequencies * HZ_TO_GHZ, y=fidelities, name="Fidelity")] - ) - - fig.update_layout( - showlegend=True, - xaxis_title="TWPA Frequency [GHz]", - yaxis_title="Assignment Fidelity", - ) - - figures.append(fig) - - return figures, fitting_report - - -def _update(results: TwpaFrequencyResults, platform: Platform, target: QubitId): - update.twpa_frequency(results.best_freqs[target], platform, target) - update.iq_angle(results.best_angles[target], platform, target) - update.threshold(results.best_thresholds[target], platform, target) - - -twpa_frequency = Routine(_acquisition, _fit, _plot, _update) -"""Twpa frequency Routine object.""" diff --git a/src/qibocal/protocols/readout_optimization/twpa_calibration/frequency_SNR.py b/src/qibocal/protocols/readout_optimization/twpa_calibration/frequency_SNR.py deleted file mode 100644 index 7b1e1e32b..000000000 --- a/src/qibocal/protocols/readout_optimization/twpa_calibration/frequency_SNR.py +++ /dev/null @@ -1,265 +0,0 @@ -from dataclasses import dataclass, field -from typing import Optional - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from plotly.subplots import make_subplots -from qibolab.platform import Platform -from qibolab.qubits import QubitId - -from qibocal.auto.operation import Data, Parameters, Results, Routine -from qibocal.protocols.resonator_spectroscopy import resonator_spectroscopy -from qibocal.protocols.utils import HZ_TO_GHZ, PowerLevel, table_dict, table_html - - -@dataclass -class ResonatorTWPAFrequencyParameters(Parameters): - """ResonatorTWPAFrequency runcard inputs.""" - - freq_width: int - """Width for frequency sweep relative to the readout frequency (Hz).""" - freq_step: int - """Frequency step for sweep (Hz).""" - twpa_freq_width: int - """Width for TPWA frequency sweep (Hz).""" - twpa_freq_step: int - """TPWA frequency step (Hz).""" - power_level: PowerLevel - """resonator Power regime (low or high).""" - nshots: Optional[int] = None - """Number of shots.""" - relaxation_time: Optional[int] = None - """Relaxation time (ns).""" - - def __post_init__(self): - self.power_level = PowerLevel(self.power_level) - - -@dataclass -class ResonatorTWPAFrequencyResults(Results): - """ResonatorTWPAFrequency outputs.""" - - twpa_frequency: dict[QubitId, float] = field(default_factory=dict) - """TWPA frequency [GHz] for each qubit.""" - frequency: Optional[dict[QubitId, float]] = field(default_factory=dict) - """Readout frequency [GHz] for each qubit.""" - bare_frequency: Optional[dict[QubitId, float]] = field(default_factory=dict) - """Bare frequency [GHz] for each qubit.""" - - -ResonatorTWPAFrequencyType = np.dtype( - [ - ("freq", np.float64), - ("twpa_freq", np.float64), - ("signal", np.float64), - ("phase", np.float64), - ] -) -"""Custom dtype for Resonator TWPA Frequency.""" - - -@dataclass -class ResonatorTWPAFrequencyData(Data): - """ResonatorTWPAFrequency data acquisition.""" - - resonator_type: str - """Resonator type.""" - data: dict[QubitId, npt.NDArray[ResonatorTWPAFrequencyType]] = field( - default_factory=dict - ) - """Raw data acquired.""" - power_level: Optional[PowerLevel] = None - """Power regime of the resonator.""" - - @classmethod - def load(cls, path): - obj = super().load(path) - # Instantiate PowerLevel object - if obj.power_level is not None: # pylint: disable=E1101 - obj.power_level = PowerLevel(obj.power_level) # pylint: disable=E1101 - return obj - - -def _acquisition( - params: ResonatorTWPAFrequencyParameters, - platform: Platform, - targets: list[QubitId], -) -> ResonatorTWPAFrequencyData: - r""" - Data acquisition for TWPA frequency optmization using SNR. - This protocol perform a classification protocol for twpa frequencies - in the range [twpa_frequency - frequency_width / 2, twpa_frequency + frequency_width / 2] - with step frequency_step. - - Args: - params (:class:`ResonatorTWPAFrequencyParameters`): input parameters - platform (:class:`Platform`): Qibolab's platform - qubits (dict): dict of target :class:`Qubit` objects to be characterized - - Returns: - data (:class:`ResonatorTWPAFrequencyData`) - """ - - data = ResonatorTWPAFrequencyData( - power_level=params.power_level, - resonator_type=platform.resonator_type, - ) - - TWPAFrequency_range = np.arange( - -params.twpa_freq_width // 2, params.twpa_freq_width // 2, params.twpa_freq_step - ) - - initial_twpa_freq = {} - for qubit in targets: - initial_twpa_freq[qubit] = float( - platform.qubits[qubit].twpa.local_oscillator.frequency - ) - - for _freq in TWPAFrequency_range: - for qubit in targets: - platform.qubits[qubit].twpa.local_oscillator.frequency = ( - initial_twpa_freq[qubit] + _freq - ) - - resonator_spectroscopy_data, _ = resonator_spectroscopy.acquisition( - resonator_spectroscopy.parameters_type.load( - { - "freq_width": params.freq_width, - "freq_step": params.freq_step, - "power_level": params.power_level, - "relaxation_time": params.relaxation_time, - "nshots": params.nshots, - } - ), - platform, - targets, - ) - - for qubit in targets: - data.register_qubit( - ResonatorTWPAFrequencyType, - (qubit), - dict( - signal=resonator_spectroscopy_data[qubit].signal, - phase=resonator_spectroscopy_data[qubit].phase, - freq=resonator_spectroscopy_data[qubit].freq, - twpa_freq=_freq + initial_twpa_freq[qubit], - ), - ) - - return data - - -def _fit(data: ResonatorTWPAFrequencyData) -> ResonatorTWPAFrequencyResults: - """Post-processing function for ResonatorTWPASpectroscopy.""" - qubits = data.qubits - bare_frequency = {} - frequency = {} - twpa_frequency = {} - for qubit in qubits: - data_qubit = data[qubit] - if data.resonator_type == "3D": - index_best_freq = np.argmax(data_qubit["signal"]) - else: - index_best_freq = np.argmin(data_qubit["signal"]) - twpa_frequency[qubit] = data_qubit["twpa_freq"][index_best_freq] - - if data.power_level is PowerLevel.high: - bare_frequency[qubit] = data_qubit["freq"][index_best_freq] - else: - frequency[qubit] = data_qubit["freq"][index_best_freq] - - if data.power_level is PowerLevel.high: - return ResonatorTWPAFrequencyResults( - twpa_frequency=twpa_frequency, - bare_frequency=bare_frequency, - ) - else: - return ResonatorTWPAFrequencyResults( - twpa_frequency=twpa_frequency, - frequency=frequency, - ) - - -def _plot(data: ResonatorTWPAFrequencyData, fit: ResonatorTWPAFrequencyResults, target): - """Plotting for ResonatorTWPAFrequency.""" - - figures = [] - fitting_report = "" - fig = make_subplots( - rows=1, - cols=2, - horizontal_spacing=0.1, - vertical_spacing=0.2, - subplot_titles=( - "Signal [a.u.]", - "Phase [rad]", - ), - ) - - fitting_report = "" - qubit_data = data[target] - resonator_frequencies = qubit_data.freq * HZ_TO_GHZ - twpa_frequencies = qubit_data.twpa_freq * HZ_TO_GHZ - - fig.add_trace( - go.Heatmap( - x=resonator_frequencies, - y=twpa_frequencies, - z=qubit_data.signal, - colorbar_x=0.46, - ), - row=1, - col=1, - ) - fig.update_xaxes(title_text="Frequency [GHz]", row=1, col=1) - fig.update_yaxes(title_text="TWPA Frequency [GHz]", row=1, col=1) - fig.add_trace( - go.Heatmap( - x=resonator_frequencies, - y=twpa_frequencies, - z=qubit_data.phase, - colorbar_x=1.01, - ), - row=1, - col=2, - ) - fig.update_xaxes(title_text="Frequency [GHz]", row=1, col=2) - fig.update_yaxes(title_text="TWPA Frequency [GHz]", row=1, col=2) - - if fit is not None: - label_1 = "TWPA Frequency [Hz]" - twpa_frequency = np.round(fit.twpa_frequency[target]) - if target in fit.bare_frequency: - label_2 = "High Power Resonator Frequency [Hz]" - resonator_frequency = np.round(fit.bare_frequency[target]) - else: - label_2 = "Low Power Resonator Frequency [Hz]" - resonator_frequency = np.round(fit.frequency[target]) - - summary = table_dict( - target, - [ - label_2, - label_1, - ], - [ - resonator_frequency, - twpa_frequency, - ], - ) - - fitting_report = table_html(summary) - - fig.update_layout( - showlegend=False, - ) - - figures.append(fig) - - return figures, fitting_report - - -twpa_frequency_snr = Routine(_acquisition, _fit, _plot) -"""Resonator TWPA Frequency Routine object.""" diff --git a/src/qibocal/protocols/readout_optimization/twpa_calibration/frequency_power.py b/src/qibocal/protocols/readout_optimization/twpa_calibration/frequency_power.py deleted file mode 100644 index 86f21a4e0..000000000 --- a/src/qibocal/protocols/readout_optimization/twpa_calibration/frequency_power.py +++ /dev/null @@ -1,226 +0,0 @@ -from dataclasses import dataclass, field - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from qibolab.platform import Platform -from qibolab.qubits import QubitId - -from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine -from qibocal.protocols import classification -from qibocal.protocols.utils import HZ_TO_GHZ, table_dict, table_html - - -@dataclass -class TwpaFrequencyPowerParameters(Parameters): - """Twpa Frequency Power runcard inputs.""" - - frequency_width: float - """Frequency total width.""" - frequency_step: float - """Frequency step to be probed.""" - power_width: float - """Power total width.""" - power_step: float - """Power step to be probed.""" - - -TwpaFrequencyPowerType = np.dtype( - [ - ("freq", np.float64), - ("power", np.float64), - ("assignment_fidelity", np.float64), - ("angle", np.float64), - ("threshold", np.float64), - ] -) - - -@dataclass -class TwpaFrequencyPowerData(Data): - """Twpa Frequency Power acquisition outputs.""" - - data: dict[ - tuple[QubitId, float, float], npt.NDArray[classification.ClassificationType] - ] = field(default_factory=dict) - """Raw data acquired.""" - frequencies: dict[QubitId, float] = field(default_factory=dict) - """Frequencies for each qubit.""" - powers: dict[QubitId, float] = field(default_factory=dict) - """Powers for each qubit.""" - - -@dataclass -class TwpaFrequencyPowerResults(Results): - """Twpa Frequency Power outputs.""" - - best_freqs: dict[QubitId, float] = field(default_factory=dict) - best_powers: dict[QubitId, float] = field(default_factory=dict) - best_fidelities: dict[QubitId, float] = field(default_factory=dict) - best_angles: dict[QubitId, float] = field(default_factory=dict) - best_thresholds: dict[QubitId, float] = field(default_factory=dict) - - -def _acquisition( - params: TwpaFrequencyPowerParameters, - platform: Platform, - targets: list[QubitId], -) -> TwpaFrequencyPowerData: - r""" - Data acquisition for TWPA frequency vs. power optmization. - This protocol perform a classification protocol for twpa frequencies - in the range [twpa_frequency - frequency_width / 2, twpa_frequency + frequency_width / 2] - with step frequency_step and powers in the range [twpa_power - power_width / 2, twpa_power + power_width / 2] - - Args: - params (:class:`TwpaFrequencyPowerParameters`): input parameters - platform (:class:`Platform`): Qibolab's platform - targets (list): list of qubit to be characterized - - Returns: - data (:class:`TwpaFrequencyPowerData`) - """ - - data = TwpaFrequencyPowerData() - - freq_range = np.arange( - -params.frequency_width / 2, params.frequency_width / 2, params.frequency_step - ).astype(int) - power_range = np.arange( - -params.power_width / 2, params.power_width / 2, params.power_step - ) - data = TwpaFrequencyPowerData() - - initial_twpa_freq = {} - initial_twpa_power = {} - for qubit in targets: - initial_twpa_freq[qubit] = platform.qubits[ - qubit - ].twpa.local_oscillator.frequency - initial_twpa_power[qubit] = platform.qubits[qubit].twpa.local_oscillator.power - - for freq in freq_range: - platform.qubits[qubit].twpa.local_oscillator.frequency = ( - initial_twpa_freq[qubit] + freq - ) - - for power in power_range: - platform.qubits[qubit].twpa.local_oscillator.power = ( - initial_twpa_power[qubit] + power - ) - - classification_data = classification._acquisition( - classification.SingleShotClassificationParameters.load( - {"nshots": params.nshots} - ), - platform, - targets, - ) - - classification_result = classification._fit(classification_data) - - data.register_qubit( - TwpaFrequencyPowerType, - (qubit), - dict( - freq=np.array( - [platform.qubits[qubit].twpa.local_oscillator.frequency], - dtype=np.float64, - ), - power=np.array( - [platform.qubits[qubit].twpa.local_oscillator.power], - dtype=np.float64, - ), - assignment_fidelity=np.array( - [classification_result.assignment_fidelity[qubit]], - ), - angle=np.array([classification_result.rotation_angle[qubit]]), - threshold=np.array([classification_result.threshold[qubit]]), - ), - ) - return data - - -def _fit(data: TwpaFrequencyPowerData) -> TwpaFrequencyPowerResults: - """Extract fidelity for each configuration qubit / param. - Where param can be either frequency or power.""" - - best_freq = {} - best_power = {} - best_fidelity = {} - best_angle = {} - best_threshold = {} - qubits = data.qubits - - for qubit in qubits: - data_qubit = data[qubit] - index_best_err = np.argmax(data_qubit["assignment_fidelity"]) - best_fidelity[qubit] = data_qubit["assignment_fidelity"][index_best_err] - best_freq[qubit] = data_qubit["freq"][index_best_err] - best_power[qubit] = data_qubit["power"][index_best_err] - best_angle[qubit] = data_qubit["angle"][index_best_err] - best_threshold[qubit] = data_qubit["threshold"][index_best_err] - - return TwpaFrequencyPowerResults( - best_freq, - best_power, - best_fidelity, - best_angles=best_angle, - best_thresholds=best_threshold, - ) - - -def _plot( - data: TwpaFrequencyPowerData, fit: TwpaFrequencyPowerResults, target: QubitId -): - """Plotting function that shows the assignment fidelity - for different values of the twpa frequency for a single qubit""" - - figures = [] - fitting_report = "" - if fit is not None: - qubit_data = data.data[target] - fidelities = qubit_data["assignment_fidelity"] - frequencies = qubit_data["freq"] - powers = qubit_data["power"] - fitting_report = table_html( - table_dict( - target, - ["Best assignment fidelity", "TWPA Frequency [Hz]", "TWPA Power [dBm]"], - [ - np.round(fit.best_fidelities[target], 3), - fit.best_freqs[target], - np.round(fit.best_powers[target], 3), - ], - ) - ) - - fig = go.Figure( - [ - go.Heatmap( - x=frequencies * HZ_TO_GHZ, y=powers, z=fidelities, name="Fidelity" - ) - ] - ) - - fig.update_layout( - showlegend=True, - xaxis_title="TWPA Frequency [GHz]", - yaxis_title="TWPA Power [dBm]", - ) - - figures.append(fig) - - return figures, fitting_report - - -def _update(results: TwpaFrequencyPowerResults, platform: Platform, target: QubitId): - update.twpa_frequency(results.best_freqs[target], platform, target) - update.twpa_power(results.best_powers[target], platform, target) - update.iq_angle(results.best_angles[target], platform, target) - update.threshold(results.best_thresholds[target], platform, target) - - -twpa_frequency_power = Routine(_acquisition, _fit, _plot, _update) -"""Twpa frequency Routine object.""" diff --git a/src/qibocal/protocols/readout_optimization/twpa_calibration/power.py b/src/qibocal/protocols/readout_optimization/twpa_calibration/power.py deleted file mode 100644 index 76f0b3c87..000000000 --- a/src/qibocal/protocols/readout_optimization/twpa_calibration/power.py +++ /dev/null @@ -1,184 +0,0 @@ -from dataclasses import dataclass, field - -import numpy as np -import plotly.graph_objects as go -from qibolab.platform import Platform -from qibolab.qubits import QubitId - -from qibocal import update -from qibocal.auto.operation import Parameters, Results, Routine -from qibocal.protocols import classification -from qibocal.protocols.utils import table_dict, table_html - -from . import frequency - - -@dataclass -class TwpaPowerParameters(Parameters): - """TwpaPower runcard inputs.""" - - power_width: float - """Power total width.""" - power_step: float - """Power step to be probed.""" - - -TwpaPowerType = np.dtype( - [ - ("power", np.float64), - ("assignment_fidelity", np.float64), - ("angle", np.float64), - ("threshold", np.float64), - ] -) - - -@dataclass -class TwpaPowerData(frequency.TwpaFrequencyData): - """Data class for twpa power protocol.""" - - powers: dict[QubitId, float] = field(default_factory=dict) - """Frequencies for each qubit.""" - - -@dataclass -class TwpaPowerResults(Results): - """Result class for twpa power protocol.""" - - best_powers: dict[QubitId, float] = field(default_factory=dict) - best_fidelities: dict[QubitId, float] = field(default_factory=dict) - best_angles: dict[QubitId, float] = field(default_factory=dict) - best_thresholds: dict[QubitId, float] = field(default_factory=dict) - - -def _acquisition( - params: