From 62a8e182badace7c32387679fc38b67820eb8138 Mon Sep 17 00:00:00 2001 From: victor Date: Fri, 1 Mar 2024 16:47:23 +0100 Subject: [PATCH 1/3] chsh_error_bars --- chsh_error_bars_fidelity.ipynb | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) diff --git a/chsh_error_bars_fidelity.ipynb b/chsh_error_bars_fidelity.ipynb index 4e2ccaa..0efece0 100644 --- a/chsh_error_bars_fidelity.ipynb +++ b/chsh_error_bars_fidelity.ipynb @@ -215,6 +215,33 @@ "name": "stderr", "output_type": "stream", "text": [ + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "{\n", + " \"title\": \"Unauthorized\",\n", + " \"status\": 401,\n", + " \"detail\": \"JWTExpired: Error verifying the authorisation access token. Expired at 1709307549, time: 1709307617(leeway: 60) 401 Client Error: for url: https://qilimanjaroqaas.ddns.net:8080/api/v1/jobs/8902\"\n", + "}\n", + "{\"title\":\"Unauthorized\",\"status\":401,\"detail\":\"JWTExpired: Error verifying the authorisation access token. Expired at 1709307549, time: 1709307617(leeway: 60)\"}\n", + "\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", + "Your job with id 8902 is still pending. Job queue position: 3\n", "Your job with id 8902 is still pending. Job queue position: 3\n", "Your job with id 8902 is still pending. Job queue position: 3\n" ] From cec26dd2fd8b5954f165185a63d96b13ce026dac Mon Sep 17 00:00:00 2001 From: victor Date: Fri, 7 Jun 2024 12:35:30 +0200 Subject: [PATCH 2/3] update changes from colab notebook --- chsh.ipynb | 128 ++++- chsh_copy.ipynb | 450 +++++++++++++++++ chsh_error_bar_sigma.ipynb | 498 +++++++++++++++++++ chsh_error_bars.ipynb | 391 +++++++++++++++ chsh_error_bars_draft.ipynb | 702 +++++++++++++++++++++++++++ chsh_error_bars_fidelity.ipynb | 134 ++--- chsh_error_bars_fidelity_clean.ipynb | 639 ++++++++++++++---------- chsh_error_bars_m.ipynb | 515 ++++++++++++++++++++ 8 files changed, 3109 insertions(+), 348 deletions(-) create mode 100644 chsh_copy.ipynb create mode 100644 chsh_error_bar_sigma.ipynb create mode 100644 chsh_error_bars.ipynb create mode 100644 chsh_error_bars_draft.ipynb create mode 100644 chsh_error_bars_m.ipynb diff --git a/chsh.ipynb b/chsh.ipynb index c7411ad..bc47a7d 100644 --- a/chsh.ipynb +++ b/chsh.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -17,7 +17,7 @@ "\n", "from itertools import product\n", "\n", - "api = API(ConnectionConfiguration(username=\"qat\", api_key=\"meow\"))\n", + "api = API(ConnectionConfiguration(username=\"vsanchez\", api_key=\"ea712370-7516-4cbf-91a6-72a82e39ba02\"))\n", "\n", "\n", "api.select_device_id(9)" @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -124,12 +124,12 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ - "CONTROL_QUBIT = 2\n", - "TARGET_QUBIT = 0\n", + "CONTROL_QUBIT = 0\n", + "TARGET_QUBIT = 2\n", "THETA_VALUES = np.linspace(-np.pi, np.pi, num=20)\n", "BELL_STATE = \"psi_minus\"\n", "\n", @@ -145,7 +145,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -168,7 +168,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -184,19 +184,109 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Your job with id 8009 is completed.\n" + "Your job with id 8666 failed.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Interruption in stage='execute': ('invalid literal for int() with base 10: \\'#41060{\"awg\":[{\"cont_mode\":{\"en_path\":[false,false],\"wave_idx_path\":[0,0]},\"gain_path\":[1.0,1.0],\"marker_ovr\":{\"en\":true,\"val\":15},\"mixer\":{\"corr_gain_ratio\":1.0,\"corr_phase_offset_degree\":-0.0,\"en\":', 'setting qblox_cluster_cluster_controller_0_module10_sequencer2_sync_en to True') (). Traceback:\n", + " File \"/home/qili-docker/qgqs/services/device_service/src/utils/decorators.py\", line 20, in wrapper\n", + " return func(*args, **kwargs)\n", + "\n", + " File \"/home/qili-docker/qgqs/services/device_service/src/api/slurm_executions.py\", line 70, in _execute\n", + " return execution_class.execute_circuit(\n", + "\n", + " File \"/home/qili-docker/qgqs/services/device_service/src/service/executions/qililab_executions.py\", line 48, in execute_circuit\n", + " results = ql.execute(\n", + "\n", + " File \"/home/qili-docker/miniconda3/envs/submitit/lib/python3.10/site-packages/qililab/execute_circuit.py\", line 79, in execute\n", + " raise e\n", + "\n", + " File \"/home/qili-docker/miniconda3/envs/submitit/lib/python3.10/site-packages/qililab/execute_circuit.py\", line 74, in execute\n", + " results.append(platform.execute(circuit, num_avg=1, repetition_duration=200_000, num_bins=nshots))\n", + "\n", + " File \"/home/qili-docker/miniconda3/envs/submitit/lib/python3.10/site-packages/qililab/platform/platform.py\", line 747, in execute\n", + " bus.upload()\n", + "\n", + " File \"/home/qili-docker/miniconda3/envs/submitit/lib/python3.10/site-packages/qililab/platform/components/bus.py\", line 209, in upload\n", + " self.system_control.upload(port=self.port)\n", + "\n", + " File \"/home/qili-docker/miniconda3/envs/submitit/lib/python3.10/site-packages/qililab/system_control/system_control.py\", line 81, in upload\n", + " instrument.upload(port=port)\n", + "\n", + " File \"/home/qili-docker/miniconda3/envs/submitit/lib/python3.10/site-packages/qililab/instruments/qblox/qblox_module.py\", line 427, in upload\n", + " self.device.sequencers[sequencer.identifier].sync_en(True)\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qcodes/parameters/parameter_base.py\", line 467, in __call__\n", + " self.set(*args, **kwargs)\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qcodes/parameters/parameter_base.py\", line 728, in set_wrapper\n", + " raise e\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qcodes/parameters/parameter_base.py\", line 713, in set_wrapper\n", + " set_function(raw_val_step, **kwargs)\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qcodes/parameters/command.py\", line 209, in __call__\n", + " return self.exec_function(*args)\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qblox_instruments/native/generic_func.py\", line 539, in decorator_wrapper\n", + " return func(*args, **kwargs)\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qblox_instruments/native/cluster.py\", line 408, in _set_sequencer_config_val\n", + " return gf.set_sequencer_config_val(funcs, sequencer, keys, val)\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qblox_instruments/native/generic_func.py\", line 1056, in set_sequencer_config_val\n", + " cfg = get_sequencer_config(funcs, sequencer)\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qblox_instruments/native/generic_func.py\", line 1026, in get_sequencer_config\n", + " return funcs._get_sequencer_config(sequencer)\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qblox_instruments/scpi/cluster.py\", line 54, in decorator_wrapper\n", + " args[0]._check_error_queue(err)\n", + "\n", + " File \"/home/qili-docker/.local/lib/python3.10/site-packages/qblox_instruments/scpi/cluster.py\", line 5316, in _check_error_queue\n", + " while int(self._read('SYSTem:ERRor:COUNt?')) != 0:\n", + "\n" + ] + } + ], + "source": [ + "results = api.get_job(result_id)\n", + "print(results.logs)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "{\n", + " \"title\": \"Unauthorized\",\n", + " \"status\": 401,\n", + " \"detail\": \"JWTExpired: Error verifying the authorisation access token. Expired at 1708702523, time: 1708703521(leeway: 60) 401 Client Error: for url: https://qilimanjaroqaas.ddns.net:8080/api/v1/jobs/8671\"\n", + "}\n", + "{\"title\":\"Unauthorized\",\"status\":401,\"detail\":\"JWTExpired: Error verifying the authorisation access token. Expired at 1708702523, time: 1708703521(leeway: 60)\"}\n", + "\n", + "Your job with id 8671 is completed.\n" ] } ], "source": [ "## retrieve data\n", + "\n", "results = api.get_result(result_id)\n", "data_probabilities = process_returned_dataformat(results, nqubits=2)\n", "\n", @@ -224,9 +314,17 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Qibo 0.1.12.dev0|INFO|2024-02-23 16:22:55]: Using numpy backend on /CPU:0\n" + ] + } + ], "source": [ "circ_list = SPAM_circuits(0, 1)\n", "ideal_results_spam = np.zeros((len(circ_list), 4))\n", @@ -255,12 +353,12 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -321,7 +419,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.13" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/chsh_copy.ipynb b/chsh_copy.ipynb new file mode 100644 index 0000000..c7b7d12 --- /dev/null +++ b/chsh_copy.ipynb @@ -0,0 +1,450 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from qibo.gates import M, X, RY, CZ, I, H\n", + "from qibo.models import Circuit\n", + "from qiboconnection.api import API\n", + "from qiboconnection.connection import ConnectionConfiguration\n", + "\n", + "from benchmarks.utils.qst_qpt_helper_functions import process_returned_dataformat\n", + "\n", + "from itertools import product\n", + "\n", + "# api = API(ConnectionConfiguration(username=\"qat\", api_key=\"meow\"))\n", + "api = API(ConnectionConfiguration(username=\"vsanchez\", api_key=\"ea712370-7516-4cbf-91a6-72a82e39ba02\"))\n", + "\n", + "\n", + "api.select_device_id(9)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "def get_chsh_circuits(bell_state, control_qubit, target_qubit, theta):\n", + " assert bell_state in (\n", + " \"phi_plus\",\n", + " \"phi_minus\",\n", + " \"psi_plus\",\n", + " \"psi_minus\",\n", + " ), \"bell_state should be phi_plus, phi_minus, psi_plus, psi_minus\"\n", + " nqubits = max(control_qubit, target_qubit) + 1\n", + "\n", + " circuits = []\n", + " for gate_a, gate_b in product([I, H], repeat=2):\n", + " circuit = Circuit(nqubits)\n", + "\n", + " if bell_state == \"phi_plus\" or bell_state == \"psi_minus\":\n", + " G1 = RY(control_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G1 = RY(control_qubit, theta=np.pi / 2)\n", + " if bell_state == \"phi_plus\" or bell_state == \"phi_minus\":\n", + " G2_prime = RY(target_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G2_prime = RY(target_qubit, theta=np.pi / 2)\n", + " ## build bell state\n", + " circuit.add(G1)\n", + " circuit.add(RY(target_qubit, theta=np.pi / 2))\n", + " circuit.add(CZ(control_qubit, target_qubit))\n", + " circuit.add(G2_prime)\n", + "\n", + " ## decoder part\n", + " circuit.add(RY(control_qubit, theta=theta))\n", + " circuit.add(gate_a(control_qubit))\n", + " circuit.add(gate_b(target_qubit))\n", + " circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " circuits.append(circuit)\n", + "\n", + " return circuits\n", + "\n", + "\n", + "def SPAM_circuits(control_qubit, target_qubit):\n", + " \"\"\"Circuits to get the SPAM matrix in order to perform measurement correction.\"\"\"\n", + " calibration_circuits = []\n", + " for gate_a, gate_b in product([I, X], repeat=2):\n", + " calibration_circuit = Circuit(5)\n", + " calibration_circuit.add(gate_a(control_qubit))\n", + " calibration_circuit.add(gate_b(target_qubit))\n", + " calibration_circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " calibration_circuits.append(calibration_circuit)\n", + " return calibration_circuits\n", + "\n", + "\n", + "def compute_witnesses(chsh_results, measurement_calibration_weights, BELL_STATE, raw=False):\n", + " \"\"\"Returns arrays of computed witness values.\n", + "\n", + " Args:\n", + " chsh_results (array): matrix containing the probabilities the chsh circuits. It must be\n", + " of dimensions len(theta_values) x 4 (decoder circuits) x 4 (probabilities)\n", + " measurement_calibration_weights (array): measurement calibration matrix.\n", + " BELL_STATE (string): can be \"phi_plus\", \"phi_minus\", \"psi_plus\" or \"psi_minus\". It needs\n", + " to be specified because the witness isn't the same for all 4 Bell states.\n", + " raw (bool): whether or not calculate the witnesses from the raw data instead of applying the\n", + " measurement corrections. Defaults to False.\n", + " Returns:\n", + " witness1 (array): array length len(theta_values) containing the first witness\n", + " witness2 (array): array length len(theta_values) containing the second witness\n", + " \"\"\"\n", + " len_theta_values = np.shape(chsh_results)[0]\n", + " witness1 = np.zeros(len_theta_values)\n", + " witness2 = np.zeros(len_theta_values)\n", + "\n", + " if BELL_STATE == \"phi_plus\" or BELL_STATE == \"psi_minus\":\n", + " signs1 = np.array([1, 1, -1, 1])\n", + " signs2 = np.array([1, -1, 1, 1])\n", + " else:\n", + " signs1 = np.array([-1, 1, 1, 1])\n", + " signs2 = np.array([1, 1, 1, -1])\n", + "\n", + " for i, chsh_result in enumerate(chsh_results):\n", + " if raw != True:\n", + " # apply measurement calibration\n", + " chsh_result = measurement_calibration_weights @ chsh_result.T\n", + " # calculate expectation values from probabilities\n", + " expectations = np.array([1, -1, -1, 1]).T @ chsh_result\n", + "\n", + " else:\n", + " # calculate expectation values from probabilities\n", + " expectations = chsh_result @ np.array([1, -1, -1, 1])\n", + " # compute witnesses\n", + " witness1[i] = signs1.T @ expectations\n", + " witness2[i] = signs2.T @ expectations\n", + " return witness1, witness2" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "CONTROL_QUBIT = 2\n", + "TARGET_QUBIT = 0\n", + "THETA_VALUES = np.linspace(-np.pi, np.pi, num=20)\n", + "BELL_STATE = \"psi_minus\"\n", + "\n", + "NUM_SHOTS = 8000" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Build circuits for CHSH and measurement correction" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "all_circuits_chsh = []\n", + "for theta in THETA_VALUES:\n", + " circuits_th = get_chsh_circuits(BELL_STATE, CONTROL_QUBIT, TARGET_QUBIT, theta)\n", + " all_circuits_chsh.extend(circuits_th)\n", + "\n", + "all_circuits = SPAM_circuits(CONTROL_QUBIT, TARGET_QUBIT)\n", + "\n", + "all_circuits.extend(all_circuits_chsh)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run circuits" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "result_id = api.execute(all_circuits, nshots=NUM_SHOTS)[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Process real data" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "result_id = 8695" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Your job with id 8695 is completed.\n" + ] + } + ], + "source": [ + "## retrieve data\n", + "results = api.get_result(result_id)\n", + "data_probabilities = process_returned_dataformat(results, nqubits=2)\n", + "\n", + "## measurement calibration data processing\n", + "spam_data_probabilities = data_probabilities[:4]\n", + "measurement_calibration_weights = np.linalg.inv(spam_data_probabilities)\n", + "\n", + "## chsh circuits data processing\n", + "chsh_data_probabilities = data_probabilities[4:]\n", + "chsh_data_probabilities_theta = chsh_data_probabilities.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "## compute witness\n", + "w1_raw, w2_raw = compute_witnesses(chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=True)\n", + "w1_corrected, w2_corrected = compute_witnesses(\n", + " chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=False\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def build_cov_matrix(prob_array):\n", + " covariance_mat = np.zeros((4, 4))\n", + " covariance_mat_diag = np.diag(prob_array * (1 - prob_array))\n", + " for i in range(4):\n", + " for j in range(i):\n", + " covariance_mat[i, j] = -prob_array[i] * prob_array[j]\n", + " covariance_mat += covariance_mat.T + covariance_mat_diag\n", + " return covariance_mat" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy.linalg import eig" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Error bar calculation" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.241351 , -0.0518925 , -0.050061 , -0.1393975 ],\n", + " [-0.0518925 , 0.11124375, -0.0156825 , -0.04366875],\n", + " [-0.050061 , -0.0156825 , 0.107871 , -0.0421275 ],\n", + " [-0.1393975 , -0.04366875, -0.0421275 , 0.22519375]])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from scipy import stats\n", + "stats.multinomial.cov(n=1, p=data_probabilities[-1])" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "np.shape(data_probabilities)\n", + "\n", + "error_bars = []\n", + "\n", + "for idx in range(20):\n", + " chsh_point = data_probabilities[(1 + idx) * 4: (2 + idx) * 4]\n", + " cov_mats = [build_cov_matrix(probs) for probs in chsh_point]\n", + " independent_vars = []\n", + " expression_in_independent_vars = []\n", + "\n", + " var_expected_obs = []\n", + "\n", + " for i, cov in enumerate(cov_mats):\n", + " evals, evecs = eig(cov)\n", + " U = evecs.T\n", + " independent_vars.append(evals)\n", + " expression_in_independent_vars.append(U)\n", + "\n", + " probs = chsh_point[i]\n", + "\n", + " var_expected_obs = np.sqrt(np.sum(np.sum(U, axis=0) ** 2 @ evals**2))\n", + "\n", + " var_witness = np.sqrt(np.sum(var_expected_obs**2))\n", + " error_bars.append(var_witness)\n", + " # print(var_witness)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run simulation, get ideal witnesses" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Qibo 0.1.12.dev0|INFO|2024-02-29 11:51:34]: Using numpy backend on /CPU:0\n" + ] + } + ], + "source": [ + "circ_list = SPAM_circuits(0, 1)\n", + "ideal_results_spam = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_spam[i] += c.execute().probabilities()\n", + "ideal_measurement_calibration_weights = np.linalg.inv(ideal_results_spam)\n", + "\n", + "circ_list = list(np.copy(all_circuits_chsh))\n", + "ideal_results_chsh = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_chsh[i] += c.execute().probabilities()\n", + "\n", + "ideal_results_chsh_theta = ideal_results_chsh.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "w1_ideal, w2_ideal = compute_witnesses(\n", + " ideal_results_chsh_theta, ideal_measurement_calibration_weights, BELL_STATE, raw=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/victor/envs/qililab/lib/python3.10/site-packages/matplotlib/cbook.py:1699: ComplexWarning: Casting complex values to real discards the imaginary part\n", + " return math.isfinite(val)\n", + "/home/victor/envs/qililab/lib/python3.10/site-packages/numpy/ma/core.py:3371: ComplexWarning: Casting complex values to real discards the imaginary part\n", + " _data[indx] = dval\n", + "/home/victor/envs/qililab/lib/python3.10/site-packages/matplotlib/cbook.py:1345: ComplexWarning: Casting complex values to real discards the imaginary part\n", + " return np.asarray(x, float)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fname = f\"chsh_{CONTROL_QUBIT}_{TARGET_QUBIT}_{BELL_STATE}_nshots{NUM_SHOTS}_jobid{result_id}.png\"\n", + "savefig = False\n", + "\n", + "fig, ax = plt.subplots()\n", + "ax.axhline(2, color=\"red\", linestyle=\"--\", label=\"classical bounds\")\n", + "ax.axhline(-2, color=\"red\", linestyle=\"--\")\n", + "ax.axhline(2 * np.sqrt(2), color=\"k\", linestyle=\"-.\", label=\"quantum bounds\")\n", + "ax.axhline(-2 * np.sqrt(2), color=\"k\", linestyle=\"-.\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_ideal, label=\"ideal\")\n", + "ax.plot(THETA_VALUES, w2_ideal)\n", + "\n", + "ax.plot(THETA_VALUES, w1_raw, \"x\", ms=3, c=\"C0\", label=\"raw\")\n", + "ax.plot(THETA_VALUES, w2_raw, \"x\", ms=3, c=\"C1\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_corrected, \".\", c=\"C0\", label=\"corrected\")\n", + "ax.errorbar(THETA_VALUES, w1_corrected, error_bars, capsize=3, c=\"C0\", ls=\"none\") # \"x--\",\n", + "\n", + "ax.plot(THETA_VALUES, w2_corrected, \".