TwpaPowerParameters, - platform: Platform, - targets: list[QubitId], -) -> TwpaPowerData: - r""" - Data acquisition for TWPA power optmization. - This protocol perform a classification protocol for twpa powers - in the range [twpa_power - power_width / 2, twpa_power + power_width / 2] - with step power_step. - - Args: - params (:class:`TwpaPowerParameters`): input parameters - platform (:class:`Platform`): Qibolab's platform - targets (list): list of QubitId to be characterized - - Returns: - data (:class:`TwpaFrequencyData`) - """ - - data = TwpaPowerData() - - power_range = np.arange( - -params.power_width / 2, params.power_width / 2, params.power_step - ) - - initial_twpa_power = {} - for qubit in targets: - initial_twpa_power[qubit] = platform.qubits[qubit].twpa.local_oscillator.power - data.powers[qubit] = list( - platform.qubits[qubit].twpa.local_oscillator.power + power_range - ) - - for power in power_range: - for qubit in targets: - platform.qubits[qubit].twpa.local_oscillator.power = ( - initial_twpa_power[qubit] + power - ) - - classification_data = classification._acquisition( - classification.SingleShotClassificationParameters.load( - {"nshots": params.nshots} - ), - platform, - targets, - ) - classification_result = classification._fit(classification_data) - - for qubit in targets: - data.register_qubit( - TwpaPowerType, - (qubit), - dict( - power=np.array( - [float(platform.qubits[qubit].twpa.local_oscillator.power)] - ), - assignment_fidelity=np.array( - [classification_result.assignment_fidelity[qubit]] - ), - angle=np.array([classification_result.rotation_angle[qubit]]), - threshold=np.array([classification_result.threshold[qubit]]), - ), - ) - return data - - -def _fit(data: TwpaPowerData) -> TwpaPowerResults: - """Extract fidelity for each configuration qubit / param. - Where param can be either frequency or power.""" - qubits = data.qubits - best_power = {} - best_fidelity = {} - best_angle = {} - best_threshold = {} - for qubit in qubits: - data_qubit = data[qubit] - index_best_err = np.argmax(data_qubit["assignment_fidelity"]) - best_fidelity[qubit] = data_qubit["assignment_fidelity"][index_best_err] - best_power[qubit] = data_qubit["power"][index_best_err] - best_angle[qubit] = data_qubit["angle"][index_best_err] - best_threshold[qubit] = data_qubit["threshold"][index_best_err] - - return TwpaPowerResults( - best_power, - best_fidelity, - best_angles=best_angle, - best_thresholds=best_threshold, - ) - - -def _plot(data: TwpaPowerData, fit: TwpaPowerResults, target: QubitId): - """Plotting function that shows the assignment fidelity - for different values of the twpa power for a single qubit.""" - - figures = [] - fitting_report = "" - - if fit is not None: - qubit_data = data.data[target] - fidelities = qubit_data["assignment_fidelity"] - powers = qubit_data["power"] - fitting_report = table_html( - table_dict( - target, - ["Best assignment fidelity", "TWPA Power [dBm]"], - [ - np.round(fit.best_fidelities[target], 3), - np.round(fit.best_powers[target], 3), - ], - ) - ) - fig = go.Figure([go.Scatter(x=powers, y=fidelities, name="Fidelity")]) - figures.append(fig) - - fig.update_layout( - showlegend=True, - xaxis_title="TWPA Power [dB]", - yaxis_title="Assignment Fidelity", - ) - - return figures, fitting_report - - -def _update(results: TwpaPowerResults, platform: Platform, target: QubitId): - update.twpa_power(results.best_powers[target], platform, target) - update.iq_angle(results.best_angles[target], platform, target) - update.threshold(results.best_thresholds[target], platform, target) - - -twpa_power = Routine(_acquisition, _fit, _plot, _update) -"""Twpa power Routine object.""" diff --git a/src/qibocal/protocols/readout_optimization/twpa_calibration/power_SNR.py b/src/qibocal/protocols/readout_optimization/twpa_calibration/power_SNR.py deleted file mode 100644 index 93b22e0e5..000000000 --- a/src/qibocal/protocols/readout_optimization/twpa_calibration/power_SNR.py +++ /dev/null @@ -1,265 +0,0 @@ -from dataclasses import dataclass, field -from typing import Optional - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from plotly.subplots import make_subplots -from qibolab.platform import Platform -from qibolab.qubits import QubitId - -from qibocal.auto.operation import Data, Parameters, Results, Routine -from qibocal.protocols.resonator_spectroscopy import resonator_spectroscopy -from qibocal.protocols.utils import HZ_TO_GHZ, PowerLevel, table_dict, table_html - - -@dataclass -class ResonatorTWPAPowerParameters(Parameters): - """ResonatorTWPAPower runcard inputs.""" - - freq_width: int - """Width for frequency sweep relative to the readout frequency (Hz).""" - freq_step: int - """Frequency step for sweep (Hz).""" - twpa_pow_width: int - """Width for TPWA power sweep (dBm).""" - twpa_pow_step: int - """TPWA power step (dBm).""" - power_level: PowerLevel - """resonator Power regime (low or high).""" - nshots: Optional[int] = None - """Number of shots.""" - relaxation_time: Optional[int] = None - """Relaxation time (ns).""" - - def __post_init__(self): - self.power_level = PowerLevel(self.power_level) - - -@dataclass -class ResonatorTWPAPowerResults(Results): - """ResonatorTWPAPower outputs.""" - - twpa_power: dict[QubitId, float] = field(default_factory=dict) - """TWPA frequency [GHz] for each qubit.""" - frequency: Optional[dict[QubitId, float]] = field(default_factory=dict) - """Readout frequency [GHz] for each qubit.""" - bare_frequency: Optional[dict[QubitId, float]] = field(default_factory=dict) - """Bare frequency [GHz] for each qubit.""" - - -ResonatorTWPAPowerType = np.dtype( - [ - ("freq", np.float64), - ("twpa_pow", np.float64), - ("signal", np.float64), - ("phase", np.float64), - ] -) -"""Custom dtype for Resonator TWPA Power.""" - - -@dataclass -class ResonatorTWPAPowerData(Data): - """ResonatorTWPAPower data acquisition.""" - - resonator_type: str - """Resonator type.""" - data: dict[QubitId, npt.NDArray[ResonatorTWPAPowerType]] = field( - default_factory=dict - ) - """Raw data acquired.""" - power_level: Optional[PowerLevel] = None - """Power regime of the resonator.""" - - @classmethod - def load(cls, path): - obj = super().load(path) - # Instantiate PowerLevel object - if obj.power_level is not None: # pylint: disable=E1101 - obj.power_level = PowerLevel(obj.power_level) # pylint: disable=E1101 - return obj - - -def _acquisition( - params: ResonatorTWPAPowerParameters, - platform: Platform, - targets: list[QubitId], -) -> ResonatorTWPAPowerData: - r""" - Data acquisition for TWPA power optmization using SNR. - This protocol perform a classification protocol for twpa powers - in the range [twpa_power - frequency_width / 2, twpa_power + frequency_width / 2] - with step frequency_step. - - Args: - params (:class:`ResonatorTWPAPowerParameters`): input parameters - platform (:class:`Platform`): Qibolab's platform - qubits (dict): dict of target :class:`Qubit` objects to be characterized - - Returns: - data (:class:`ResonatorTWPAPowerData`) - """ - - data = ResonatorTWPAPowerData( - power_level=params.power_level, - resonator_type=platform.resonator_type, - ) - - TWPAPower_range = np.arange( - -params.twpa_pow_width / 2, params.twpa_pow_width / 2, params.twpa_pow_step - ) - - initial_twpa_pow = {} - for qubit in targets: - initial_twpa_pow[qubit] = float( - platform.qubits[qubit].twpa.local_oscillator.power - ) - - for _pow in TWPAPower_range: - for qubit in targets: - platform.qubits[qubit].twpa.local_oscillator.power = ( - initial_twpa_pow[qubit] + _pow - ) - - resonator_spectroscopy_data, _ = resonator_spectroscopy.acquisition( - resonator_spectroscopy.parameters_type.load( - { - "freq_width": params.freq_width, - "freq_step": params.freq_step, - "power_level": params.power_level, - "relaxation_time": params.relaxation_time, - "nshots": params.nshots, - } - ), - platform, - targets, - ) - - for qubit in targets: - data.register_qubit( - ResonatorTWPAPowerType, - (qubit), - dict( - signal=resonator_spectroscopy_data.data[qubit].signal, - phase=resonator_spectroscopy_data.data[qubit].phase, - freq=resonator_spectroscopy_data.data[qubit].freq, - twpa_pow=_pow + initial_twpa_pow[qubit], - ), - ) - - return data - - -def _fit(data: ResonatorTWPAPowerData, fit_type="att") -> ResonatorTWPAPowerResults: - """Post-processing function for ResonatorTWPASpectroscopy.""" - qubits = data.qubits - bare_frequency = {} - frequency = {} - twpa_power = {} - for qubit in qubits: - data_qubit = data[qubit] - if data.resonator_type == "3D": - index_best_pow = np.argmax(data_qubit["signal"]) - else: - index_best_pow = np.argmin(data_qubit["signal"]) - twpa_power[qubit] = data_qubit["twpa_pow"][index_best_pow] - - if data.power_level is PowerLevel.high: - bare_frequency[qubit] = data_qubit["freq"][index_best_pow] - else: - frequency[qubit] = data_qubit["freq"][index_best_pow] - - if data.power_level is PowerLevel.high: - return ResonatorTWPAPowerResults( - twpa_power=twpa_power, - bare_frequency=bare_frequency, - ) - else: - return ResonatorTWPAPowerResults( - twpa_power=twpa_power, - frequency=frequency, - ) - - -def _plot(data: ResonatorTWPAPowerData, fit: ResonatorTWPAPowerResults, target): - """Plotting for ResonatorTWPAPower.""" - - figures = [] - fitting_report = "" - fig = make_subplots( - rows=1, - cols=2, - horizontal_spacing=0.1, - vertical_spacing=0.2, - subplot_titles=( - "Signal [a.u.]", - "Phase [rad]", - ), - ) - - fitting_report = "" - qubit_data = data[target] - frequencies = qubit_data.freq * HZ_TO_GHZ - powers = qubit_data.twpa_pow - - fig.add_trace( - go.Heatmap( - x=frequencies, - y=powers, - z=qubit_data.signal, - colorbar_x=0.46, - ), - row=1, - col=1, - ) - fig.update_xaxes(title_text="Frequency [GHz]", row=1, col=1) - fig.update_yaxes(title_text="TWPA Power [dBm]", row=1, col=1) - fig.add_trace( - go.Heatmap( - x=frequencies, - y=powers, - z=qubit_data.phase, - colorbar_x=1.01, - ), - row=1, - col=2, - ) - fig.update_xaxes(title_text="Frequency [GHz]", row=1, col=2) - fig.update_yaxes(title_text="TWPA Power [dBm]", row=1, col=2) - - if fit is not None: - label_1 = "TWPA Power" - twpa_power = np.round(fit.twpa_power[target]) - if target in fit.bare_frequency: - label_2 = "High Power Resonator Frequency [Hz]" - resonator_frequency = np.round(fit.bare_frequency[target]) - else: - label_2 = "Low Power Resonator Frequency [Hz]" - resonator_frequency = np.round(fit.frequency[target]) - - summary = table_dict( - target, - [ - label_2, - label_1, - ], - [ - resonator_frequency, - twpa_power, - ], - ) - - fitting_report = table_html(summary) - - fig.update_layout( - showlegend=False, - ) - - figures.append(fig) - - return figures, fitting_report - - -twpa_power_snr = Routine(_acquisition, _fit, _plot) -"""Resonator TWPA Power Routine object.""" diff --git a/src/qibocal/protocols/resonator_punchout.py b/src/qibocal/protocols/resonator_punchout.py index 3580ee954..771913a0f 100644 --- a/src/qibocal/protocols/resonator_punchout.py +++ b/src/qibocal/protocols/resonator_punchout.py @@ -5,14 +5,12 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, PulseSequence, Sweeper from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.result import magnitude, phase from .utils import HZ_TO_GHZ, fit_punchout, norm, table_dict, table_html @@ -25,11 +23,11 @@ class ResonatorPunchoutParameters(Parameters): """Width for frequency sweep relative to the readout frequency [Hz].""" freq_step: int """Frequency step for sweep [Hz].""" - min_amp_factor: float + min_amp: float """Minimum amplitude multiplicative factor.""" - max_amp_factor: float + max_amp: float """Maximum amplitude multiplicative factor.""" - step_amp_factor: float + step_amp: float """Step amplitude multiplicative factor.""" amplitude: float = None """Initial readout amplitude.""" @@ -66,7 +64,7 @@ class ResonatorPunchoutData(Data): resonator_type: str """Resonator type.""" - amplitudes: dict[QubitId, float] + amplitudes: dict[QubitId, float] = field(default_factory=dict) """Amplitudes provided by the user.""" data: dict[QubitId, npt.NDArray[ResPunchoutType]] = field(default_factory=dict) """Raw data acquired.""" @@ -85,47 +83,44 @@ def register_qubit(self, qubit, freq, amp, signal, phase): def _acquisition( params: ResonatorPunchoutParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> ResonatorPunchoutData: """Data acquisition for Punchout over amplitude.""" # create a sequence of pulses for the experiment: # MZ - # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel - sequence = PulseSequence() - - ro_pulses = {} - amplitudes = {} - for qubit in targets: - ro_pulses[qubit] = platform.create_qubit_readout_pulse(qubit, start=0) - if params.amplitude is not None: - ro_pulses[qubit].amplitude = params.amplitude - - amplitudes[qubit] = ro_pulses[qubit].amplitude - sequence.add(ro_pulses[qubit]) - # define the parameters to sweep and their range: # resonator frequency delta_frequency_range = np.arange( -params.freq_width / 2, params.freq_width / 2, params.freq_step ) - freq_sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - [ro_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) - # amplitude - amplitude_range = np.arange( - params.min_amp_factor, params.max_amp_factor, params.step_amp_factor - ) + # taking advantage of multiplexing, apply the same set of gates to all qubits in parallel + ro_pulses = {} + amplitudes = {} + freq_sweepers = {} + sequence = PulseSequence() + for qubit in targets: + natives = platform.natives.single_qubit[qubit] + ro_channel, ro_pulse = natives.MZ()[0] + + ro_pulses[qubit] = ro_pulse + amplitudes[qubit] = ro_pulse.probe.amplitude + sequence.append((ro_channel, ro_pulse)) + + probe = platform.qubits[qubit].probe + f0 = platform.config(probe).frequency + freq_sweepers[qubit] = Sweeper( + parameter=Parameter.frequency, + values=f0 + delta_frequency_range, + channels=[probe], + ) + amp_sweeper = Sweeper( - Parameter.amplitude, - amplitude_range, - [ro_pulses[qubit] for qubit in targets], - type=SweeperType.FACTOR, + parameter=Parameter.amplitude, + range=(params.min_amp, params.max_amp, params.step_amp), + pulses=[ro_pulses[qubit] for qubit in targets], ) data = ResonatorPunchoutData( @@ -133,16 +128,13 @@ def _acquisition( resonator_type=platform.resonator_type, ) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - amp_sweeper, - freq_sweeper, + results = platform.execute( + [sequence], + [[amp_sweeper], [freq_sweepers[q] for q in targets]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, ) # retrieve the results for every qubit @@ -159,7 +151,7 @@ def _acquisition( signal=result.magnitude, phase=phase, freq=delta_frequency_range + ro_pulse.frequency, - amp=amplitude_range * amplitudes[qubit], + amp=amp_sweeper.values, ) return data @@ -267,9 +259,14 @@ def _plot( return figures, fitting_report -def _update(results: ResonatorPunchoutResults, platform: Platform, target: QubitId): +def _update( + results: ResonatorPunchoutResults, platform: CalibrationPlatform, target: QubitId +): update.readout_frequency(results.readout_frequency[target], platform, target) update.bare_resonator_frequency(results.bare_frequency[target], platform, target) + update.dressed_resonator_frequency( + results.readout_frequency[target], platform, target + ) update.readout_amplitude(results.readout_amplitude[target], platform, target) diff --git a/src/qibocal/protocols/resonator_spectroscopy.py b/src/qibocal/protocols/resonator_spectroscopy.py index 56124ac45..752d2c8aa 100644 --- a/src/qibocal/protocols/resonator_spectroscopy.py +++ b/src/qibocal/protocols/resonator_spectroscopy.py @@ -5,13 +5,13 @@ import numpy as np import numpy.typing as npt from _collections_abc import Callable -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, PulseSequence, Sweeper from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.result import magnitude, phase +from qibocal.update import replace from .utils import ( PowerLevel, @@ -95,9 +95,6 @@ class ResonatorSpectroscopyParameters(Parameters): amplitude: Optional[float] = None """Readout amplitude (optional). If defined, same amplitude will be used in all qubits. Otherwise the default amplitude defined on the platform runcard will be used""" - attenuation: Optional[int] = None - """Readout attenuation (optional). If defined, same attenuation will be used in all qubits. - Otherwise the default attenuation defined on the platform runcard will be used""" hardware_average: bool = True """By default hardware average will be performed.""" phase_delay: float = None @@ -131,10 +128,6 @@ class ResonatorSpectroscopyResults(Results): default_factory=dict, ) """Readout amplitude for each qubit.""" - attenuation: Optional[dict[QubitId, int]] = field( - default_factory=dict, - ) - """Readout attenuation [dB] for each qubit.""" def __contains__(self, key: QubitId): return all( @@ -162,8 +155,6 @@ class ResonatorSpectroscopyData(Data): """Raw data acquired.""" power_level: Optional[PowerLevel] = None """Power regime of the resonator.""" - attenuations: Optional[dict[QubitId, int]] = field(default_factory=dict) - """Readout attenuation [dB] for each qubit""" @classmethod def load(cls, path): @@ -175,7 +166,9 @@ def load(cls, path): def _acquisition( - params: ResonatorSpectroscopyParameters, platform: Platform, targets: list[QubitId] + params: ResonatorSpectroscopyParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> ResonatorSpectroscopyData: """Data acquisition for resonator spectroscopy.""" # create a sequence of pulses for the experiment: @@ -185,73 +178,67 @@ def _acquisition( sequence = PulseSequence() ro_pulses = {} amplitudes = {} - attenuations = {} - for qubit in targets: - ro_pulses[qubit] = platform.create_qubit_readout_pulse(qubit, start=0) + for q in targets: + natives = platform.natives.single_qubit[q] + channel, pulse = natives.MZ()[0] if params.amplitude is not None: - ro_pulses[qubit].amplitude = params.amplitude - - amplitudes[qubit] = ro_pulses[qubit].amplitude + probe = replace(pulse.probe, amplitude=params.amplitude) + pulse = replace(pulse, probe=probe) - if params.attenuation is not None: - platform.qubits[qubit].readout.attenuation = params.attenuation + amplitudes[q] = pulse.probe.amplitude - try: - attenuation = platform.qubits[qubit].readout.attenuation - except AttributeError: - attenuation = None - - attenuations[qubit] = attenuation - sequence.add(ro_pulses[qubit]) + ro_pulses[q] = pulse + sequence.append((channel, pulse)) # define the parameter to sweep and its range: delta_frequency_range = np.arange( -params.freq_width / 2, params.freq_width / 2, params.freq_step ) - sweeper = Sweeper( - Parameter.frequency, - delta_frequency_range, - pulses=[ro_pulses[qubit] for qubit in targets], - type=SweeperType.OFFSET, - ) + sweepers = [ + Sweeper( + parameter=Parameter.frequency, + values=platform.config(platform.qubits[q].probe).frequency + + delta_frequency_range, + channels=[platform.qubits[q].probe], + ) + for q in targets + ] + data = ResonatorSpectroscopyData( resonator_type=platform.resonator_type, power_level=params.power_level, amplitudes=amplitudes, - attenuations=attenuations, fit_function=params.fit_function, phase_sign=params.phase_sign, ) - results = platform.sweep( - sequence, - params.execution_parameters, - sweeper, + results = platform.execute( + [sequence], + [sweepers], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.SINGLESHOT, ) # retrieve the results for every qubit - for qubit in targets: - result = results[ro_pulses[qubit].serial] + for q in targets: + result = results[ro_pulses[q].id] # store the results - frequency =delta_frequency_range + ro_pulses[qubit].frequency - - if params.phase_delay is not None: - phase = result.average.phase - phase = np.unwrap(phase)-(frequency-frequency[0])*1e-6*params.phase_delay - else: - phase = result.average.phase - + ro_frequency = platform.config(platform.qubits[q].probe).frequency + signal = magnitude(result) + phase_ = phase(result) data.register_qubit( ResSpecType, - (qubit), + (q), dict( - signal=result.average.magnitude, - phase=phase, - freq=delta_frequency_range + ro_pulses[qubit].frequency, - error_signal=result.average.std, - error_phase=result.phase_std, + signal=signal.mean(axis=0), + phase=phase_.mean(axis=0), + freq=delta_frequency_range + ro_frequency, + error_signal=np.std(signal, axis=0, ddof=1) / np.sqrt(signal.shape[0]), + error_phase=np.std(phase_, axis=0, ddof=1) / np.sqrt(phase_.shape[0]), ), ) return data @@ -313,7 +300,6 @@ def _fit( error_fit_pars=error_fit_pars, chi2_reduced=chi2, amplitude=data.amplitudes, - attenuation=data.attenuations, ) return ResonatorSpectroscopyResults( frequency=frequency, @@ -321,7 +307,6 @@ def _fit( error_fit_pars=error_fit_pars, chi2_reduced=chi2, amplitude=data.amplitudes, - attenuation=data.attenuations, ) @@ -332,15 +317,14 @@ def _plot( return FITS[data.fit_function].plot(data, target, fit) -def _update(results: ResonatorSpectroscopyResults, platform: Platform, target: QubitId): +def _update( + results: ResonatorSpectroscopyResults, + platform: CalibrationPlatform, + target: QubitId, +): update.readout_frequency(results.frequency[target], platform, target) - - # if this condition is satifisfied means that we are in the low power regime - # therefore we update also the readout amplitude if len(results.bare_frequency) == 0: update.readout_amplitude(results.amplitude[target], platform, target) - if results.attenuation[target] is not None: - update.readout_attenuation(results.attenuation[target], platform, target) else: update.bare_resonator_frequency( results.bare_frequency[target], platform, target diff --git a/src/qibocal/protocols/signal_experiments/calibrate_state_discrimination.py b/src/qibocal/protocols/signal_experiments/calibrate_state_discrimination.py index 89c02242d..28dba9c42 100644 --- a/src/qibocal/protocols/signal_experiments/calibrate_state_discrimination.py +++ b/src/qibocal/protocols/signal_experiments/calibrate_state_discrimination.py @@ -5,13 +5,11 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, AveragingMode, PulseSequence from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform SAMPLES_FACTOR = 16 @@ -25,6 +23,7 @@ class CalibrateStateDiscriminationParameters(Parameters): """Number of shots.""" relaxation_time: Optional[int] = None """Relaxation time (ns).""" + unrolling: Optional[bool] = False CalibrateStateDiscriminationResType = np.dtype( @@ -49,8 +48,6 @@ class CalibrateStateDiscriminationResults(Results): [ ("i", np.float64), ("q", np.float64), - ("signal", np.float64), - ("phase", np.float64), ] ) """Custom dtype for CalibrateStateDiscrimination.""" @@ -69,7 +66,7 @@ class CalibrateStateDiscriminationData(Data): def _acquisition( params: CalibrateStateDiscriminationParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitId], ) -> CalibrateStateDiscriminationData: r""" @@ -79,67 +76,58 @@ def _acquisition( Args: params (CalibrateStateDiscriminationParameters): experiment's parameters - platform (Platform): Qibolab platform object + platform (CalibrationPlatform): Qibolab platform object qubits (dict): list of target qubits to perform the action """ - # create 2 sequences of pulses for the experiment: - # sequence_0: I - MZ - # sequence_1: RX - MZ - - data = CalibrateStateDiscriminationData(resonator_type=platform.resonator_type) - - # TODO: test if qibolab supports multiplex with raw acquisition - for qubit in targets: - sequence_0 = PulseSequence() - sequence_1 = PulseSequence() - sequence_1.add(platform.create_RX_pulse(qubit, start=0)) - - sequence_0.add( - platform.create_qubit_readout_pulse(qubit, start=sequence_0.finish) - ) - sequence_1.add( - platform.create_qubit_readout_pulse(qubit, start=sequence_1.finish) - ) + native = platform.natives.single_qubit + sequences, all_ro_pulses = [], [] + for state in [0, 1]: + ro_pulses = {} + sequence = PulseSequence() + for q in targets: + ro_sequence = native[q].MZ() + ro_pulses[q] = ro_sequence[0][1].id + sequence += ro_sequence + + if state == 1: + rx_sequence = PulseSequence() + for q in targets: + rx_sequence += native[q].RX() + sequence = rx_sequence | sequence + + sequences.append(sequence) + all_ro_pulses.append(ro_pulses) + + options = dict( + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.RAW, + averaging_mode=AveragingMode.CYCLIC, + ) - results_0 = platform.execute_pulse_sequence( - sequence_0, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.RAW, - averaging_mode=AveragingMode.CYCLIC, - ), - ) + if params.unrolling: + results = platform.execute(sequences, **options) + else: + results = {} + for sequence in sequences: + results.update(platform.execute([sequence], **options)) - results_1 = platform.execute_pulse_sequence( - sequence_1, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.RAW, - averaging_mode=AveragingMode.CYCLIC, - ), - ) + data = CalibrateStateDiscriminationData(resonator_type=platform.resonator_type) - for i, experiment in enumerate( - zip([sequence_0, sequence_1], [results_0, results_1]) - ): - sequence, results = experiment - result = results[sequence.ro_pulses[0].serial] - # store the results + for state, ro_pulses in zip([0, 1], all_ro_pulses): + for qubit in targets: + serial = ro_pulses[qubit] + result = results[serial] data.register_qubit( CalibrateStateDiscriminationType, - (qubit, i), + (qubit, state), dict( - signal=result.magnitude, - phase=result.phase, - i=result.voltage_i, - q=result.voltage_q, + i=result[..., 0], + q=result[..., 1], ), ) - return data @@ -200,21 +188,48 @@ def _plot( fig.add_trace( go.Scatter( - x=np.arange(len(fit.data[target])), - y=np.abs(fit.data[target]), + x=data[target, 0].i, + y=data[target, 0].q, opacity=1, - name="kernel state 0", + name="State 0", showlegend=True, - legendgroup="kernel state 0", + legendgroup="State 0", ), row=1, col=1, ) + fig.add_trace( + go.Scatter( + x=data[target, 1].i, + y=data[target, 1].q, + opacity=1, + name="State 1", + showlegend=True, + legendgroup="State 1", + ), + row=1, + col=1, + ) + + # TODO: check which plot we prefer + # fig.add_trace( + # go.Scatter( + # x=np.arange(len(fit.data[target])), + # y=np.abs(fit.data[target]), + # opacity=1, + # name="kernel state 0", + # showlegend=True, + # legendgroup="kernel state 0", + # ), + # row=1, + # col=1, + # ) + fig.update_layout( showlegend=True, - xaxis_title="Kernel samples", - yaxis_title="Kernel absolute value", + xaxis_title="I", + yaxis_title="Q", ) figures.append(fig) @@ -223,7 +238,9 @@ def _plot( def _update( - results: CalibrateStateDiscriminationResults, platform: Platform, qubit: QubitId + results: CalibrateStateDiscriminationResults, + platform: CalibrationPlatform, + qubit: QubitId, ): update.kernel(results.data[qubit], platform, qubit) diff --git a/src/qibocal/protocols/signal_experiments/time_of_flight_readout.py b/src/qibocal/protocols/signal_experiments/time_of_flight_readout.py index 94356618a..351b5c103 100644 --- a/src/qibocal/protocols/signal_experiments/time_of_flight_readout.py +++ b/src/qibocal/protocols/signal_experiments/time_of_flight_readout.py @@ -4,13 +4,13 @@ import numpy as np import numpy.typing as npt import plotly.graph_objects as go -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitId +from qibolab import AcquisitionType, AveragingMode, PulseSequence -from qibocal.auto.operation import Data, Parameters, Results, Routine -from qibocal.protocols.utils import S_TO_NS, table_dict, table_html +from qibocal.auto.operation import Data, Parameters, QubitId, Results, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.protocols.utils import table_dict, table_html +from qibocal.result import magnitude +from qibocal.update import replace @dataclass @@ -46,27 +46,29 @@ class TimeOfFlightReadoutData(Data): def _acquisition( - params: TimeOfFlightReadoutParameters, platform: Platform, targets: list[QubitId] + params: TimeOfFlightReadoutParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> TimeOfFlightReadoutData: """Data acquisition for time of flight experiment.""" sequence = PulseSequence() ro_pulses = {} + native = platform.natives.single_qubit for qubit in targets: - ro_pulses[qubit] = platform.create_qubit_readout_pulse(qubit, start=0) + ro_channel, ro_pulse = native[qubit].MZ()[0] if params.readout_amplitude is not None: - ro_pulses[qubit].amplitude = params.readout_amplitude - sequence.add(ro_pulses[qubit]) - - results = platform.execute_pulse_sequence( - sequence, - options=ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.RAW, - averaging_mode=AveragingMode.CYCLIC, - ), + ro_pulse = replace(ro_pulse, amplitude=params.readout_amplitude) + ro_pulses[qubit] = ro_pulse + sequence.append((ro_channel, ro_pulse)) + + results = platform.execute( + [sequence], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.RAW, + averaging_mode=AveragingMode.CYCLIC, ) data = TimeOfFlightReadoutData( @@ -75,7 +77,7 @@ def _acquisition( # retrieve and store the results for every qubit for qubit in targets: - samples = results[ro_pulses[qubit].serial].magnitude + samples = magnitude(results[ro_pulses[qubit].id]) # store the results data.register_qubit(TimeOfFlightReadoutType, (qubit), dict(samples=samples)) return data @@ -141,9 +143,7 @@ def _plot( line_color="grey", ) fitting_report = table_html( - table_dict( - target, "Time of flights [ns]", fit.fitted_parameters[target] * S_TO_NS - ) + table_dict(target, "Time of flights [ns]", fit.fitted_parameters[target]) ) fig.update_layout( showlegend=True, diff --git a/src/qibocal/protocols/state_tomography.py b/src/qibocal/protocols/state_tomography.py index 7724a2c08..ab48d4d69 100644 --- a/src/qibocal/protocols/state_tomography.py +++ b/src/qibocal/protocols/state_tomography.py @@ -10,11 +10,10 @@ from qibo import Circuit, gates from qibo.backends import NumpyBackend, construct_backend, matrices from qibo.quantum_info import fidelity, partial_trace -from qibolab.platform import Platform -from qibolab.qubits import QubitId -from qibocal.auto.operation import DATAFILE, Data, Parameters, Results, Routine +from qibocal.auto.operation import DATAFILE, Data, Parameters, QubitId, Results, Routine from qibocal.auto.transpile import dummy_transpiler, execute_transpiled_circuit +from qibocal.calibration import CalibrationPlatform from .utils import table_dict, table_html @@ -96,7 +95,9 @@ class StateTomographyResults(Results): def _acquisition( - params: StateTomographyParameters, platform: Platform, targets: list[QubitId] + params: StateTomographyParameters, + platform: CalibrationPlatform, + targets: list[QubitId], ) -> StateTomographyData: """Acquisition protocol for single qubit state tomography experiment.""" if params.circuit is None: diff --git a/src/qibocal/protocols/two_qubit_interaction/__init__.py b/src/qibocal/protocols/two_qubit_interaction/__init__.py index 37870c41d..723b4d067 100644 --- a/src/qibocal/protocols/two_qubit_interaction/__init__.py +++ b/src/qibocal/protocols/two_qubit_interaction/__init__.py @@ -14,4 +14,3 @@ from .mermin import mermin from .optimize import optimize_two_qubit_gate from .virtual_z_phases import correct_virtual_z_phases -from .virtual_z_phases_signal import correct_virtual_z_phases_signal diff --git a/src/qibocal/protocols/two_qubit_interaction/chevron/chevron.py b/src/qibocal/protocols/two_qubit_interaction/chevron/chevron.py index 59aa00967..bc305b631 100644 --- a/src/qibocal/protocols/two_qubit_interaction/chevron/chevron.py +++ b/src/qibocal/protocols/two_qubit_interaction/chevron/chevron.py @@ -1,23 +1,21 @@ """SWAP experiment for two qubit gates, chevron plot.""" from dataclasses import dataclass, field -from typing import Optional +from typing import Literal, Optional import numpy as np import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitPairId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper from scipy.optimize import curve_fit -from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import Data, Parameters, QubitPairId, Results, Routine +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import table_dict, table_html +from .... import update from ..utils import fit_flux_amplitude, order_pair from .utils import COLORAXIS, chevron_fit, chevron_sequence @@ -26,11 +24,11 @@ class ChevronParameters(Parameters): """CzFluxTime runcard inputs.""" - amplitude_min_factor: float + amplitude_min: float """Amplitude minimum.""" - amplitude_max_factor: float + amplitude_max: float """Amplitude maximum.""" - amplitude_step_factor: float + amplitude_step: float """Amplitude step.""" duration_min: float """Duration minimum.""" @@ -42,28 +40,8 @@ class ChevronParameters(Parameters): """Time delay between flux pulses and readout.""" parking: bool = True """Wether to park non interacting qubits or not.""" - native: str = "CZ" - """Two qubit interaction to be calibrated. - - iSWAP and CZ are the possible options. - - """ - - @property - def amplitude_range(self): - return np.arange( - self.amplitude_min_factor, - self.amplitude_max_factor, - self.amplitude_step_factor, - ) - - @property - def duration_range(self): - return np.arange( - self.duration_min, - self.duration_max, - self.duration_step, - ) + native: Literal["CZ", "iSWAP"] = "CZ" + """Two qubit interaction to be calibrated.""" @dataclass @@ -74,12 +52,8 @@ class ChevronResults(Results): """CZ angle.""" duration: dict[QubitPairId, int] """Virtual Z phase correction.""" - native: str = "CZ" - """Two qubit interaction to be calibrated. - - iSWAP and CZ are the possible options. - - """ + native: Literal["CZ", "iSWAP"] = "CZ" + """Two qubit interaction to be calibrated.""" ChevronType = np.dtype( @@ -105,8 +79,6 @@ class ChevronData(Data): iSWAP and CZ are the possible options. """ - sweetspot: dict[QubitPairId, float] = field(default_factory=dict) - """Sweetspot value for high frequency qubit.""" data: dict[QubitPairId, npt.NDArray[ChevronType]] = field(default_factory=dict) label: Optional[str] = None @@ -140,14 +112,14 @@ def high_frequency(self, pair): def _aquisition( params: ChevronParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitPairId], ) -> ChevronData: r"""Perform an CZ experiment between pairs of qubits by changing its frequency. Args: - platform: Platform to use. + platform: CalibrationPlatform to use. params: Experiment parameters. targets (list): List of pairs to use sequentially. @@ -159,51 +131,51 @@ def _aquisition( data = ChevronData(native=params.native) for pair in targets: # order the qubits so that the low frequency one is the first - sequence = chevron_sequence( + ordered_pair = order_pair(pair, platform) + sequence, flux_pulse, parking_pulses, delays = chevron_sequence( platform=platform, - pair=pair, + ordered_pair=ordered_pair, duration_max=params.duration_max, parking=params.parking, dt=params.dt, native=params.native, ) - ordered_pair = order_pair(pair, platform) - # TODO: move in function to avoid code duplications sweeper_amplitude = Sweeper( - Parameter.amplitude, - params.amplitude_range, - pulses=[sequence.get_qubit_pulses(ordered_pair[1]).qf_pulses[0]], - type=SweeperType.FACTOR, - ) - data.native_amplitude[ordered_pair] = ( - sequence.get_qubit_pulses(ordered_pair[1]).qf_pulses[0].amplitude + parameter=Parameter.amplitude, + range=(params.amplitude_min, params.amplitude_max, params.amplitude_step), + pulses=[flux_pulse], ) - data.sweetspot[ordered_pair] = platform.qubits[ordered_pair[1]].sweetspot sweeper_duration = Sweeper( - Parameter.duration, - params.duration_range, - pulses=[sequence.get_qubit_pulses(ordered_pair[1]).qf_pulses[0]], - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + range=(params.duration_min, params.duration_max, params.duration_step), + pulses=[flux_pulse] + delays + parking_pulses, ) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper_duration, - sweeper_amplitude, + ro_high = list(sequence.channel(platform.qubits[ordered_pair[1]].acquisition))[ + -1 + ] + ro_low = list(sequence.channel(platform.qubits[ordered_pair[0]].acquisition))[ + -1 + ] + + data.native_amplitude[ordered_pair] = flux_pulse.amplitude + + results = platform.execute( + [sequence], + [[sweeper_duration], [sweeper_amplitude]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.CYCLIC, ) + data.register_qubit( ordered_pair[0], ordered_pair[1], - params.duration_range, - params.amplitude_range * data.native_amplitude[ordered_pair], - results[ordered_pair[0]].probability(state=1), - results[ordered_pair[1]].probability(state=1), + sweeper_duration.values, + sweeper_amplitude.values, + results[ro_low.id], + results[ro_high.id], ) return data @@ -323,11 +295,10 @@ def _plot(data: ChevronData, fit: ChevronResults, target: QubitPairId): fitting_report = table_html( table_dict( target[1], - [f"{fit.native} amplitude", f"{fit.native} duration", "Bias point"], + [f"{fit.native} amplitude", f"{fit.native} duration"], [ fit.amplitude[target], fit.duration[target], - fit.amplitude[target] + data.sweetspot[target], ], ) ) @@ -335,12 +306,13 @@ def _plot(data: ChevronData, fit: ChevronResults, target: QubitPairId): return [fig], fitting_report -def _update(results: ChevronResults, platform: Platform, target: QubitPairId): +def _update( + results: ChevronResults, platform: CalibrationPlatform, target: QubitPairId +): if isinstance(target, list): target = tuple(target) - if target not in results.duration: - target = (target[1], target[0]) + target = target[::-1] if target not in results.duration else target getattr(update, f"{results.native}_duration")( results.duration[target], platform, target diff --git a/src/qibocal/protocols/two_qubit_interaction/chevron/chevron_signal.py b/src/qibocal/protocols/two_qubit_interaction/chevron/chevron_signal.py index ccd21bdc1..003231460 100644 --- a/src/qibocal/protocols/two_qubit_interaction/chevron/chevron_signal.py +++ b/src/qibocal/protocols/two_qubit_interaction/chevron/chevron_signal.py @@ -4,12 +4,11 @@ import numpy as np import numpy.typing as npt -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitPairId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper -from qibocal.auto.operation import Routine +from qibocal.auto.operation import QubitPairId, Routine +from qibocal.calibration import CalibrationPlatform +from qibocal.result import magnitude from ..utils import order_pair from .chevron import ( @@ -74,7 +73,7 @@ def high_frequency(self, pair): def _aquisition( params: ChevronSignalParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitPairId], ) -> ChevronSignalData: r""" @@ -82,7 +81,7 @@ def _aquisition( Args: params: Experiment parameters. - platform: Platform to use. + platform: CalibrationPlatform to use. targets (list): List of pairs to use sequentially. Returns: @@ -94,50 +93,50 @@ def _aquisition( for pair in targets: # order the qubits so that the low frequency one is the first ordered_pair = order_pair(pair, platform) - sequence = chevron_sequence( + sequence, flux_pulse, parking_pulses, delays = chevron_sequence( platform=platform, - pair=pair, + ordered_pair=ordered_pair, duration_max=params.duration_max, parking=params.parking, dt=params.dt, native=params.native, ) - data.native_amplitude[ordered_pair] = ( - sequence.get_qubit_pulses(ordered_pair[1]).qf_pulses[0].amplitude - ) - data.sweetspot[ordered_pair] = platform.qubits[ordered_pair[1]].sweetspot - sweeper_amplitude = Sweeper( - Parameter.amplitude, - params.amplitude_range, - pulses=[sequence.get_qubit_pulses(ordered_pair[1]).qf_pulses[0]], - type=SweeperType.FACTOR, + parameter=Parameter.amplitude, + range=(params.amplitude_min, params.amplitude_max, params.amplitude_step), + pulses=[flux_pulse], ) sweeper_duration = Sweeper( - Parameter.duration, - params.duration_range, - pulses=[sequence.get_qubit_pulses(ordered_pair[1]).qf_pulses[0]], - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + range=(params.duration_min, params.duration_max, params.duration_step), + pulses=[flux_pulse] + delays + parking_pulses, ) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper_duration, - sweeper_amplitude, + + ro_high = list(sequence.channel(platform.qubits[ordered_pair[1]].acquisition))[ + -1 + ] + ro_low = list(sequence.channel(platform.qubits[ordered_pair[0]].acquisition))[ + -1 + ] + + data.native_amplitude[ordered_pair] = flux_pulse.amplitude + + results = platform.execute( + [sequence], + [[sweeper_duration], [sweeper_amplitude]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.INTEGRATION, + averaging_mode=AveragingMode.CYCLIC, ) data.register_qubit( ordered_pair[0], ordered_pair[1], - params.duration_range, - params.amplitude_range * data.native_amplitude[ordered_pair], - results[ordered_pair[0]].magnitude, - results[ordered_pair[1]].magnitude, + sweeper_duration.values, + sweeper_amplitude.values, + magnitude(results[ro_low.id]), + magnitude(results[ro_high.id]), ) return data diff --git a/src/qibocal/protocols/two_qubit_interaction/chevron/utils.py b/src/qibocal/protocols/two_qubit_interaction/chevron/utils.py index 40ea08213..973a64a1a 100644 --- a/src/qibocal/protocols/two_qubit_interaction/chevron/utils.py +++ b/src/qibocal/protocols/two_qubit_interaction/chevron/utils.py @@ -1,9 +1,11 @@ +from typing import Optional + import numpy as np -from qibolab.platform import Platform -from qibolab.pulses import PulseSequence -from qibolab.qubits import QubitPairId +from qibolab import Delay, PulseSequence, VirtualZ -from ..utils import order_pair +from qibocal.auto.operation import QubitPairId +from qibocal.calibration import CalibrationPlatform +from qibocal.update import replace COLORAXIS = ["coloraxis2", "coloraxis1"] @@ -14,68 +16,75 @@ def chevron_sequence( - platform: Platform, - pair: QubitPairId, - duration_max: int, + platform: CalibrationPlatform, + ordered_pair: QubitPairId, + duration_max: Optional[int] = None, parking: bool = False, native: str = "CZ", dt: int = 0, ): """Chevron pulse sequence.""" - sequence = PulseSequence() - ordered_pair = order_pair(pair, platform) - # initialize in system in 11 state - + low_natives = platform.natives.single_qubit[ordered_pair[0]] + high_natives = platform.natives.single_qubit[ordered_pair[1]] if native == "CZ": - initialize_lowfreq = platform.create_RX_pulse( - ordered_pair[0], start=0, relative_phase=0 - ) - sequence.add(initialize_lowfreq) - - initialize_highfreq = platform.create_RX_pulse( - ordered_pair[1], start=0, relative_phase=0 - ) - sequence.add(initialize_highfreq) - - flux_sequence, _ = getattr(platform, f"create_{native}_pulse_sequence")( - qubits=(ordered_pair[1], ordered_pair[0]), - start=initialize_highfreq.finish, - ) + sequence += low_natives.RX() + sequence += high_natives.RX() - sequence.add(flux_sequence.get_qubit_pulses(ordered_pair[0])) - sequence.add(flux_sequence.get_qubit_pulses(ordered_pair[1])) + drive_duration = sequence.duration + raw_flux_sequence = getattr(platform.natives.two_qubit[ordered_pair], native)() + flux_channel, flux_pulse = [ + (ch, pulse) + for ch, pulse in raw_flux_sequence + if ch == platform.qubits[ordered_pair[1]].flux + ][0] - delay_measurement = duration_max + if duration_max is not None: + flux_pulse = replace(flux_pulse, duration=duration_max) - if platform.couplers: - coupler_pulse = flux_sequence.coupler_pulses( - platform.pairs[tuple(ordered_pair)].coupler.name - ) - sequence.add(coupler_pulse) - delay_measurement = max(duration_max, coupler_pulse.duration) + sequence.append((flux_channel, Delay(duration=drive_duration))) + sequence.append((flux_channel, flux_pulse)) + parking_pulses = [] if parking: - for pulse in flux_sequence: - if pulse.qubit not in ordered_pair: - pulse.start = COUPLER_PULSE_START - pulse.duration = COUPLER_PULSE_DURATION - sequence.add(pulse) + for ch, pulse in raw_flux_sequence: + if not isinstance(pulse, VirtualZ) and ch != flux_channel: + sequence.append((ch, Delay(duration=drive_duration))) + sequence.append((ch, pulse)) + parking_pulses.append(pulse) - # add readout - measure_lowfreq = platform.create_qubit_readout_pulse( - ordered_pair[0], - start=initialize_highfreq.finish + delay_measurement + dt, - ) - measure_highfreq = platform.create_qubit_readout_pulse( - ordered_pair[1], - start=initialize_highfreq.finish + delay_measurement + dt, + flux_duration = max(flux_pulse.duration, raw_flux_sequence.duration) + + ro_low_channel, ro_high_channel = ( + platform.qubits[ordered_pair[0]].acquisition, + platform.qubits[ordered_pair[1]].acquisition, ) + ro_low_delay = ro_high_delay = drive_delay = Delay(duration=flux_duration) + dt_delay = Delay(duration=dt) + drive_channel, second_rx = high_natives.RX()[0] + sequence += [ + (ro_low_channel, Delay(duration=drive_duration)), + (ro_high_channel, Delay(duration=drive_duration)), + (ro_low_channel, ro_low_delay), + (ro_high_channel, ro_high_delay), + (ro_low_channel, dt_delay), + (ro_high_channel, dt_delay), + (drive_channel, drive_delay), + (drive_channel, dt_delay), + (ro_low_channel, Delay(duration=second_rx.duration)), + (ro_high_channel, Delay(duration=second_rx.duration)), + (drive_channel, second_rx), + ] - sequence.add(measure_lowfreq) - sequence.add(measure_highfreq) + # add readout + sequence += low_natives.MZ() + high_natives.MZ() - return sequence + return ( + sequence, + flux_pulse, + parking_pulses, + [ro_low_delay, ro_high_delay, drive_delay], + ) # fitting function for single row in chevron plot (rabi-like curve) diff --git a/src/qibocal/protocols/two_qubit_interaction/chsh/__init__.py b/src/qibocal/protocols/two_qubit_interaction/chsh/__init__.py deleted file mode 100644 index 61fe5789b..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/chsh/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .protocol import chsh_circuits, chsh_pulses diff --git a/src/qibocal/protocols/two_qubit_interaction/chsh/circuits.py b/src/qibocal/protocols/two_qubit_interaction/chsh/circuits.py deleted file mode 100644 index 898ab8536..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/chsh/circuits.py +++ /dev/null @@ -1,95 +0,0 @@ -"""Auxiliary functions to run CHSH using circuits.""" - -import numpy as np -from qibo import gates -from qibo.models import Circuit - -from .utils import READOUT_BASIS - - -def create_bell_circuit(theta=np.pi / 4, bell_state=0): - """Creates the circuit to generate the bell states and with a theta-measurement - bell_state chooses the initial bell state for the test: - 0 -> |00>+|11> - 1 -> |00>-|11> - 2 -> |10>-|01> - 3 -> |10>+|01> - Native defaults to only using GPI2 and GPI gates. - """ - p = [0, 0] - c = Circuit(2) - c.add(gates.H(0)) - c.add(gates.H(1)) - c.add(gates.CZ(0, 1)) - c.add(gates.H(1)) - if bell_state == 1: - c.add(gates.Z(0)) - elif bell_state == 2: - c.add(gates.Z(0)) - c.add(gates.X(0)) - elif bell_state == 3: - c.add(gates.X(0)) - - c.add(gates.RY(0, theta)) - return c, p - - -def create_bell_circuit_native(theta=np.pi / 4, bell_state=0): - """Creates the circuit to generate the bell states and with a theta-measurement - bell_state chooses the initial bell state for the test: - 0 -> |00>+|11> - 1 -> |00>-|11> - 2 -> |10>-|01> - 3 -> |10>+|01> - Native defaults to only using GPI2 and GPI gates. - """ - - c = Circuit(2) - p = [0, 0] - c.add(gates.GPI2(0, np.pi / 2)) - c.add(gates.GPI2(1, np.pi / 2)) - c.add(gates.CZ(0, 1)) - c.add(gates.GPI2(1, -np.pi / 2)) - if bell_state == 0: - p[0] += np.pi - elif bell_state == 1: - p[0] += 0 - elif bell_state == 2: - p[0] += 0 - c.add(gates.GPI2(0, p[0])) - c.add(gates.GPI2(0, p[0])) - elif bell_state == 3: - p[0] += np.pi - c.add(gates.GPI2(0, p[0])) - c.add(gates.GPI2(0, p[0])) - - c.add(gates.GPI2(0, p[0])) - p[0] += theta - c.add(gates.GPI2(0, p[0] + np.pi)) - - return c, p - - -def create_chsh_circuits( - theta=np.pi / 4, - bell_state=0, - native=True, - readout_basis=READOUT_BASIS, -): - """Creates the circuits needed for the 4 measurement settings for chsh. - Native defaults to only using GPI2 and GPI gates. - rerr adds a readout bitflip error to the simulation. - """ - create_bell = create_bell_circuit_native if native else create_bell_circuit - chsh_circuits = {} - for basis in readout_basis: - c, p = create_bell(theta, bell_state) - for i, base in enumerate(basis): - if base == "X": - if native: - c.add(gates.GPI2(i, p[i] + np.pi / 2)) - else: - c.add(gates.H(i)) - c.add(gates.M(0, 1)) - chsh_circuits[basis] = c - return chsh_circuits diff --git a/src/qibocal/protocols/two_qubit_interaction/chsh/protocol.py b/src/qibocal/protocols/two_qubit_interaction/chsh/protocol.py deleted file mode 100644 index b5beb46c6..