\", c=\"C1\")\n", + "ax.legend()\n", + "\n", + "ax.set_xlabel(\"$\\\\theta$\")\n", + "ax.set_ylabel(\"witness 1 (blue), witness 2 (orange)\")\n", + "\n", + "ax.set_title(f\"({CONTROL_QUBIT}, {TARGET_QUBIT}), bell: {BELL_STATE}\")\n", + "if savefig:\n", + " fig.savefig(fname, bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "LastMile", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/chsh_error_bar_sigma.ipynb b/chsh_error_bar_sigma.ipynb new file mode 100644 index 0000000..b29deba --- /dev/null +++ b/chsh_error_bar_sigma.ipynb @@ -0,0 +1,498 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from qibo.gates import M, X, RY, CZ, I, H\n", + "from qibo.models import Circuit\n", + "from qiboconnection.api import API\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from qiboconnection.connection import ConnectionConfiguration\n", + "\n", + "from benchmarks.utils.qst_qpt_helper_functions import process_returned_dataformat\n", + "\n", + "from itertools import product\n", + "from scipy.stats import multivariate_normal\n", + "api = API(ConnectionConfiguration(username=\"vsanchez\", api_key=\"ea712370-7516-4cbf-91a6-72a82e39ba02\"))\n", + "from scipy import stats\n", + "\n", + "api.select_device_id(9)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "def get_chsh_circuits(bell_state, control_qubit, target_qubit, theta):\n", + " assert bell_state in (\n", + " \"phi_plus\",\n", + " \"phi_minus\",\n", + " \"psi_plus\",\n", + " \"psi_minus\",\n", + " ), \"bell_state should be phi_plus, phi_minus, psi_plus, psi_minus\"\n", + " nqubits = max(control_qubit, target_qubit) + 1\n", + "\n", + " circuits = []\n", + " for gate_a, gate_b in product([I, H], repeat=2):\n", + " circuit = Circuit(nqubits)\n", + "\n", + " if bell_state == \"phi_plus\" or bell_state == \"psi_minus\":\n", + " G1 = RY(control_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G1 = RY(control_qubit, theta=np.pi / 2)\n", + " if bell_state == \"phi_plus\" or bell_state == \"phi_minus\":\n", + " G2_prime = RY(target_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G2_prime = RY(target_qubit, theta=np.pi / 2)\n", + " ## build bell state\n", + " circuit.add(G1)\n", + " circuit.add(RY(target_qubit, theta=np.pi / 2))\n", + " circuit.add(CZ(control_qubit, target_qubit))\n", + " circuit.add(G2_prime)\n", + "\n", + " ## decoder part\n", + " circuit.add(RY(control_qubit, theta=theta))\n", + " circuit.add(gate_a(control_qubit))\n", + " circuit.add(gate_b(target_qubit))\n", + " circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " circuits.append(circuit)\n", + "\n", + " return circuits\n", + "\n", + "\n", + "def SPAM_circuits(control_qubit, target_qubit):\n", + " \"\"\"Circuits to get the SPAM matrix in order to perform measurement correction.\"\"\"\n", + " calibration_circuits = []\n", + " for gate_a, gate_b in product([I, X], repeat=2):\n", + " calibration_circuit = Circuit(5)\n", + " calibration_circuit.add(gate_a(control_qubit))\n", + " calibration_circuit.add(gate_b(target_qubit))\n", + " calibration_circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " calibration_circuits.append(calibration_circuit)\n", + " return calibration_circuits\n", + "\n", + "\n", + "def compute_witnesses(chsh_results, measurement_calibration_weights, BELL_STATE, raw=False):\n", + " \"\"\"Returns arrays of computed witness values.\n", + "\n", + " Args:\n", + " chsh_results (array): matrix containing the probabilities the chsh circuits. It must be\n", + " of dimensions len(theta_values) x 4 (decoder circuits) x 4 (probabilities)\n", + " measurement_calibration_weights (array): measurement calibration matrix.\n", + " BELL_STATE (string): can be \"phi_plus\", \"phi_minus\", \"psi_plus\" or \"psi_minus\". It needs\n", + " to be specified because the witness isn't the same for all 4 Bell states.\n", + " raw (bool): whether or not calculate the witnesses from the raw data instead of applying the\n", + " measurement corrections. Defaults to False.\n", + " Returns:\n", + " witness1 (array): array length len(theta_values) containing the first witness\n", + " witness2 (array): array length len(theta_values) containing the second witness\n", + " \"\"\"\n", + " len_theta_values = np.shape(chsh_results)[0]\n", + " witness1 = np.zeros(len_theta_values)\n", + " witness2 = np.zeros(len_theta_values)\n", + "\n", + " if BELL_STATE in [\"phi_plus\", \"psi_minus\"]:\n", + " signs1 = np.array([1, 1, -1, 1])\n", + " signs2 = np.array([1, -1, 1, 1])\n", + " else:\n", + " signs1 = np.array([-1, 1, 1, 1])\n", + " signs2 = np.array([1, 1, 1, -1])\n", + "\n", + " for i, chsh_result in enumerate(chsh_results):\n", + " if raw is not True:\n", + " # apply measurement calibration\n", + " chsh_result = measurement_calibration_weights @ chsh_result.T\n", + " # calculate expectation values from probabilities\n", + " expectations = np.array([1, -1, -1, 1]).T @ chsh_result\n", + "\n", + " else:\n", + " # calculate expectation values from probabilities\n", + " expectations = chsh_result @ np.array([1, -1, -1, 1])\n", + " # compute witnesses\n", + " witness1[i] = signs1.T @ expectations\n", + " witness2[i] = signs2.T @ expectations\n", + " return witness1, witness2" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "CONTROL_QUBIT = 2\n", + "TARGET_QUBIT = 0\n", + "THETA_VALUES = np.linspace(-np.pi, np.pi, num=20)\n", + "BELL_STATE = \"psi_minus\"\n", + "\n", + "NUM_SHOTS = 1000" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Build circuits for CHSH and measurement correction" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "all_circuits_chsh = []\n", + "for theta in THETA_VALUES:\n", + " circuits_th = get_chsh_circuits(BELL_STATE, CONTROL_QUBIT, TARGET_QUBIT, theta)\n", + " all_circuits_chsh.extend(circuits_th)\n", + "\n", + "all_circuits = SPAM_circuits(CONTROL_QUBIT, TARGET_QUBIT)\n", + "\n", + "all_circuits.extend(all_circuits_chsh)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run circuits" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "results_id = [api.execute(all_circuits, nshots=NUM_SHOTS)[0] for i in range(20)] #2k shots takes 1min14s\n", + "# result_id = 8695" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[8800,\n", + " 8801,\n", + " 8802,\n", + " 8803,\n", + " 8804,\n", + " 8805,\n", + " 8806,\n", + " 8807,\n", + " 8808,\n", + " 8809,\n", + " 8810,\n", + " 8811,\n", + " 8812,\n", + " 8813,\n", + " 8814,\n", + " 8815,\n", + " 8816,\n", + " 8817,\n", + " 8818,\n", + " 8819]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results_id" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Your job with id 8800 is completed.