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/chsh/protocol.py +++ /dev/null @@ -1,381 +0,0 @@ -"""Protocol for CHSH experiment using both circuits and pulses.""" - -import json -from dataclasses import dataclass, field -from pathlib import Path -from typing import Optional - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from qibo.backends import construct_backend -from qibolab import ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId, QubitPairId - -from qibocal.auto.operation import Data, Parameters, Results, Routine -from qibocal.auto.transpile import dummy_transpiler, execute_transpiled_circuit -from qibocal.config import log - -from ...readout_mitigation_matrix import ( - ReadoutMitigationMatrixParameters as mitigation_params, -) -from ...readout_mitigation_matrix import _acquisition as mitigation_acquisition -from ...readout_mitigation_matrix import _fit as mitigation_fit -from ...utils import calculate_frequencies -from .circuits import create_chsh_circuits -from .pulses import create_chsh_sequences -from .utils import READOUT_BASIS, compute_chsh - -COMPUTATIONAL_BASIS = ["00", "01", "10", "11"] - -CLASSICAL_BOUND = 2 -"""Classical limit of CHSH,""" -QUANTUM_BOUND = 2 * np.sqrt(2) -"""Quantum limit of CHSH.""" - - -MITIGATION_MATRIX_FILE = "mitigation_matrix" -"""File where readout mitigation matrix is stored.""" - - -@dataclass -class CHSHParameters(Parameters): - """CHSH runcard inputs.""" - - bell_states: list - """List with Bell states to compute CHSH. - The following notation it is used: - 0 -> |00>+|11> - 1 -> |00>-|11> - 2 -> |10>-|01> - 3 -> |10>+|01> - """ - ntheta: int - """Number of angles probed linearly between 0 and 2 pi.""" - native: Optional[bool] = False - """If True a circuit will be created using only GPI2 and CZ gates.""" - apply_error_mitigation: Optional[bool] = False - """Error mitigation model""" - - -@dataclass -class CHSHData(Data): - """CHSH Data structure.""" - - bell_states: list - """Bell states list.""" - thetas: list - """Angles probed.""" - data: dict[QubitId, QubitId, int, tuple, str] = field(default_factory=dict) - """Raw data acquired.""" - mitigation_matrix: dict[tuple[QubitId, ...], npt.NDArray] = field( - default_factory=dict - ) - """Mitigation matrix computed using the readout_mitigation_matrix protocol.""" - - def save(self, path: Path): - """Saving data including mitigation matrix.""" - if self.mitigation_matrix: - np.savez( - path / f"{MITIGATION_MATRIX_FILE}.npz", - **{ - json.dumps((control, target)): self.mitigation_matrix[ - control, target - ] - for control, target, _, _, _ in self.data - }, - ) - super().save(path=path) - - @classmethod - def load(cls, path: Path): - """Custom loading to acco modate mitigation matrix""" - instance = super().load(path=path) - # load readout mitigation matrix - mitigation_matrix = super().load_data( - path=path, filename=MITIGATION_MATRIX_FILE - ) - instance.mitigation_matrix = mitigation_matrix - return instance - - def register_basis(self, pair, bell_state, basis, frequencies): - """Store output for single qubit.""" - - # Add zero is state do not appear in state - # could be removed by using high number of shots - for i in COMPUTATIONAL_BASIS: - if i not in frequencies: - frequencies[i] = 0 - - for state, freq in frequencies.items(): - if (pair[0], pair[1], bell_state, basis, state) in self.data: - self.data[pair[0], pair[1], bell_state, basis, state] = np.concatenate( - ( - self.data[pair[0], pair[1], bell_state, basis, state], - np.array([freq]), - ) - ) - else: - self.data[pair[0], pair[1], bell_state, basis, state] = np.array([freq]) - - def merge_frequencies(self, pair, bell_state): - """Merge frequencies with different measurement basis.""" - freqs = [] - bell_data = { - (index[3], index[4]): value - for index, value in self.data.items() - if index[:3] == (pair[0], pair[1], bell_state) - } - - freqs = [] - for i in READOUT_BASIS: - freqs.append( - {state[1]: value for state, value in bell_data.items() if state[0] == i} - ) - - return freqs - - @property - def params(self): - """Convert non-arrays attributes into dict.""" - data_dict = super().params - data_dict.pop("mitigation_matrix") - - return data_dict - - -@dataclass -class CHSHResults(Results): - """CHSH Results class.""" - - chsh: dict[tuple[QubitPairId, int], float] = field(default_factory=dict) - """Raw CHSH value.""" - chsh_mitigated: dict[tuple[QubitPairId, int], float] = field(default_factory=dict) - """Mitigated CHSH value.""" - - def __contains__(self, key: QubitPairId): - """Check if key is in class. - - While key is a QubitPairId both chsh and chsh_mitigated contain - an additional key which represents the basis chosen. - - """ - - return key in [(target, control) for target, control, _ in self.chsh] - - -def _acquisition_pulses( - params: CHSHParameters, - platform: Platform, - targets: list[list[QubitId]], -) -> CHSHData: - r"""Data acquisition for CHSH protocol using pulse sequences.""" - thetas = np.linspace(0, 2 * np.pi, params.ntheta) - data = CHSHData(bell_states=params.bell_states, thetas=thetas.tolist()) - - if params.apply_error_mitigation: - mitigation_data = mitigation_acquisition( - mitigation_params(nshots=params.nshots), platform, targets - ) - mitigation_results = mitigation_fit(mitigation_data) - - platform.connect() - for pair in targets: - if params.apply_error_mitigation: - try: - data.mitigation_matrix[pair] = ( - mitigation_results.readout_mitigation_matrix[pair] - ) - except KeyError: - log.warning( - f"Skipping error mitigation for qubits {pair} due to error." - ) - - for bell_state in params.bell_states: - for theta in thetas: - chsh_sequences = create_chsh_sequences( - platform=platform, - qubits=pair, - theta=theta, - bell_state=bell_state, - ) - for basis, sequence in chsh_sequences.items(): - results = platform.execute_pulse_sequence( - sequence, - ExecutionParameters( - nshots=params.nshots, relaxation_time=params.relaxation_time - ), - ) - frequencies = calculate_frequencies(results, list(pair)) - data.register_basis(pair, bell_state, basis, frequencies) - return data - - -def _acquisition_circuits( - params: CHSHParameters, - platform: Platform, - targets: list[QubitPairId], -) -> CHSHData: - """Data acquisition for CHSH protocol using circuits.""" - thetas = np.linspace(0, 2 * np.pi, params.ntheta) - data = CHSHData( - bell_states=params.bell_states, - thetas=thetas.tolist(), - ) - backend = construct_backend("qibolab", platform=platform) - transpiler = dummy_transpiler(backend) - if params.apply_error_mitigation: - mitigation_data = mitigation_acquisition( - mitigation_params(nshots=params.nshots), platform, targets - ) - mitigation_results = mitigation_fit(mitigation_data) - for pair in targets: - if params.apply_error_mitigation: - try: - data.mitigation_matrix[pair] = ( - mitigation_results.readout_mitigation_matrix[pair] - ) - except KeyError: - log.warning( - f"Skipping error mitigation for qubits {pair} due to error." - ) - for bell_state in params.bell_states: - for theta in thetas: - chsh_circuits = create_chsh_circuits( - bell_state=bell_state, - theta=theta, - native=params.native, - ) - for basis, circuit in chsh_circuits.items(): - _, result = execute_transpiled_circuit( - circuit, - nshots=params.nshots, - transpiler=transpiler, - backend=backend, - qubit_map=pair, - ) - frequencies = result.frequencies() - data.register_basis(pair, bell_state, basis, frequencies) - - return data - - -def _plot(data: CHSHData, fit: CHSHResults, target: QubitPairId): - """Plotting function for CHSH protocol.""" - figures = [] - - for bell_state in data.bell_states: - fig = go.Figure(layout_yaxis_range=[-3, 3]) - if fit is not None: - fig.add_trace( - go.Scatter( - x=data.thetas, - y=fit.chsh[target[0], target[1], bell_state], - name="Bare", - ) - ) - if fit.chsh_mitigated: - fig.add_trace( - go.Scatter( - x=data.thetas, - y=fit.chsh_mitigated[target[0], target[1], bell_state], - name="Mitigated", - ) - ) - - fig.add_trace( - go.Scatter( - mode="lines", - x=data.thetas, - y=[+CLASSICAL_BOUND] * len(data.thetas), - line_color="gray", - name="Classical limit", - line_dash="dash", - legendgroup="classic", - ) - ) - - fig.add_trace( - go.Scatter( - mode="lines", - x=data.thetas, - y=[-CLASSICAL_BOUND] * len(data.thetas), - line_color="gray", - name="Classical limit", - legendgroup="classic", - line_dash="dash", - showlegend=False, - ) - ) - - fig.add_trace( - go.Scatter( - mode="lines", - x=data.thetas, - y=[+QUANTUM_BOUND] * len(data.thetas), - line_color="gray", - name="Quantum limit", - legendgroup="quantum", - ) - ) - - fig.add_trace( - go.Scatter( - mode="lines", - x=data.thetas, - y=[-QUANTUM_BOUND] * len(data.thetas), - line_color="gray", - name="Quantum limit", - legendgroup="quantum", - showlegend=False, - ) - ) - - fig.update_layout( - xaxis_title="Theta [rad]", - yaxis_title="CHSH value", - xaxis=dict(range=[min(data.thetas), max(data.thetas)]), - ) - figures.append(fig) - - return figures, "" - - -def _fit(data: CHSHData) -> CHSHResults: - """Fitting for CHSH protocol.""" - results = {} - mitigated_results = {} - for pair in data.pairs: - for bell_state in data.bell_states: - freq = data.merge_frequencies(pair, bell_state) - if data.mitigation_matrix: - matrix = data.mitigation_matrix[pair] - - mitigated_freq_list = [] - for freq_basis in freq: - mitigated_freq = {format(i, f"0{2}b"): [] for i in range(4)} - for i in range(len(data.thetas)): - freq_array = np.zeros(4) - for k, v in freq_basis.items(): - freq_array[int(k, 2)] = v[i] - freq_array = freq_array.reshape(-1, 1) - for j, val in enumerate(matrix @ freq_array): - mitigated_freq[format(j, f"0{2}b")].append(float(val)) - mitigated_freq_list.append(mitigated_freq) - results[pair[0], pair[1], bell_state] = [ - compute_chsh(freq, bell_state, l) for l in range(len(data.thetas)) - ] - - if data.mitigation_matrix: - mitigated_results[pair[0], pair[1], bell_state] = [ - compute_chsh(mitigated_freq_list, bell_state, l) - for l in range(len(data.thetas)) - ] - return CHSHResults(chsh=results, chsh_mitigated=mitigated_results) - - -chsh_circuits = Routine(_acquisition_circuits, _fit, _plot, two_qubit_gates=True) -"""CHSH experiment using circuits.""" -chsh_pulses = Routine(_acquisition_pulses, _fit, _plot, two_qubit_gates=True) -"""CHSH experiment using pulses.""" diff --git a/src/qibocal/protocols/two_qubit_interaction/chsh/pulses.py b/src/qibocal/protocols/two_qubit_interaction/chsh/pulses.py deleted file mode 100644 index 3602d88bd..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/chsh/pulses.py +++ /dev/null @@ -1,111 +0,0 @@ -"""Auxialiary functions to run CHSH using pulses.""" - -from collections import defaultdict - -import numpy as np -from qibolab.pulses import PulseSequence - -from .utils import READOUT_BASIS - - -def create_bell_sequence(platform, qubits, theta=np.pi / 4, bell_state=0): - """Creates the pulse sequence to generate the bell states and with a theta-measurement - bell_state chooses the initial bell state for the test: - 0 -> |00>+|11> - 1 -> |00>-|11> - 2 -> |10>-|01> - 3 -> |10>+|01> - """ - - virtual_z_phases = defaultdict(int) - - sequence = PulseSequence() - sequence.add( - platform.create_RX90_pulse(qubits[0], start=0, relative_phase=np.pi / 2) - ) - sequence.add( - platform.create_RX90_pulse(qubits[1], start=0, relative_phase=np.pi / 2) - ) - - (cz_sequence, cz_virtual_z_phases) = platform.create_CZ_pulse_sequence( - qubits, sequence.finish - ) - sequence.add(cz_sequence) - for qubit in cz_virtual_z_phases: - virtual_z_phases[qubit] += cz_virtual_z_phases[qubit] - - t = sequence.finish - - sequence.add( - platform.create_RX90_pulse( - qubits[1], - start=t, - relative_phase=virtual_z_phases[qubits[1]] - np.pi / 2, - ) - ) - - if bell_state == 0: - virtual_z_phases[qubits[0]] += np.pi - elif bell_state == 1: - virtual_z_phases[qubits[0]] += 0 - elif bell_state == 2: - virtual_z_phases[qubits[0]] += 0 - sequence.add( - platform.create_RX_pulse( - qubits[0], start=t, relative_phase=virtual_z_phases[qubits[0]] - ) - ) - elif bell_state == 3: - virtual_z_phases[qubits[0]] += np.pi - sequence.add( - platform.create_RX_pulse( - qubits[0], start=t, relative_phase=virtual_z_phases[qubits[0]] - ) - ) - - t = sequence.finish - sequence.add( - platform.create_RX90_pulse( - qubits[0], start=t, relative_phase=virtual_z_phases[qubits[0]] - ) - ) - virtual_z_phases[qubits[0]] += theta - sequence.add( - platform.create_RX90_pulse( - qubits[0], - start=sequence.finish, - relative_phase=virtual_z_phases[qubits[0]] + np.pi, - ) - ) - - return sequence, virtual_z_phases - - -def create_chsh_sequences( - platform, qubits, theta=np.pi / 4, bell_state=0, readout_basis=READOUT_BASIS -): - """Creates the pulse sequences needed for the 4 measurement settings for chsh.""" - - chsh_sequences = {} - - for basis in readout_basis: - sequence, virtual_z_phases = create_bell_sequence( - platform, qubits, theta, bell_state - ) - t = sequence.finish - for i, base in enumerate(basis): - if base == "X": - sequence.add( - platform.create_RX90_pulse( - qubits[i], - start=t, - relative_phase=virtual_z_phases[qubits[i]] + np.pi / 2, - ) - ) - measurement_start = sequence.finish - for qubit in qubits: - MZ_pulse = platform.create_MZ_pulse(qubit, start=measurement_start) - sequence.add(MZ_pulse) - chsh_sequences[basis] = sequence - - return chsh_sequences diff --git a/src/qibocal/protocols/two_qubit_interaction/chsh/utils.py b/src/qibocal/protocols/two_qubit_interaction/chsh/utils.py deleted file mode 100644 index 0f38a3589..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/chsh/utils.py +++ /dev/null @@ -1,26 +0,0 @@ -"""Auxiliary functions to run CHSH protocol.""" - -from qibo.config import log - -READOUT_BASIS = ["ZZ", "ZX", "XZ", "XX"] - - -def compute_chsh(frequencies, basis, i): - """Computes the chsh inequality out of the frequencies of the 4 circuits executed.""" - chsh = 0 - aux = 0 - for freq in frequencies: - for outcome in freq: - if aux == 1 + 2 * ( - basis % 2 - ): # This value sets where the minus sign is in the CHSH inequality - chsh -= (-1) ** (int(outcome[0]) + int(outcome[1])) * freq[outcome][i] - else: - chsh += (-1) ** (int(outcome[0]) + int(outcome[1])) * freq[outcome][i] - aux += 1 - nshots = sum(freq[x][i] for x in freq) - try: - return chsh / nshots - except ZeroDivisionError: - log.warning("Zero number of shots, returning zero.") - return 0 diff --git a/src/qibocal/protocols/two_qubit_interaction/mermin/__init__.py b/src/qibocal/protocols/two_qubit_interaction/mermin/__init__.py deleted file mode 100644 index 5a4e9488d..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/mermin/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .protocol import mermin diff --git a/src/qibocal/protocols/two_qubit_interaction/mermin/protocol.py b/src/qibocal/protocols/two_qubit_interaction/mermin/protocol.py deleted file mode 100644 index a4f764d02..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/mermin/protocol.py +++ /dev/null @@ -1,264 +0,0 @@ -from dataclasses import dataclass, field -from typing import Optional - -import numpy as np -import numpy.typing as npt -import plotly.graph_objects as go -from qibolab import ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId - -from qibocal.auto.operation import Data, Parameters, Results, Routine - -from ...readout_mitigation_matrix import readout_mitigation_matrix -from ...utils import STRING_TYPE, calculate_frequencies -from .pulses import create_mermin_sequences -from .utils import ( - compute_mermin, - get_mermin_coefficients, - get_mermin_polynomial, - get_readout_basis, -) - -PLOT_PADDING = 0.2 - - -@dataclass -class MerminParameters(Parameters): - """Mermin experiment input parameters.""" - - ntheta: int - """Number of angles probed linearly between 0 and 2 pi.""" - native: Optional[bool] = False - """If True a circuit will be created using only GPI2 and CZ gates.""" - apply_error_mitigation: Optional[bool] = False - """Error mitigation model""" - - -MerminType = np.dtype( - [ - ("theta", float), - ("basis", STRING_TYPE), - ("state", int), - ("frequency", int), - ] -) - - -@dataclass -class MerminData(Data): - """Mermin Data structure.""" - - thetas: list - """Angles probed.""" - data: dict[list[QubitId], npt.NDArray[MerminType]] = field(default_factory=dict) - """Raw data acquired.""" - mitigation_matrix: dict[list[QubitId], npt.NDArray[np.float64]] = field( - default_factory=dict - ) - """Mitigation matrix computed using the readout_mitigation_matrix protocol.""" - - @property - def targets(self): - return list(self.data) - - -@dataclass -class MerminResults(Results): - """Mermin Results class.""" - - mermin: dict[tuple[QubitId, ...], npt.NDArray[np.float64]] = field( - default_factory=dict - ) - """Raw Mermin value.""" - - mermin_mitigated: dict[tuple[QubitId, ...], npt.NDArray[np.float64]] = field( - default_factory=dict - ) - """Mitigated Mermin value.""" - - -def _acquisition( - params: MerminParameters, - platform: Platform, - targets: list[list[QubitId]], -) -> MerminData: - """Data acquisition for Mermin protocol using pulse sequences.""" - - thetas = np.linspace(0, 2 * np.pi, params.ntheta) - data = MerminData(thetas=thetas.tolist()) - if params.apply_error_mitigation: - mitigation_data, _ = readout_mitigation_matrix.acquisition( - readout_mitigation_matrix.parameters_type.load(dict(nshots=params.nshots)), - platform, - targets, - ) - - mitigation_results, _ = readout_mitigation_matrix.fit(mitigation_data) - data.mitigation_matrix = mitigation_results.readout_mitigation_matrix - platform.connect() - for qubits in targets: - mermin_polynomial = get_mermin_polynomial(len(qubits)) - readout_basis = get_readout_basis(mermin_polynomial) - - for theta in thetas: - mermin_sequences = create_mermin_sequences( - platform, qubits, readout_basis=readout_basis, theta=theta - ) - options = ExecutionParameters(nshots=params.nshots) - # TODO: use unrolling - for basis, sequence in mermin_sequences.items(): - results = platform.execute_pulse_sequence(sequence, options=options) - frequencies = calculate_frequencies(results, qubits) - for state, frequency in enumerate(frequencies.values()): - data.register_qubit( - MerminType, - tuple(qubits), - dict( - theta=np.array([theta]), - basis=np.array([basis]), - state=np.array([state]), - frequency=np.array([frequency]), - ), - ) - return data - - -def _fit(data: MerminData) -> MerminResults: - """Fitting for Mermin protocol.""" - targets = data.targets - results = {qubits: [] for qubits in targets} - mitigated_results = {qubits: [] for qubits in targets} - basis = np.unique(data.data[targets[0]].basis) - for qubits in targets: - mermin_polynomial = get_mermin_polynomial(len(qubits)) - mermin_coefficients = get_mermin_coefficients(mermin_polynomial) - - for theta in data.thetas: - qubit_data = data.data[qubits] - outputs = [] - mitigated_outputs = [] - for base in basis: - frequencies = np.zeros(2 ** len(qubits)) - data_filter = (qubit_data.basis == base) & (qubit_data.theta == theta) - filtered_data = qubit_data[data_filter] - state_freq = qubit_data[data_filter].frequency - for state, freq in zip(filtered_data.state, filtered_data.frequency): - frequencies[state] = freq - - outputs.append( - { - format(i, f"0{len(qubits)}b"): freq - for i, freq in enumerate(state_freq) - } - ) - - if data.mitigation_matrix: - mitigated_output = np.dot( - data.mitigation_matrix[qubits], - frequencies, - ) - mitigated_outputs.append( - { - format(i, f"0{len(qubits)}b"): freq - for i, freq in enumerate(mitigated_output) - } - ) - if data.mitigation_matrix: - mitigated_results[tuple(qubits)].append( - compute_mermin(mitigated_outputs, mermin_coefficients) - ) - results[tuple(qubits)].append(compute_mermin(outputs, mermin_coefficients)) - return MerminResults( - mermin=results, - mermin_mitigated=mitigated_results, - ) - - -def _plot(data: MerminData, fit: MerminResults, target): - """Plotting function for Mermin protocol.""" - figures = [] - - n_qubits = len(target) - classical_bound = 2 ** (n_qubits // 2) - quantum_bound = 2 ** ((n_qubits - 1) / 2) * (2 ** (n_qubits // 2)) - - fig = go.Figure( - layout_yaxis_range=[-quantum_bound - PLOT_PADDING, quantum_bound + PLOT_PADDING] - ) - if fit is not None: - fig.add_trace( - go.Scatter( - x=data.thetas, - y=fit.mermin[tuple(target)], - name="Bare", - ) - ) - if fit.mermin_mitigated: - fig.add_trace( - go.Scatter( - x=data.thetas, - y=fit.mermin_mitigated[tuple(target)], - name="Mitigated", - ) - ) - - fig.add_trace( - go.Scatter( - mode="lines", - x=data.thetas, - y=[+classical_bound] * len(data.thetas), - line_color="gray", - name="Classical limit", - line_dash="dash", - legendgroup="classic", - ) - ) - - fig.add_trace( - go.Scatter( - mode="lines", - x=data.thetas, - y=[-classical_bound] * len(data.thetas), - line_color="gray", - name="Classical limit", - legendgroup="classic", - line_dash="dash", - showlegend=False, - ) - ) - - fig.add_trace( - go.Scatter( - mode="lines", - x=data.thetas, - y=[+quantum_bound] * len(data.thetas), - line_color="gray", - name="Quantum limit", - legendgroup="quantum", - ) - ) - - fig.add_trace( - go.Scatter( - mode="lines", - x=data.thetas, - y=[-quantum_bound] * len(data.thetas), - line_color="gray", - name="Quantum limit", - legendgroup="quantum", - showlegend=False, - ) - ) - - fig.update_layout( - xaxis_title="Theta [rad]", - yaxis_title="Mermin polynomial value", - xaxis=dict(range=[min(data.thetas), max(data.thetas)]), - ) - figures.append(fig) - - return figures, "" - - -mermin = Routine(_acquisition, _fit, _plot) diff --git a/src/qibocal/protocols/two_qubit_interaction/mermin/pulses.py b/src/qibocal/protocols/two_qubit_interaction/mermin/pulses.py deleted file mode 100644 index 239f81d67..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/mermin/pulses.py +++ /dev/null @@ -1,84 +0,0 @@ -from collections import defaultdict - -import numpy as np -from qibolab.pulses import PulseSequence - - -def create_mermin_sequence(platform, qubits, theta=None): - """Creates the pulse sequence to generate the bell states and with a theta-measurement""" - - nqubits = len(qubits) - if theta is None: - theta = ((nqubits - 1) * 0.25 * np.pi) % (2 * np.pi) - - virtual_z_phases = defaultdict(int) - sequence = PulseSequence() - - for qubit in qubits: - sequence.add( - platform.create_RX90_pulse( - qubit, start=0, relative_phase=virtual_z_phases[qubit] + np.pi / 2 - ) - ) - - # TODO: Not hardcode topology - - # qubits[0] needs to be the center qubit where everything is connected - for i in range(1, len(qubits)): - (cz_sequence1, cz_virtual_z_phases) = platform.create_CZ_pulse_sequence( - [qubits[0]] + [qubits[i]], sequence.finish + 8 # TODO: ask for the 8 - ) - sequence.add(cz_sequence1) - for qubit in cz_virtual_z_phases: - virtual_z_phases[qubit] += cz_virtual_z_phases[qubit] - - t = sequence.finish + 8 - - for i in range(1, len(qubits)): - sequence.add( - platform.create_RX90_pulse( - qubits[i], - start=t, - relative_phase=virtual_z_phases[qubits[i]] - np.pi / 2, - ) - ) - - virtual_z_phases[qubits[0]] -= theta - - return sequence, virtual_z_phases - - -def create_mermin_sequences(platform, qubits, readout_basis, theta): - """Creates the pulse sequences needed for the 4 measurement settings for chsh.""" - - mermin_sequences = {} - - for basis in readout_basis: - sequence, virtual_z_phases = create_mermin_sequence( - platform, qubits, theta=theta - ) - # t = sequence.finish - for i, base in enumerate(basis): - if base == "X": - sequence.add( - platform.create_RX90_pulse( - qubits[i], - start=sequence.finish, - relative_phase=virtual_z_phases[qubits[i]] + np.pi / 2, - ) - ) - if base == "Y": - sequence.add( - platform.create_RX90_pulse( - qubits[i], - start=sequence.finish, - relative_phase=virtual_z_phases[qubits[i]], - ) - ) - measurement_start = sequence.finish - - for qubit in qubits: - sequence.add(platform.create_MZ_pulse(qubit, start=measurement_start)) - - mermin_sequences[basis] = sequence - return mermin_sequences diff --git a/src/qibocal/protocols/two_qubit_interaction/mermin/utils.py b/src/qibocal/protocols/two_qubit_interaction/mermin/utils.py deleted file mode 100644 index e0afdca28..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/mermin/utils.py +++ /dev/null @@ -1,44 +0,0 @@ -from qibo.hamiltonians import SymbolicHamiltonian -from qibo.symbols import X, Y - - -def compute_mermin(frequencies, mermin_coefficients): - """Computes the chsh inequality out of the frequencies of the 4 circuits executed.""" - assert len(frequencies) == len(mermin_coefficients) - m = 0 - for j, freq in enumerate(frequencies): - for key in freq: - m += ( - mermin_coefficients[j] - * freq[key] - * (-1) ** (sum([int(key[k]) for k in range(len(key))])) - ) - nshots = sum(freq[x] for x in freq) - if nshots != 0: - return float(m / nshots) - - return 0 - - -def get_mermin_polynomial(n): - assert n > 1 - m0 = X(0) - m0p = Y(0) - for i in range(1, n): - mn = m0 * (X(i) + Y(i)) + m0p * (X(i) - Y(i)) - mnp = m0 * (Y(i) - X(i)) + m0p * (X(i) + Y(i)) - m0 = mn.expand() - m0p = mnp.expand() - m = m0 / 2 ** ((n - 1) // 2) - return SymbolicHamiltonian(m.expand()) - - -def get_readout_basis(mermin_polynomial): - return [ - "".join([factor.name[0] for factor in term.factors]) - for term in mermin_polynomial.terms - ] - - -def get_mermin_coefficients(mermin_polynomial): - return [term.coefficient.real for term in mermin_polynomial.terms] diff --git a/src/qibocal/protocols/two_qubit_interaction/optimize.py b/src/qibocal/protocols/two_qubit_interaction/optimize.py index dcf4845b9..7ea214032 100644 --- a/src/qibocal/protocols/two_qubit_interaction/optimize.py +++ b/src/qibocal/protocols/two_qubit_interaction/optimize.py @@ -7,13 +7,18 @@ import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitId, QubitPairId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import AcquisitionType, AveragingMode, Parameter, Sweeper from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import ( + Data, + Parameters, + QubitId, + QubitPairId, + Results, + Routine, +) +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import table_dict, table_html @@ -43,10 +48,8 @@ class OptimizeTwoQubitGateParameters(Parameters): """Maximum duration of flux pulse swept.""" duration_step: int """Step duration of flux pulse swept.""" - dt: Optional[float] = 20 + dt: Optional[float] = 0 """Time delay between flux pulses and readout.""" - parking: bool = True - """Wether to park non interacting qubits or not.""" native: str = "CZ" """Two qubit interaction to be calibrated. @@ -141,7 +144,7 @@ def register_qubit( def _acquisition( params: OptimizeTwoQubitGateParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitPairId], ) -> OptimizeTwoQubitGateData: r""" @@ -154,97 +157,81 @@ def _acquisition( ) for pair in targets: # order the qubits so that the low frequency one is the first - ord_pair = order_pair(pair, platform) + ordered_pair = order_pair(pair, platform) for target_q, control_q in ( - (ord_pair[0], ord_pair[1]), - (ord_pair[1], ord_pair[0]), + (ordered_pair[0], ordered_pair[1]), + (ordered_pair[1], ordered_pair[0]), ): for setup in ("I", "X"): ( sequence, flux_pulse, theta_pulse, + ro_delays, ) = create_sequence( platform, setup, target_q, control_q, - ord_pair, + ordered_pair, params.native, params.dt, - params.parking, flux_pulse_max_duration=params.duration_max, ) - theta = np.arange( - params.theta_start, - params.theta_end, - params.theta_step, - dtype=float, - ) - - amplitude_range = np.arange( - params.flux_pulse_amplitude_min, - params.flux_pulse_amplitude_max, - params.flux_pulse_amplitude_step, - dtype=float, - ) - - duration_range = np.arange( - params.duration_min, - params.duration_max, - params.duration_step, - dtype=float, - ) - - data.amplitudes[ord_pair] = amplitude_range.tolist() - data.durations[ord_pair] = duration_range.tolist() sweeper_theta = Sweeper( - Parameter.relative_phase, - theta, + parameter=Parameter.relative_phase, + range=(params.theta_start, params.theta_end, params.theta_step), pulses=[theta_pulse], - type=SweeperType.ABSOLUTE, ) sweeper_amplitude = Sweeper( - Parameter.amplitude, - amplitude_range / flux_pulse.amplitude, + parameter=Parameter.amplitude, + range=( + params.flux_pulse_amplitude_min, + params.flux_pulse_amplitude_max, + params.flux_pulse_amplitude_step, + ), pulses=[flux_pulse], - type=SweeperType.FACTOR, ) sweeper_duration = Sweeper( - Parameter.duration, - duration_range, - pulses=[flux_pulse], - type=SweeperType.ABSOLUTE, + parameter=Parameter.duration, + range=( + params.duration_min, + params.duration_max, + params.duration_step, + ), + pulses=[flux_pulse] + ro_delays, ) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper_duration, - sweeper_amplitude, - sweeper_theta, + ro_target = list( + sequence.channel(platform.qubits[target_q].acquisition) + )[-1] + ro_control = list( + sequence.channel(platform.qubits[control_q].acquisition) + )[-1] + results = platform.execute( + [sequence], + [[sweeper_duration], [sweeper_amplitude], [sweeper_theta]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.CYCLIC, ) - result_target = results[target_q].probability(1) - result_control = results[control_q].probability(1) + data.amplitudes[ordered_pair] = sweeper_amplitude.values.tolist() + data.durations[ordered_pair] = sweeper_duration.values.tolist() data.register_qubit( target_q, control_q, setup, - theta, - data.amplitudes[ord_pair], - data.durations[ord_pair], - result_control, - result_target, + sweeper_theta.values, + sweeper_amplitude.values, + sweeper_duration.values, + results[ro_control.id], + results[ro_target.id], ) return data @@ -374,7 +361,6 @@ def _plot( """Plot routine for OptimizeTwoQubitGate.""" fitting_report = "" qubits = next(iter(data.amplitudes))[:2] - fig = make_subplots( rows=2, cols=2, @@ -402,7 +388,6 @@ def _plot( leakage.append(fit.leakages[qubits[0], qubits[1], i, j][control_q]) condition = [target_q, control_q] == list(target) - fig.add_trace( go.Heatmap( x=durs, @@ -458,7 +443,9 @@ def _plot( def _update( - results: OptimizeTwoQubitGateResults, platform: Platform, target: QubitPairId + results: OptimizeTwoQubitGateResults, + platform: CalibrationPlatform, + target: QubitPairId, ): # FIXME: quick fix for qubit order target = tuple(sorted(target)) diff --git a/src/qibocal/protocols/two_qubit_interaction/utils.py b/src/qibocal/protocols/two_qubit_interaction/utils.py index 06c912a30..b5eec8e99 100644 --- a/src/qibocal/protocols/two_qubit_interaction/utils.py +++ b/src/qibocal/protocols/two_qubit_interaction/utils.py @@ -1,18 +1,18 @@ import numpy as np -from qibolab.platform import Platform -from qibolab.qubits import QubitId, QubitPairId +from qibolab import Platform + +from qibocal.auto.operation import QubitId, QubitPairId from ..utils import fallback_period, guess_period def order_pair(pair: QubitPairId, platform: Platform) -> tuple[QubitId, QubitId]: """Order a pair of qubits by drive frequency.""" - if ( - platform.qubits[pair[0]].drive_frequency - > platform.qubits[pair[1]].drive_frequency - ): - return pair[1], pair[0] - return pair[0], pair[1] + q0, q1 = pair + + drive0 = platform.config(platform.qubits[q0].drive) + drive1 = platform.config(platform.qubits[q1].drive) + return (q1, q0) if drive0.frequency > drive1.frequency else (q0, q1) def fit_flux_amplitude(matrix, amps, times): diff --git a/src/qibocal/protocols/two_qubit_interaction/virtual_z_phases.py b/src/qibocal/protocols/two_qubit_interaction/virtual_z_phases.py index d450f6068..fafbc9e3a 100644 --- a/src/qibocal/protocols/two_qubit_interaction/virtual_z_phases.py +++ b/src/qibocal/protocols/two_qubit_interaction/virtual_z_phases.py @@ -1,24 +1,38 @@ """CZ virtual correction experiment for two qubit gates, tune landscape.""" from dataclasses import dataclass, field -from typing import Optional +from typing import Literal, Optional import numpy as np import numpy.typing as npt import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.pulses import Pulse, PulseSequence -from qibolab.qubits import QubitId, QubitPairId -from qibolab.sweeper import Parameter, Sweeper, SweeperType +from qibolab import ( + AcquisitionType, + AveragingMode, + Delay, + Parameter, + Pulse, + PulseSequence, + Sweeper, + VirtualZ, +) from scipy.optimize import curve_fit -from qibocal import update -from qibocal.auto.operation import Data, Parameters, Results, Routine +from qibocal.auto.operation import ( + Data, + Parameters, + QubitId, + QubitPairId, + Results, + Routine, +) +from qibocal.calibration import CalibrationPlatform from qibocal.config import log from qibocal.protocols.utils import table_dict, table_html +from ... import update +from ...update import replace from .utils import order_pair @@ -40,8 +54,6 @@ class VirtualZPhasesParameters(Parameters): """ dt: Optional[float] = 20 """Time delay between flux pulses and readout.""" - parking: bool = True - """Wether to park non interacting qubits or not.""" @dataclass @@ -64,7 +76,6 @@ def __contains__(self, key: QubitPairId): While key is a QubitPairId both chsh and chsh_mitigated contain an additional key which represents the basis chosen. """ - # TODO: fix this (failing only for qq report) return key in [ (target, control) for target, control, _ in self.fitted_parameters ] @@ -90,13 +101,12 @@ def __getitem__(self, pair): def create_sequence( - platform: Platform, - setup: str, + platform: CalibrationPlatform, + setup: Literal["I", "X"], target_qubit: QubitId, control_qubit: QubitId, ordered_pair: list[QubitId, QubitId], - native: str, - parking: bool, + native: Literal["CZ", "iSWAP"], dt: float, flux_pulse_max_duration: float = None, ) -> tuple[ @@ -106,66 +116,112 @@ def create_sequence( ]: """Create the experiment