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-02-28 16:02:33,096 - qm - INFO - Starting session: 99be2aaa-d2f2-44ab-8d0e-39706493cd49\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Your job with id 8801 is completed.\n", + "Your job with id 8802 is still pending. 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Job queue position: 20\n" + ] + }, + { + "data": { + "text/plain": [ + "[JobData(completed_at='2024-02-28T15:00:23.873104+00:00', created_at='2024-02-28T14:59:09.372971+00:00', description=[, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ], device_id=9, execution_time=71.707486, execution_type='qililab', favourite=False, job_execution_time_mark='2024-02-28T14:59:12.949133+00:00', job_id=8800, job_postprocessing_time_mark='2024-02-28T15:00:23.872619+00:00', job_preprocessing_time_mark='2024-02-28T14:59:12.165618+00:00', job_processing_time_mark='2024-02-28T14:59:12.165756+00:00', job_results_post_time_mark='2024-02-28T15:00:23.873104+00:00', job_results_reading_time_mark='2024-02-28T15:00:23.664505+00:00', job_type='circuit', logs=None, name='-', number_shots=1000, queue_position=0, result=[{'probabilities': {'00': 0.74, '01': 0.107, '10': 0.132, '11': 0.021}}, 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0.223, '10': 0.148, '11': 0.288}}, {'probabilities': {'00': 0.282, '01': 0.264, '10': 0.231, '11': 0.223}}, {'probabilities': {'00': 0.119, '01': 0.445, '10': 0.337, '11': 0.099}}, {'probabilities': {'00': 0.295, '01': 0.247, '10': 0.244, '11': 0.214}}, {'probabilities': {'00': 0.349, '01': 0.177, '10': 0.132, '11': 0.342}}, {'probabilities': {'00': 0.298, '01': 0.237, '10': 0.212, '11': 0.253}}, {'probabilities': {'00': 0.14, '01': 0.382, '10': 0.339, '11': 0.139}}, {'probabilities': {'00': 0.261, '01': 0.266, '10': 0.254, '11': 0.219}}, {'probabilities': {'00': 0.391, '01': 0.142, '10': 0.095, '11': 0.372}}, {'probabilities': {'00': 0.29, '01': 0.244, '10': 0.223, '11': 0.243}}, {'probabilities': {'00': 0.181, '01': 0.358, '10': 0.322, '11': 0.139}}, {'probabilities': {'00': 0.277, '01': 0.275, '10': 0.245, '11': 0.203}}, {'probabilities': {'00': 0.401, '01': 0.109, '10': 0.086, '11': 0.404}}, {'probabilities': {'00': 0.256, '01': 0.258, '10': 0.24, '11': 0.246}}, {'probabilities': 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job_execution_time_mark=None, job_id=8817, job_postprocessing_time_mark=None, job_preprocessing_time_mark=None, job_processing_time_mark=None, job_results_post_time_mark=None, job_results_reading_time_mark=None, job_type='circuit', logs=None, name='-', number_shots=1000, queue_position=18, result=None, slurm_job_id=18354, status='queued', summary='-', updated_at='2024-02-28T14:59:29.377848+00:00', user_id=31),\n", + " JobData(completed_at=None, created_at='2024-02-28T14:59:30.465645+00:00', description=[, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ], device_id=9, execution_time=None, execution_type='default', favourite=False, job_execution_time_mark=None, job_id=8818, job_postprocessing_time_mark=None, job_preprocessing_time_mark=None, job_processing_time_mark=None, job_results_post_time_mark=None, job_results_reading_time_mark=None, job_type='circuit', logs=None, name='-', number_shots=1000, queue_position=19, result=None, slurm_job_id=18355, status='queued', summary='-', updated_at='2024-02-28T14:59:30.499856+00:00', user_id=31),\n", + " JobData(completed_at=None, created_at='2024-02-28T14:59:31.709029+00:00', description=[, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ], device_id=9, execution_time=None, execution_type='default', favourite=False, job_execution_time_mark=None, job_id=8819, job_postprocessing_time_mark=None, job_preprocessing_time_mark=None, job_processing_time_mark=None, job_results_post_time_mark=None, job_results_reading_time_mark=None, job_type='circuit', logs=None, name='-', number_shots=1000, queue_position=20, result=None, slurm_job_id=18356, status='queued', summary='-', updated_at='2024-02-28T14:59:31.744521+00:00', user_id=31)]" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results = [api.get_job(result_id) for result_id in results_id]\n", + "results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Process real data" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'result_id' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[8], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m## retrieve data\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m results \u001b[38;5;241m=\u001b[39m api\u001b[38;5;241m.\u001b[39mget_result(\u001b[43mresult_id\u001b[49m)\n\u001b[1;32m 3\u001b[0m data_probabilities \u001b[38;5;241m=\u001b[39m process_returned_dataformat(results, nqubits\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m## measurement calibration data processing\u001b[39;00m\n", + "\u001b[0;31mNameError\u001b[0m: name 'result_id' is not defined" + ] + } + ], + "source": [ + "## retrieve data\n", + "results = api.get_result(result_id)\n", + "data_probabilities = process_returned_dataformat(results, nqubits=2)\n", + "\n", + "## measurement calibration data processing\n", + "spam_data_probabilities = data_probabilities[:4]\n", + "measurement_calibration_weights = np.linalg.inv(spam_data_probabilities)\n", + "\n", + "## chsh circuits data processing\n", + "chsh_data_probabilities = data_probabilities[4:]\n", + "chsh_data_probabilities_theta = chsh_data_probabilities.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "\n", + "## compute witness\n", + "w1_raw, w2_raw = compute_witnesses(chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=True)\n", + "w1_corrected, w2_corrected = compute_witnesses(\n", + " chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run simulation, get ideal witnesses" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Qibo 0.1.12.dev0|INFO|2024-02-27 17:13:29]: Using numpy backend on /CPU:0\n" + ] + } + ], + "source": [ + "circ_list = SPAM_circuits(0, 1)\n", + "ideal_results_spam = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_spam[i] += c.execute().probabilities()\n", + "ideal_measurement_calibration_weights = np.linalg.inv(ideal_results_spam)\n", + "\n", + "circ_list = list(np.copy(all_circuits_chsh))\n", + "ideal_results_chsh = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_chsh[i] += c.execute().probabilities()\n", + "\n", + "ideal_results_chsh_theta = ideal_results_chsh.