PulseSequence.""" + target_natives = platform.natives.single_qubit[target_qubit] + control_natives = platform.natives.single_qubit[control_qubit] + sequence = PulseSequence() + # Y90 + sequence += target_natives.R(theta=np.pi / 2, phi=np.pi / 2) + # X + if setup == "X": + sequence += control_natives.RX() + else: + sequence.append( + (platform.qubits[control_qubit].drive, Delay(duration=sequence.duration)) + ) - Y90_pulse = platform.create_RX90_pulse( - target_qubit, start=0, relative_phase=np.pi / 2 - ) - RX_pulse_start = platform.create_RX_pulse(control_qubit, start=0, relative_phase=0) + drive_duration = sequence.duration - flux_sequence, _ = getattr(platform, f"create_{native}_pulse_sequence")( - (ordered_pair[1], ordered_pair[0]), - start=max(Y90_pulse.finish, RX_pulse_start.finish), - ) + # CZ + flux_sequence = getattr(platform.natives.two_qubit[ordered_pair], native)() + flux_pulses = [ + (ch, pulse) for ch, pulse in flux_sequence if not isinstance(pulse, VirtualZ) + ] - flux_pulse = flux_sequence.get_qubit_pulses(ordered_pair[1])[0] if flux_pulse_max_duration is not None: - flux_pulse.duration = flux_pulse_max_duration + flux_pulses[0] = ( + flux_pulses[0][0], + replace(flux_pulses[0][1], duration=flux_pulse_max_duration), + ) - theta_pulse = platform.create_RX90_pulse( - target_qubit, - start=flux_sequence.finish + dt, - relative_phase=0, - ) - RX_pulse_end = platform.create_RX_pulse( - control_qubit, - start=flux_sequence.finish + dt, - relative_phase=0, - ) - measure_target = platform.create_qubit_readout_pulse( - target_qubit, start=theta_pulse.finish - ) - measure_control = platform.create_qubit_readout_pulse( - control_qubit, start=theta_pulse.finish - ) + _, flux_pulse = flux_pulses[0] + flux_sequence = PulseSequence(flux_pulses) + sequence |= flux_sequence - sequence.add( - Y90_pulse, - flux_sequence.get_qubit_pulses(ordered_pair[1]), - flux_sequence.cf_pulses, - theta_pulse, - measure_target, - measure_control, - ) + flux_duration = flux_sequence.duration + dt_delay = Delay(duration=dt) + theta_sequence = PulseSequence( + [ + ( + platform.qubits[target_qubit].drive, + dt_delay, + ), + ( + platform.qubits[control_qubit].drive, + dt_delay, + ), + ( + platform.qubits[target_qubit].drive, + Delay(duration=flux_duration), + ), + ( + platform.qubits[control_qubit].drive, + Delay(duration=flux_duration), + ), + ] + ) + # R90 (angle to be swept) + theta_sequence += target_natives.R(theta=np.pi / 2, phi=0) + theta_pulse = theta_sequence[-1][1] + # X if setup == "X": - sequence.add( - RX_pulse_start, - RX_pulse_end, - ) + theta_sequence += control_natives.RX() + + sequence += theta_sequence + + ro_target_delay = Delay(duration=flux_duration) + ro_control_delay = Delay(duration=flux_duration) + # M + ro_sequence = PulseSequence( + [ + ( + platform.qubits[target_qubit].acquisition, + Delay(duration=drive_duration), + ), + ( + platform.qubits[control_qubit].acquisition, + Delay(duration=drive_duration), + ), + ( + platform.qubits[target_qubit].acquisition, + ro_target_delay, + ), + ( + platform.qubits[control_qubit].acquisition, + ro_control_delay, + ), + ( + platform.qubits[target_qubit].acquisition, + Delay(duration=theta_sequence.duration), + ), + ( + platform.qubits[control_qubit].acquisition, + Delay(duration=theta_sequence.duration), + ), + target_natives.MZ()[0], + control_natives.MZ()[0], + ] + ) - if parking: - for pulse in flux_sequence: - if pulse.qubit not in ordered_pair: - pulse.duration = theta_pulse.finish - sequence.add(pulse) + sequence += ro_sequence - return sequence, flux_pulse, theta_pulse + return sequence, flux_pulse, theta_pulse, [ro_target_delay, ro_control_delay] def _acquisition( params: VirtualZPhasesParameters, - platform: Platform, + platform: CalibrationPlatform, targets: list[QubitPairId], ) -> VirtualZPhasesData: r""" @@ -189,52 +245,49 @@ def _acquisition( data = VirtualZPhasesData(thetas=theta_absolute.tolist(), native=params.native) for pair in targets: # order the qubits so that the low frequency one is the first - ord_pair = order_pair(pair, platform) + ordered_pair = order_pair(pair, platform) for target_q, control_q in ( - (ord_pair[0], ord_pair[1]), - (ord_pair[1], ord_pair[0]), + (ordered_pair[0], ordered_pair[1]), + (ordered_pair[1], ordered_pair[0]), ): for setup in ("I", "X"): ( sequence, _, theta_pulse, + _, ) = create_sequence( platform, setup, target_q, control_q, - ord_pair, + ordered_pair, params.native, params.dt, - params.parking, - ) - theta = np.arange( - params.theta_start, - params.theta_end, - params.theta_step, - dtype=float, ) sweeper = Sweeper( - Parameter.relative_phase, - theta, + parameter=Parameter.relative_phase, + range=(params.theta_start, params.theta_end, params.theta_step), pulses=[theta_pulse], - type=SweeperType.ABSOLUTE, ) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.DISCRIMINATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper, + results = platform.execute( + [sequence], + [[sweeper]], + nshots=params.nshots, + relaxation_time=params.relaxation_time, + acquisition_type=AcquisitionType.DISCRIMINATION, + averaging_mode=AveragingMode.CYCLIC, ) - result_target = results[target_q].probability(1) - result_control = results[control_q].probability(1) + ro_target = list( + sequence.channel(platform.qubits[target_q].acquisition) + )[-1] + ro_control = list( + sequence.channel(platform.qubits[control_q].acquisition) + )[-1] + result_target = results[ro_target.id] + result_control = results[ro_control.id] data.register_qubit( VirtualZPhasesType, @@ -445,7 +498,9 @@ def _plot(data: VirtualZPhasesData, fit: VirtualZPhasesResults, target: QubitPai return [fig1, fig2], "".join(fitting_report) # target and control qubit -def _update(results: VirtualZPhasesResults, platform: Platform, target: QubitPairId): +def _update( + results: VirtualZPhasesResults, platform: CalibrationPlatform, target: QubitPairId +): # FIXME: quick fix for qubit order target = tuple(sorted(target)) update.virtual_phases( diff --git a/src/qibocal/protocols/two_qubit_interaction/virtual_z_phases_signal.py b/src/qibocal/protocols/two_qubit_interaction/virtual_z_phases_signal.py deleted file mode 100644 index 35db5dc37..000000000 --- a/src/qibocal/protocols/two_qubit_interaction/virtual_z_phases_signal.py +++ /dev/null @@ -1,149 +0,0 @@ -"""CZ virtual correction experiment for two qubit gates, tune landscape.""" - -from dataclasses import dataclass - -import numpy as np -from qibolab import AcquisitionType, AveragingMode, ExecutionParameters -from qibolab.platform import Platform -from qibolab.qubits import QubitPairId -from qibolab.sweeper import Parameter, Sweeper, SweeperType - -from qibocal.auto.operation import Routine - -from .utils import order_pair -from .virtual_z_phases import ( - VirtualZPhasesData, - VirtualZPhasesParameters, - VirtualZPhasesResults, - VirtualZPhasesType, - _fit, -) -from .virtual_z_phases import _plot as _plot_prob -from .virtual_z_phases import ( - _update, - create_sequence, -) - - -@dataclass -class VirtualZPhasesSignalParameters(VirtualZPhasesParameters): - """VirtualZ runcard inputs.""" - - -@dataclass -class VirtualZPhasesSignalResults(VirtualZPhasesResults): - """VirtualZ outputs when fitting will be done.""" - - -VirtualZPhasesType = np.dtype([("target", np.float64), ("control", np.float64)]) - - -@dataclass -class VirtualZPhasesSignalData(VirtualZPhasesData): - """VirtualZPhases data.""" - - -def _acquisition( - params: VirtualZPhasesSignalParameters, - platform: Platform, - targets: list[QubitPairId], -) -> VirtualZPhasesSignalData: - r""" - Acquisition for VirtualZPhases. See https://arxiv.org/pdf/1904.06560.pdf - - Check the two-qubit landscape created by a flux pulse of a given duration - and amplitude. - The system is initialized with a Y90 pulse on the low frequency qubit and either - an Id or an X gate on the high frequency qubit. Then the flux pulse is applied to - the high frequency qubit in order to perform a two-qubit interaction. The Id/X gate - is undone in the high frequency qubit and a theta90 pulse is applied to the low - frequency qubit before measurement. That is, a pi-half pulse around the relative phase - parametereized by the angle theta. - Measurements on the low frequency qubit yield the 2Q-phase of the gate and the - remnant single qubit Z phase aquired during the execution to be corrected. - Population of the high frequency qubit yield the leakage to the non-computational states - during the execution of the flux pulse. - """ - - theta_absolute = np.arange(params.theta_start, params.theta_end, params.theta_step) - data = VirtualZPhasesData(native=params.native, thetas=theta_absolute.tolist()) - for pair in targets: - # order the qubits so that the low frequency one is the first - ord_pair = order_pair(pair, platform) - - for target_q, control_q in ( - (ord_pair[0], ord_pair[1]), - (ord_pair[1], ord_pair[0]), - ): - for setup in ("I", "X"): - ( - sequence, - _, - theta_pulse, - ) = create_sequence( - platform, - setup, - target_q, - control_q, - ord_pair, - params.native, - params.dt, - params.parking, - ) - theta = np.arange( - params.theta_start, - params.theta_end, - params.theta_step, - dtype=float, - ) - sweeper = Sweeper( - Parameter.relative_phase, - theta, - pulses=[theta_pulse], - type=SweeperType.ABSOLUTE, - ) - results = platform.sweep( - sequence, - ExecutionParameters( - nshots=params.nshots, - relaxation_time=params.relaxation_time, - acquisition_type=AcquisitionType.INTEGRATION, - averaging_mode=AveragingMode.CYCLIC, - ), - sweeper, - ) - - result_target = results[target_q].magnitude - result_control = results[control_q].magnitude - - data.register_qubit( - VirtualZPhasesType, - (target_q, control_q, setup), - dict( - target=result_target, - control=result_control, - ), - ) - return data - - -def _plot( - data: VirtualZPhasesSignalData, - fit: VirtualZPhasesSignalResults, - target: QubitPairId, -): - """Plot routine for VirtualZPhases.""" - figs, fitting_report = _plot_prob(data, fit, target) - - for fig in figs: - fig.update_layout( - yaxis_title="Signal [a.u.]", - ) - - return figs, fitting_report - - -correct_virtual_z_phases_signal = Routine( - _acquisition, _fit, _plot, _update, two_qubit_gates=True -) -"""Virtual Z correction routine.""" diff --git a/src/qibocal/protocols/two_qubit_state_tomography.py b/src/qibocal/protocols/two_qubit_state_tomography.py index 58da7ae15..4914363bc 100644 --- a/src/qibocal/protocols/two_qubit_state_tomography.py +++ b/src/qibocal/protocols/two_qubit_state_tomography.py @@ -12,11 +12,17 @@ from qibo.backends import NumpyBackend, construct_backend from qibo.quantum_info import fidelity, partial_trace from qibo.result import QuantumState -from qibolab.platform import Platform -from qibolab.qubits import QubitId, QubitPairId -from qibocal.auto.operation import DATAFILE, Data, Results, Routine +from qibocal.auto.operation import ( + DATAFILE, + Data, + QubitId, + QubitPairId, + Results, + Routine, +) from qibocal.auto.transpile import dummy_transpiler, execute_transpiled_circuit +from qibocal.calibration import CalibrationPlatform from .state_tomography import StateTomographyParameters, plot_reconstruction from .utils import table_dict, table_html @@ -84,7 +90,9 @@ class StateTomographyResults(Results): def _acquisition( - params: StateTomographyParameters, platform: Platform, targets: list[QubitPairId] + params: StateTomographyParameters, + platform: CalibrationPlatform, + targets: list[QubitPairId], ) -> StateTomographyData: """Acquisition protocol for two qubit state tomography experiment.""" qubits = [q for pair in targets for q in pair] diff --git a/src/qibocal/protocols/utils.py b/src/qibocal/protocols/utils.py index 026a44240..474e6cfca 100644 --- a/src/qibocal/protocols/utils.py +++ b/src/qibocal/protocols/utils.py @@ -7,12 +7,11 @@ import plotly.graph_objects as go from numpy.typing import NDArray from plotly.subplots import make_subplots -from qibolab.qubits import QubitId from scipy import constants from scipy.optimize import curve_fit from scipy.signal import find_peaks -from qibocal.auto.operation import Data, Results +from qibocal.auto.operation import Data, QubitId, Results from qibocal.config import log from qibocal.fitting.classifier import run from qibocal.protocols.resonator_utils import ( @@ -81,7 +80,7 @@ def effective_qubit_temperature( return temp, error -def calculate_frequencies(results, qubit_list): +def calculate_frequencies(results, ro_pulses): """Calculates outcome frequencies from individual shots. Args: results (dict): return of execute_pulse_sequence @@ -90,9 +89,8 @@ def calculate_frequencies(results, qubit_list): Returns: dictionary containing frequencies. """ - shots = np.stack([results[i].samples for i in qubit_list]).T + shots = np.stack([results[ro_pulses[qubit].id] for qubit in ro_pulses]).T values, counts = np.unique(shots, axis=0, return_counts=True) - return {"".join(str(int(i)) for i in v): cnt for v, cnt in zip(values, counts)} @@ -368,26 +366,6 @@ def spectroscopy_plot(data, qubit, fit: Results = None): label = "Qubit Frequency [Hz]" freq = fit.frequency - if data.attenuations: - if data.attenuations[qubit] is not None: - if show_error_bars: - labels = [label, "Amplitude", "Attenuation", "Chi2 Reduced"] - values = [ - ( - freq[qubit], - fit.error_fit_pars[qubit][1], - ), - (data.amplitudes[qubit], 0), - (data.attenuations[qubit], 0), - fit.chi2_reduced[qubit], - ] - else: - labels = [label, "Amplitude", "Attenuation"] - values = [ - freq[qubit], - data.amplitudes[qubit], - data.attenuations[qubit], - ] if data.amplitudes[qubit] is not None: if show_error_bars: labels = [label, "Amplitude", "Chi2 reduced"] @@ -517,11 +495,10 @@ def s21_spectroscopy_plot(data, qubit, fit: Results = None): row=1, col=1, ) - fig_raw.add_trace( go.Scatter( x=np.concatenate((frequencies, frequencies[::-1])), - y=np.concatenate((phase + errors_phase), (phase - errors_phase[::-1])), + y=np.concatenate((phase + errors_phase, (phase - errors_phase)[::-1])), fill="toself", fillcolor=COLORBAND, line=dict(color=COLORBAND_LINE), @@ -712,12 +689,11 @@ def s21_spectroscopy_plot(data, qubit, fit: Results = None): row=1, col=1, ) - fig_calibrated.add_trace( go.Scatter( x=np.concatenate((frequencies, frequencies[::-1])), y=np.concatenate( - (phase + errors_phase), (phase - errors_phase[::-1]) + (phase + errors_phase, (phase - errors_phase)[::-1]) ), fill="toself", fillcolor=COLORBAND, diff --git a/src/qibocal/result.py b/src/qibocal/result.py new file mode 100644 index 000000000..675b8091e --- /dev/null +++ b/src/qibocal/result.py @@ -0,0 +1,88 @@ +"""Common result operations.""" + +import numpy as np +import numpy.typing as npt + +IQ = npt.NDArray[np.float64] +"""An array of I and Q values. + +It is assumed that the I and Q component are discriminated by the +innermost dimension of the array. +""" + + +def _lift(values: IQ) -> npt.NDArray: + """Transpose the innermost dimension to the outermost.""" + return np.moveaxis(values, -1, 0) + + +def _sink(values: npt.NDArray) -> IQ: + """Transpose the outermost dimension to the innermost. + + Inverse of :func:`_lift`. + """ + return np.moveaxis(values, 0, -1) + + +def collect(i: npt.NDArray, q: npt.NDArray) -> IQ: + """Collect I and Q components in a single array.""" + return _sink(np.stack([i, q])) + + +def unpack(iq: IQ) -> tuple[npt.NDArray, npt.NDArray]: + """Unpack I and Q components from single array. + + Inverse of :func:`collect`. + """ + i, q = tuple(_lift(iq)) + return i, q + + +def magnitude(iq: IQ): + """Signal magnitude. + + It is supposed to be a tension, possibly in arbitrary units. + """ + iq_ = _lift(iq) + return np.sqrt(iq_[0] ** 2 + iq_[1] ** 2) + + +def average(values: npt.NDArray) -> tuple[npt.NDArray, npt.NDArray]: + """Perform the values average. + + It returns both the average estimator itself, and its standard + deviation estimator. + + Use this also for I and Q values in the *standard layout*, cf. :class:`IQ`. + """ + mean = np.mean(values, axis=0) + std = np.std(values, axis=0, ddof=1) / np.sqrt(values.shape[0]) + return mean, std + + +def average_iq(i: npt.NDArray, q: npt.NDArray) -> tuple[npt.NDArray, npt.NDArray]: + """Perform the average over I and Q. + + Convenience wrapper over :func:`average` for separate i and q samples arrays. + """ + return average(collect(i, q)) + + +def phase(iq: npt.NDArray): + """Signal phase in radians. + + It is assumed that the I and Q component are discriminated by the + innermost dimension of the array. + """ + iq_ = _lift(iq) + return np.unwrap(np.arctan2(iq_[0], iq_[1])) + + +def probability(values: npt.NDArray, state: int = 0): + """Return the statistical frequency of the specified state. + + The only accepted values `state` are `0` and `1`. + """ + # The absolute value is only needed to make sure the result is always positive, even + # when extremely close to zero + return abs(1 - state - np.mean(values, axis=0)) diff --git a/src/qibocal/update.py b/src/qibocal/update.py index 376cad2c3..78f865df1 100644 --- a/src/qibocal/update.py +++ b/src/qibocal/update.py @@ -4,10 +4,10 @@ from typing import Union import numpy as np -from qibolab import pulses -from qibolab.native import VirtualZPulse -from qibolab.platform import Platform -from qibolab.qubits import QubitId, QubitPairId +from pydantic import BaseModel +from qibolab import Platform, PulseSequence, VirtualZ + +from qibocal.auto.operation import QubitId, QubitPairId CLASSIFICATION_PARAMS = [ "threshold", @@ -18,29 +18,30 @@ ] +def replace(model: BaseModel, **update): + """Replace interface for pydantic models.""" + return model.model_copy(update=update) + + def readout_frequency(freq: float, platform: Platform, qubit: QubitId): """Update readout frequency value in platform for specific qubit.""" - mz = platform.qubits[qubit].native_gates.MZ - freq_hz = int(freq) - mz.frequency = freq_hz - if mz.if_frequency is not None: - mz.if_frequency = freq_hz - platform.qubits[qubit].readout.lo_frequency - platform.qubits[qubit].readout_frequency = freq_hz + ro_channel = platform.qubits[qubit].probe + platform.update({f"configs.