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "w1_ideal, w2_ideal = compute_witnesses(\n", + " ideal_results_chsh_theta, ideal_measurement_calibration_weights, BELL_STATE, raw=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get error bars" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def return_mock_results():\n", + " # returns simulated results using distribution from experimental results' probabilities\n", + " mock_results = data_probabilities[4:].copy()\n", + " measurement_calibration_weights = np.linalg.inv(data_probabilities[:4]) \n", + " for i, _ in enumerate(mock_results): \n", + " mock_results[i] = stats.multinomial.rvs(NUM_SHOTS, mock_results[i]) / NUM_SHOTS\n", + "\n", + " return list((compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=False) +\n", + " compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=True)))\n", + " \n", + "def get_err_bars(mock_results):\n", + " data_hist = np.stack(mock_results)\n", + " err_bars = np.empty(len(data_hist.T))\n", + " for i, hist in enumerate(data_hist.T):\n", + " _ , var = stats.norm.fit(hist)\n", + " err_bars[i] =np.sqrt(var)\n", + " return err_bars\n", + "\n", + "# generate n copies of random results\n", + "err_w1, err_w2, err_w1_unc, err_w2_unc = [get_err_bars(mock_results) for mock_results in zip(*[return_mock_results() for _ in range(10_000)])]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fname = f\"chsh_{CONTROL_QUBIT}_{TARGET_QUBIT}_{BELL_STATE}_nshots{NUM_SHOTS}_jobid{result_id}.png\"\n", + "savefig = False\n", + "\n", + "fig, ax = plt.subplots()\n", + "ax.axhline(2, color=\"red\", linestyle=\"--\", label=\"classical bounds\")\n", + "ax.axhline(-2, color=\"red\", linestyle=\"--\")\n", + "ax.axhline(2 * np.sqrt(2), color=\"k\", linestyle=\"-.\", label=\"quantum bounds\")\n", + "ax.axhline(-2 * np.sqrt(2), color=\"k\", linestyle=\"-.\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_ideal, label=\"ideal\")\n", + "ax.plot(THETA_VALUES, w2_ideal)\n", + "\n", + "ax.plot(THETA_VALUES, w1_raw, \"x\", ms=3, c=\"C0\", label=\"raw\")\n", + "ax.errorbar(THETA_VALUES, w1_raw, err_w1_unc, capsize=3, c=\"C0\", ls=\"none\")\n", + "\n", + "ax.plot(THETA_VALUES, w2_raw, \"x\", ms=3, c=\"C1\")\n", + "ax.errorbar(THETA_VALUES, w2_raw, err_w2_unc, capsize=3, c=\"C1\", ls=\"none\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_corrected, \".\", c=\"C0\", label=\"corrected\")\n", + "ax.errorbar(THETA_VALUES, w1_corrected, err_w1, capsize=3, c=\"C0\", ls=\"none\")\n", + "\n", + "ax.plot(THETA_VALUES, w2_corrected, \".\", c=\"C1\")\n", + "ax.errorbar(THETA_VALUES, w2_corrected, err_w2, capsize=3, c=\"C1\", ls=\"none\")\n", + "\n", + "ax.legend()\n", + "\n", + "ax.set_xlabel(\"$\\\\theta$\")\n", + "ax.set_ylabel(\"witness 1 (blue), witness 2 (orange)\")\n", + "\n", + "ax.set_title(f\"({CONTROL_QUBIT}, {TARGET_QUBIT}), bell: {BELL_STATE}\")\n", + "if savefig:\n", + " fig.savefig(fname, bbox_inches=\"tight\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "LastMile", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/chsh_error_bars.ipynb b/chsh_error_bars.ipynb new file mode 100644 index 0000000..5f5e2f7 --- /dev/null +++ b/chsh_error_bars.ipynb @@ -0,0 +1,391 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from qibo.gates import M, X, RY, CZ, I, H\n", + "from qibo.models import Circuit\n", + "from qiboconnection.api import API\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from qiboconnection.connection import ConnectionConfiguration\n", + "\n", + "from benchmarks.utils.qst_qpt_helper_functions import process_returned_dataformat\n", + "from time import sleep\n", + "\n", + "from itertools import product\n", + "from scipy.stats import multivariate_normal\n", + "api = API(ConnectionConfiguration(username=\"vsanchez\", api_key=\"ea712370-7516-4cbf-91a6-72a82e39ba02\"))\n", + "from scipy import stats\n", + "\n", + "api.select_device_id(9)" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [ + { + "ename": "SyntaxError", + "evalue": "invalid syntax (1839872217.py, line 83)", + "output_type": "error", + "traceback": [ + "\u001b[0;36m Cell \u001b[0;32mIn[111], line 83\u001b[0;36m\u001b[0m\n\u001b[0;31m expectations = chsh_result @ np.array([1, -1, -1, 1])z\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n" + ] + } + ], + "source": [ + "def get_chsh_circuits(bell_state, control_qubit, target_qubit, theta):\n", + " assert bell_state in (\n", + " \"phi_plus\",\n", + " \"phi_minus\",\n", + " \"psi_plus\",\n", + " \"psi_minus\",\n", + " ), \"bell_state should be phi_plus, phi_minus, psi_plus, psi_minus\"\n", + " nqubits = max(control_qubit, target_qubit) + 1\n", + "\n", + " circuits = []\n", + " for gate_a, gate_b in product([I, H], repeat=2):\n", + " circuit = Circuit(nqubits)\n", + "\n", + " if bell_state == \"phi_plus\" or bell_state == \"psi_minus\":\n", + " G1 = RY(control_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G1 = RY(control_qubit, theta=np.pi / 2)\n", + " if bell_state == \"phi_plus\" or bell_state == \"phi_minus\":\n", + " G2_prime = RY(target_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G2_prime = RY(target_qubit, theta=np.pi / 2)\n", + " ## build bell state\n", + " circuit.add(G1)\n", + " circuit.add(RY(target_qubit, theta=np.pi / 2))\n", + " circuit.add(CZ(control_qubit, target_qubit))\n", + " circuit.add(G2_prime)\n", + "\n", + " ## decoder part\n", + " circuit.add(RY(control_qubit, theta=theta))\n", + " circuit.add(gate_a(control_qubit))\n", + " circuit.add(gate_b(target_qubit))\n", + " circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " circuits.append(circuit)\n", + "\n", + " return circuits\n", + "\n", + "\n", + "def SPAM_circuits(control_qubit, target_qubit):\n", + " \"\"\"Circuits to get the SPAM matrix in order to perform measurement correction.\"\"\"\n", + " calibration_circuits = []\n", + " for gate_a, gate_b in product([I, X], repeat=2):\n", + " calibration_circuit = Circuit(5)\n", + " calibration_circuit.add(gate_a(control_qubit))\n", + " calibration_circuit.add(gate_b(target_qubit))\n", + " calibration_circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " calibration_circuits.append(calibration_circuit)\n", + " return calibration_circuits\n", + "\n", + "\n", + "def compute_witnesses(chsh_results, measurement_calibration_weights, BELL_STATE, raw=False):\n", + " \"\"\"Returns arrays of computed witness values.\n", + "\n", + " Args:\n", + " chsh_results (array): matrix containing the probabilities the chsh circuits. It must be\n", + " of dimensions len(theta_values) x 4 (decoder circuits) x 4 (probabilities)\n", + " measurement_calibration_weights (array): measurement calibration matrix.\n", + " BELL_STATE (string): can be \"phi_plus\", \"phi_minus\", \"psi_plus\" or \"psi_minus\". It needs\n", + " to be specified because the witness isn't the same for all 4 Bell states.\n", + " raw (bool): whether or not calculate the witnesses from the raw data instead of applying the\n", + " measurement corrections. Defaults to False.\n", + " Returns:\n", + " witness1 (array): array length len(theta_values) containing the first witness\n", + " witness2 (array): array length len(theta_values) containing the second witness\n", + " \"\"\"\n", + " len_theta_values = np.shape(chsh_results)[0]\n", + " witness1 = np.zeros(len_theta_values)\n", + " witness2 = np.zeros(len_theta_values)\n", + "\n", + " if BELL_STATE in [\"phi_plus\", \"psi_minus\"]:\n", + " signs1 = np.array([1, 1, -1, 1])\n", + " signs2 = np.array([1, -1, 1, 1])\n", + " else:\n", + " signs1 = np.array([-1, 1, 1, 1])\n", + " signs2 = np.array([1, 1, 1, -1])\n", + "\n", + " for i, chsh_result in enumerate(chsh_results):\n", + " if raw is not True:\n", + " # apply measurement calibration\n", + " chsh_result = chsh_result @ measurement_calibration_weights\n", + " # calculate expectation values from probabilities\n", + " expectations = chsh_result @ np.array([1, -1, -1, 1])\n", + "\n", + " else:\n", + " # calculate expectation values from probabilities\n", + " expectations = chsh_result @ np.array([1, -1, -1, 1])\n", + " # compute witnesses\n", + " witness1[i] = signs1.T @ expectations\n", + " witness2[i] = signs2.T @ expectations\n", + " return witness1, witness2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "CONTROL_QUBIT = 2\n", + "TARGET_QUBIT = 0\n", + "THETA_VALUES = np.linspace(-np.pi, np.pi, num=20)\n", + "BELL_STATE = \"psi_minus\" # was psi_minus\n", + "\n", + "NUM_SHOTS = 8000" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Build circuits for CHSH and measurement correction" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "all_circuits_chsh = []\n", + "for theta in THETA_VALUES:\n", + " circuits_th = get_chsh_circuits(BELL_STATE, CONTROL_QUBIT, TARGET_QUBIT, theta)\n", + " all_circuits_chsh.extend(circuits_th)\n", + "\n", + "all_circuits = SPAM_circuits(CONTROL_QUBIT, TARGET_QUBIT)\n", + "\n", + "all_circuits.extend(all_circuits_chsh)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run circuits" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# result_id = api.execute(all_circuits, nshots=NUM_SHOTS)[0]\n", + "result_id = 8695" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# results = None\n", + "# while results is None:\n", + "# results = api.get_result(result_id)\n", + "# sleep(30)\n", + "# results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Process real data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Your job with id 8695 is completed.\n" + ] + } + ], + "source": [ + "## retrieve data\n", + "results = api.get_result(result_id)\n", + "data_probabilities = process_returned_dataformat(results, nqubits=2)\n", + "\n", + "## measurement calibration data processing\n", + "spam_data_probabilities = data_probabilities[:4]\n", + "measurement_calibration_weights = np.linalg.inv(spam_data_probabilities)\n", + "\n", + "## chsh circuits data processing\n", + "chsh_data_probabilities = data_probabilities[4:]\n", + "chsh_data_probabilities_theta = chsh_data_probabilities.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "\n", + "## compute witness\n", + "w1_raw, w2_raw = compute_witnesses(chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=True)\n", + "w1_corrected, w2_corrected = compute_witnesses(\n", + " chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run simulation, get ideal witnesses" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "circ_list = SPAM_circuits(0, 1)\n", + "ideal_results_spam = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_spam[i] += c.execute().probabilities()\n", + "ideal_measurement_calibration_weights = np.linalg.inv(ideal_results_spam)\n", + "\n", + "circ_list = list(np.copy(all_circuits_chsh))\n", + "ideal_results_chsh = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_chsh[i] += c.execute().probabilities()\n", + "\n", + "ideal_results_chsh_theta = ideal_results_chsh.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "w1_ideal, w2_ideal = compute_witnesses(\n", + " ideal_results_chsh_theta, ideal_measurement_calibration_weights, BELL_STATE, raw=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get error bars" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def return_mock_results():\n", + " # returns simulated results using distribution from experimental results' probabilities\n", + " mock_results = data_probabilities[4:].copy()\n", + " measurement_calibration_weights = np.linalg.inv(data_probabilities[:4]) \n", + " for i, _ in enumerate(mock_results): \n", + " mock_results[i] = stats.multinomial.rvs(NUM_SHOTS, mock_results[i]) / NUM_SHOTS\n", + "\n", + " return list((compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=False) +\n", + " compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=True)))\n", + " \n", + "def get_err_bars(mock_results):\n", + " data_hist = np.stack(mock_results)\n", + " err_bars = np.empty(len(data_hist.T))\n", + " for i, hist in enumerate(data_hist.T):\n", + " _ , var = stats.norm.fit(hist)\n", + " err_bars[i] =np.sqrt(var)\n", + " return err_bars\n", + "\n", + "# generate n copies of random results\n", + "err_w1, err_w2, err_w1_unc, err_w2_unc = [get_err_bars(mock_results) for mock_results in zip(*[return_mock_results() for _ in range(100)])]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fname = f\"chsh_{CONTROL_QUBIT}_{TARGET_QUBIT}_{BELL_STATE}_nshots{NUM_SHOTS}_jobid{result_id}.png\"\n", + "savefig = False\n", + "\n", + "fig, ax = plt.subplots()\n", + "ax.axhline(2, color=\"red\", linestyle=\"--\", label=\"classical bounds\")\n", + "ax.axhline(-2, color=\"red\", linestyle=\"--\")\n", + "ax.axhline(2 * np.sqrt(2), color=\"k\", linestyle=\"-.\", label=\"quantum bounds\")\n", + "ax.axhline(-2 * np.sqrt(2), color=\"k\", linestyle=\"-.