{ro_channel}.frequency": freq}) def bare_resonator_frequency(freq: float, platform: Platform, qubit: QubitId): """Update rbare frequency value in platform for specific qubit.""" - platform.qubits[qubit].bare_resonator_frequency = int(freq) + platform.calibration.single_qubits[qubit].resonator.bare_frequency = int(freq) -def readout_amplitude(amp: float, platform: Platform, qubit: QubitId): - """Update readout amplitude value in platform for specific qubit.""" - platform.qubits[qubit].native_gates.MZ.amplitude = float(amp) +def dressed_resonator_frequency(freq: float, platform: Platform, qubit: QubitId): + """Update rbare frequency value in platform for specific qubit.""" + platform.calibration.single_qubits[qubit].resonator.dressed_frequency = int(freq) -def readout_attenuation(att: int, platform: Platform, qubit: QubitId): - """Update readout attenuation value in platform for specific qubit.""" - platform.qubits[qubit].readout.attenuation = int(att) +def readout_amplitude(amp: float, platform: Platform, qubit: QubitId): + """Update readout amplitude value in platform for specific qubit.""" + platform.update({f"native_gates.single_qubit.{qubit}.MZ.0.1.probe.amplitude": amp}) def drive_frequency( @@ -49,183 +50,180 @@ def drive_frequency( """Update drive frequency value in platform for specific qubit.""" if isinstance(freq, Iterable): freq = freq[0] - freq = int(freq) - platform.qubits[qubit].native_gates.RX.frequency = int(freq) - platform.qubits[qubit].drive_frequency = int(freq) + drive_channel = platform.qubits[qubit].drive + platform.update({f"configs.{drive_channel}.frequency": freq}) -def drive_amplitude(amp: Union[float, tuple, list], platform: Platform, qubit: QubitId): +def drive_amplitude( + amp: Union[float, tuple, list], rx90: bool, platform: Platform, qubit: QubitId +): """Update drive frequency value in platform for specific qubit.""" if isinstance(amp, Iterable): amp = amp[0] - platform.qubits[qubit].native_gates.RX.amplitude = float(amp) + if rx90: + platform.update({f"native_gates.single_qubit.{qubit}.RX90.0.1.amplitude": amp}) + else: + platform.update({f"native_gates.single_qubit.{qubit}.RX.0.1.amplitude": amp}) def drive_duration( - duration: Union[int, tuple, list], platform: Platform, qubit: QubitId + duration: Union[int, tuple, list], rx90: bool, platform: Platform, qubit: QubitId ): """Update drive duration value in platform for specific qubit.""" if isinstance(duration, Iterable): duration = duration[0] - platform.qubits[qubit].native_gates.RX.duration = int(duration) + if rx90: + platform.update( + {f"native_gates.single_qubit.{qubit}.RX90.0.1.duration": int(duration)} + ) + else: + platform.update( + {f"native_gates.single_qubit.{qubit}.RX.0.1.duration": int(duration)} + ) def crosstalk_matrix( matrix_element: float, platform: Platform, qubit: QubitId, flux_qubit: QubitId ): """Update crosstalk_matrix element.""" - platform.qubits[qubit].crosstalk_matrix[flux_qubit] = float(matrix_element) + if platform.calibration.flux_crosstalk_matrix is None: + platform.calibration.flux_crosstalk_matrix = np.zeros( + (platform.calibration.nqubits, platform.calibration.nqubits) + ) + platform.calibration.set_crosstalk_element(qubit, flux_qubit, matrix_element) def iq_angle(angle: float, platform: Platform, qubit: QubitId): """Update iq angle value in platform for specific qubit.""" - platform.qubits[qubit].iq_angle = float(angle) + ro_channel = platform.qubits[qubit].acquisition + platform.update({f"configs.{ro_channel}.iq_angle": angle}) def threshold(threshold: float, platform: Platform, qubit: QubitId): - platform.qubits[qubit].threshold = float(threshold) + ro_channel = platform.qubits[qubit].acquisition + platform.update({f"configs.{ro_channel}.threshold": threshold}) -def mean_gnd_states(gnd_state: list, platform: Platform, qubit: QubitId): +def mean_gnd_states(ground_state: list, platform: Platform, qubit: QubitId): """Update mean ground state value in platform for specific qubit.""" - platform.qubits[qubit].mean_gnd_states = gnd_state + platform.calibration.single_qubits[qubit].readout.ground_state = ground_state -def mean_exc_states(exc_state: list, platform: Platform, qubit: QubitId): +def mean_exc_states(excited_state: list, platform: Platform, qubit: QubitId): """Update mean excited state value in platform for specific qubit.""" - platform.qubits[qubit].mean_exc_states = exc_state + platform.calibration.single_qubits[qubit].readout.excited_state = excited_state def readout_fidelity(fidelity: float, platform: Platform, qubit: QubitId): """Update fidelity of single shot classification.""" - platform.qubits[qubit].readout_fidelity = float(fidelity) - - -def assignment_fidelity(fidelity: float, platform: Platform, qubit: QubitId): - """Update fidelity of single shot classification.""" - platform.qubits[qubit].assignment_fidelity = float(fidelity) + platform.calibration.single_qubits[qubit].readout.fidelity = float(fidelity) def virtual_phases( phases: dict[QubitId, float], native: str, platform: Platform, pair: QubitPairId ): - """Update virtual phases for given qubits in pair in results.""" - virtual_z_pulses = { - pulse.qubit.name: pulse - for pulse in getattr(platform.pairs[pair].native_gates, native).pulses - if isinstance(pulse, VirtualZPulse) - } - for qubit_id, phase in phases.items(): - if qubit_id in virtual_z_pulses: - virtual_z_pulses[qubit_id].phase = phase - else: - virtual_z_pulses[qubit_id] = VirtualZPulse( - phase=phase, qubit=platform.qubits[qubit_id] - ) - getattr(platform.pairs[pair].native_gates, native).pulses.append( - virtual_z_pulses[qubit_id] - ) + native_sequence = getattr(platform.natives.two_qubit[pair], native) + new_native = PulseSequence() + if len(native_sequence) > 1: + new_native.append(native_sequence[0]) + else: # pragma: no cover + new_native = native_sequence + for qubit, phase in phases.items(): + new_native.append((platform.qubits[qubit].drive, VirtualZ(phase=phase))) + + platform.update( + {f"native_gates.two_qubit.{f'{pair[0]}-{pair[1]}'}.{native}": new_native} + ) def CZ_duration(duration: int, platform: Platform, pair: QubitPairId): """Update CZ duration for specific pair.""" - for pulse in platform.pairs[pair].native_gates.CZ.pulses: - if pulse.qubit.name == pair[1]: - pulse.duration = int(duration) + platform.update( + {f"native_gates.two_qubit.{f'{pair[0]}-{pair[1]}'}.CZ.0.1.duration": duration} + ) def CZ_amplitude(amp: float, platform: Platform, pair: QubitPairId): """Update CZ amplitude for specific pair.""" - for pulse in platform.pairs[pair].native_gates.CZ.pulses: - if pulse.qubit.name == pair[1]: - pulse.amplitude = float(amp) + platform.update( + {f"native_gates.two_qubit.{f'{pair[0]}-{pair[1]}'}.CZ.0.1.amplitude": amp} + ) def iSWAP_duration(duration: int, platform: Platform, pair: QubitPairId): """Update iSWAP_duration duration for specific pair.""" - for pulse in platform.pairs[pair].native_gates.iSWAP.pulses: - if pulse.qubit.name == pair[1]: - pulse.duration = int(duration) + platform.update( + {f"native_gates.two_qubit.{f'{pair[0]}-{pair[1]}'}.CZ.0.1.duration": duration} + ) def iSWAP_amplitude(amp: float, platform: Platform, pair: QubitPairId): """Update iSWAP_duration amplitude for specific pair.""" - for pulse in platform.pairs[pair].native_gates.iSWAP.pulses: - if pulse.qubit.name == pair[1]: - pulse.amplitude = float(amp) + platform.update( + {f"native_gates.two_qubit.{f'{pair[0]}-{pair[1]}'}.CZ.0.1.amplitude": amp} + ) def t1(t1: int, platform: Platform, qubit: QubitId): """Update t1 value in platform for specific qubit.""" - if isinstance(t1, Iterable): - platform.qubits[qubit].T1 = int(t1[0]) - else: - platform.qubits[qubit].T1 = int(t1) + platform.calibration.single_qubits[qubit].t1 = tuple(t1) def t2(t2: int, platform: Platform, qubit: QubitId): """Update t2 value in platform for specific qubit.""" - if isinstance(t2, Iterable): - platform.qubits[qubit].T2 = int(t2[0]) - else: - platform.qubits[qubit].T2 = int(t2) + platform.calibration.single_qubits[qubit].t2 = tuple(t2) def t2_spin_echo(t2_spin_echo: float, platform: Platform, qubit: QubitId): """Update t2 echo value in platform for specific qubit.""" - if isinstance(t2_spin_echo, Iterable): - platform.qubits[qubit].T2_spin_echo = int(t2_spin_echo[0]) - else: - platform.qubits[qubit].T2_spin_echo = int(t2_spin_echo) + platform.calibration.single_qubits[qubit].t2_spin_echo = tuple(t2_spin_echo) def drag_pulse_beta(beta: float, platform: Platform, qubit: QubitId): """Update beta parameter value in platform for specific qubit.""" - pulse = platform.qubits[qubit].native_gates.RX.pulse(start=0) - rel_sigma = pulse.shape.rel_sigma - drag_pulse = pulses.Drag(rel_sigma=rel_sigma, beta=beta) - platform.qubits[qubit].native_gates.RX.shape = repr(drag_pulse) + platform.update( + { + f"native_gates.single_qubit.{qubit}.RX.0.1.envelope.kind": "drag", + f"native_gates.single_qubit.{qubit}.RX.0.1.envelope.beta": beta, + } + ) def sweetspot(sweetspot: float, platform: Platform, qubit: QubitId): """Update sweetspot parameter in platform for specific qubit.""" - platform.qubits[qubit].sweetspot = float(sweetspot) + platform.calibration.single_qubits[qubit].qubit.sweetspot = float(sweetspot) + + +def flux_offset(offset: float, platform: Platform, qubit: QubitId): + """Update flux offset parameter in platform for specific qubit.""" + platform.update({f"configs.{platform.qubits[qubit].flux}.offset": offset}) def frequency_12_transition(frequency: int, platform: Platform, qubit: QubitId): - platform.qubits[qubit].native_gates.RX12.frequency = int(frequency) + channel = platform.qubits[qubit].drive_qudits[1, 2] + platform.update({f"configs.{channel}.frequency": frequency}) + platform.calibration.single_qubits[qubit].qubit.frequency_12 = int(frequency) def drive_12_amplitude(amplitude: float, platform: Platform, qubit: QubitId): - platform.qubits[qubit].native_gates.RX12.amplitude = float(amplitude) + platform.update( + {f"native_gates.single_qubit.{qubit}.RX12.0.1.amplitude": amplitude} + ) def drive_12_duration( duration: Union[int, tuple, list], platform: Platform, qubit: QubitId ): """Update drive duration value in platform for specific qubit.""" - platform.qubits[qubit].native_gates.RX12.duration = int(duration) - - -def twpa_frequency(frequency: int, platform: Platform, qubit: QubitId): - platform.qubits[qubit].twpa.local_oscillator.frequency = int(frequency) - - -def twpa_power(power: float, platform: Platform, qubit: QubitId): - platform.qubits[qubit].twpa.local_oscillator.power = float(power) - - -def anharmonicity(anharmonicity: float, platform: Platform, qubit: QubitId): - platform.qubits[qubit].anharmonicity = int(anharmonicity) - - -def asymmetry(asymmetry: float, platform: Platform, qubit: QubitId): - platform.qubits[qubit].asymmetry = float(asymmetry) + platform.update( + {f"native_gates.single_qubit.{qubit}.RX12.0.1.duration": int(duration)} + ) def coupling(g: float, platform: Platform, qubit: QubitId): - platform.qubits[qubit].g = float(g) + platform.calibration.single_qubits[qubit].readout.coupling = float(g) def kernel(kernel: np.ndarray, platform: Platform, qubit: QubitId): - platform.qubits[qubit].kernel = kernel + ro_channel = platform.qubits[qubit].acquisition + platform.update({f"configs.{ro_channel}.kernel": kernel}) diff --git a/src/qibocal/web/compared_report.py b/src/qibocal/web/compared_report.py index 562416c22..80af8be44 100644 --- a/src/qibocal/web/compared_report.py +++ b/src/qibocal/web/compared_report.py @@ -7,9 +7,9 @@ import pandas as pd import plotly.graph_objects as go from plotly.subplots import make_subplots -from qibolab.qubits import QubitId, QubitPairId from qibocal.auto.history import History +from qibocal.auto.operation import QubitId, QubitPairId from qibocal.auto.output import Output from qibocal.auto.task import Completed, TaskId from qibocal.cli.report import generate_figures_and_report diff --git a/src/qibocal/web/report.py b/src/qibocal/web/report.py index 64a54ffaa..591a19319 100644 --- a/src/qibocal/web/report.py +++ b/src/qibocal/web/report.py @@ -7,12 +7,18 @@ WEB_DIR = pathlib.Path(__file__).parent STYLES = WEB_DIR / "static" / "styles.css" +SCRIPT = WEB_DIR / "script.js" TEMPLATES = WEB_DIR / "templates" -def report_css_styles(styles_path: pathlib.Path): +def report_css_styles(path: pathlib.Path): """HTML string containing path of css file.""" - return f"" + return f"" + + +def report_script(path: pathlib.Path): + """HTML string containing path of js file.""" + return f"" @dataclass diff --git a/src/qibocal/web/script.js b/src/qibocal/web/script.js new file mode 100644 index 000000000..b61595653 --- /dev/null +++ b/src/qibocal/web/script.js @@ -0,0 +1,42 @@ +function redirectToRuncard() { + window.location.href = './action.yml'; +} + +function redirectToPlatform() { + window.location.href = './new_platform/parameters.json'; +} + + +// To Download PDF +var exportPDFButton = document.getElementById("export-pdf"); + +exportPDFButton.addEventListener("click", function() { + +document.body.classList.add("impresion"); + +var doc = new jsPDF({orientation: 'landscape',}); + +var iframes = document.querySelectorAll("iframe.gh-fit") +source = "" +for(var id = 0; id < iframes.length; id++) { + var win = iframes[id].contentWindow + var doc = win.document + var html = doc.documentElement + var body = doc.body + var ifrm = iframes[id] // or win.frameElement + source = source + html +} + +print(source) + +doc.fromHTML(source, 0, 0, { +width: 210, +margins: { + left: 10, + right: 10, + top: 10, + bottom: 10 +} +}); +doc.save("report.pdf"); +}); diff --git a/src/qibocal/web/static/styles.css b/src/qibocal/web/static/styles.css index 67964f6ac..7b48bba07 100644 --- a/src/qibocal/web/static/styles.css +++ b/src/qibocal/web/static/styles.css @@ -155,11 +155,10 @@ font-family: system-ui,-apple-system,"Segoe UI",Roboto,"Helvetica Neue","Noto Sans","Liberation Sans",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol","Noto Color Emoji"; } -.button-export -{ - background:#6400FF; - color:white; - font-family: system-ui,-apple-system,"Segoe UI",Roboto,"Helvetica Neue","Noto Sans","Liberation Sans",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol","Noto Color Emoji"; +.button-container button { + background: #6400FF; + color: white; + font-family: system-ui, -apple-system, "Segoe UI", Roboto, "Helvetica Neue", "Noto Sans", "Liberation Sans", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 0.8em; } diff --git a/src/qibocal/web/templates/template.html b/src/qibocal/web/templates/template.html index 414dd1696..5f375a020 100644 --- a/src/qibocal/web/templates/template.html +++ b/src/qibocal/web/templates/template.html @@ -32,11 +32,18 @@
- Qibocal Reports + Qibocal Reports + + + + +
@@ -46,10 +53,10 @@