\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_ideal, label=\"ideal\")\n", + "ax.plot(THETA_VALUES, w2_ideal)\n", + "\n", + "ax.plot(THETA_VALUES, w1_raw, \"x\", ms=3, c=\"C0\", label=\"raw\")\n", + "ax.errorbar(THETA_VALUES, w1_raw, err_w1_unc, capsize=3, c=\"C0\", ls=\"none\")\n", + "\n", + "ax.plot(THETA_VALUES, w2_raw, \"x\", ms=3, c=\"C1\")\n", + "ax.errorbar(THETA_VALUES, w2_raw, err_w2_unc, capsize=3, c=\"C1\", ls=\"none\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_corrected, \".\", c=\"C0\", label=\"corrected\")\n", + "ax.errorbar(THETA_VALUES, w1_corrected, err_w1, capsize=3, c=\"C0\", ls=\"none\")\n", + "\n", + "ax.plot(THETA_VALUES, w2_corrected, \".\", c=\"C1\")\n", + "ax.errorbar(THETA_VALUES, w2_corrected, err_w2, capsize=3, c=\"C1\", ls=\"none\")\n", + "\n", + "ax.legend()\n", + "\n", + "ax.set_xlabel(\"$\\\\theta$\")\n", + "ax.set_ylabel(\"witness 1 (blue), witness 2 (orange)\")\n", + "\n", + "ax.set_title(f\"({CONTROL_QUBIT}, {TARGET_QUBIT}), bell: {BELL_STATE}\")\n", + "if savefig:\n", + " fig.savefig(fname, bbox_inches=\"tight\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "LastMile", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/chsh_error_bars_draft.ipynb b/chsh_error_bars_draft.ipynb new file mode 100644 index 0000000..3c9e5f7 --- /dev/null +++ b/chsh_error_bars_draft.ipynb @@ -0,0 +1,702 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from qibo.gates import M, X, RY, CZ, I, H\n", + "from qibo.models import Circuit\n", + "from qiboconnection.api import API\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from qiboconnection.connection import ConnectionConfiguration\n", + "\n", + "from benchmarks.utils.qst_qpt_helper_functions import process_returned_dataformat\n", + "\n", + "from itertools import product\n", + "from scipy.stats import multivariate_normal\n", + "api = API(ConnectionConfiguration(username=\"apalacios\", api_key=\"3ec51562-3ff2-4f7b-add8-b21e1645a89d\"))\n", + "from scipy import stats\n", + "\n", + "api.select_device_id(9)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def get_chsh_circuits(bell_state, control_qubit, target_qubit, theta):\n", + " assert bell_state in (\n", + " \"phi_plus\",\n", + " \"phi_minus\",\n", + " \"psi_plus\",\n", + " \"psi_minus\",\n", + " ), \"bell_state should be phi_plus, phi_minus, psi_plus, psi_minus\"\n", + " nqubits = max(control_qubit, target_qubit) + 1\n", + "\n", + " circuits = []\n", + " for gate_a, gate_b in product([I, H], repeat=2):\n", + " circuit = Circuit(nqubits)\n", + "\n", + " if bell_state == \"phi_plus\" or bell_state == \"psi_minus\":\n", + " G1 = RY(control_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G1 = RY(control_qubit, theta=np.pi / 2)\n", + " if bell_state == \"phi_plus\" or bell_state == \"phi_minus\":\n", + " G2_prime = RY(target_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G2_prime = RY(target_qubit, theta=np.pi / 2)\n", + " ## build bell state\n", + " circuit.add(G1)\n", + " circuit.add(RY(target_qubit, theta=np.pi / 2))\n", + " circuit.add(CZ(control_qubit, target_qubit))\n", + " circuit.add(G2_prime)\n", + "\n", + " ## decoder part\n", + " circuit.add(RY(control_qubit, theta=theta))\n", + " circuit.add(gate_a(control_qubit))\n", + " circuit.add(gate_b(target_qubit))\n", + " circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " circuits.append(circuit)\n", + "\n", + " return circuits\n", + "\n", + "\n", + "def SPAM_circuits(control_qubit, target_qubit):\n", + " \"\"\"Circuits to get the SPAM matrix in order to perform measurement correction.\"\"\"\n", + " calibration_circuits = []\n", + " for gate_a, gate_b in product([I, X], repeat=2):\n", + " calibration_circuit = Circuit(5)\n", + " calibration_circuit.add(gate_a(control_qubit))\n", + " calibration_circuit.add(gate_b(target_qubit))\n", + " calibration_circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " calibration_circuits.append(calibration_circuit)\n", + " return calibration_circuits\n", + "\n", + "\n", + "def compute_witnesses(chsh_results, measurement_calibration_weights, BELL_STATE, raw=False):\n", + " \"\"\"Returns arrays of computed witness values.\n", + "\n", + " Args:\n", + " chsh_results (array): matrix containing the probabilities the chsh circuits. It must be\n", + " of dimensions len(theta_values) x 4 (decoder circuits) x 4 (probabilities)\n", + " measurement_calibration_weights (array): measurement calibration matrix.\n", + " BELL_STATE (string): can be \"phi_plus\", \"phi_minus\", \"psi_plus\" or \"psi_minus\". It needs\n", + " to be specified because the witness isn't the same for all 4 Bell states.\n", + " raw (bool): whether or not calculate the witnesses from the raw data instead of applying the\n", + " measurement corrections. Defaults to False.\n", + " Returns:\n", + " witness1 (array): array length len(theta_values) containing the first witness\n", + " witness2 (array): array length len(theta_values) containing the second witness\n", + " \"\"\"\n", + " len_theta_values = np.shape(chsh_results)[0]\n", + " witness1 = np.zeros(len_theta_values)\n", + " witness2 = np.zeros(len_theta_values)\n", + "\n", + " if BELL_STATE in [\"phi_plus\", \"psi_minus\"]:\n", + " signs1 = np.array([1, 1, -1, 1])\n", + " signs2 = np.array([1, -1, 1, 1])\n", + " else:\n", + " signs1 = np.array([-1, 1, 1, 1])\n", + " signs2 = np.array([1, 1, 1, -1])\n", + "\n", + " for i, chsh_result in enumerate(chsh_results):\n", + " if raw is not True:\n", + " # apply measurement calibration\n", + " chsh_result = measurement_calibration_weights @ chsh_result.T\n", + " # calculate expectation values from probabilities\n", + " expectations = np.array([1, -1, -1, 1]).T @ chsh_result\n", + "\n", + " else:\n", + " # calculate expectation values from probabilities\n", + " expectations = chsh_result @ np.array([1, -1, -1, 1])\n", + " # compute witnesses\n", + " witness1[i] = signs1.T @ expectations\n", + " witness2[i] = signs2.T @ expectations\n", + " return witness1, witness2" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "CONTROL_QUBIT = 2\n", + "TARGET_QUBIT = 0\n", + "THETA_VALUES = np.linspace(-np.pi, np.pi, num=20)\n", + "BELL_STATE = \"psi_minus\"\n", + "\n", + "NUM_SHOTS = 8000" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Build circuits for CHSH and measurement correction" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "all_circuits_chsh = []\n", + "for theta in THETA_VALUES:\n", + " circuits_th = get_chsh_circuits(BELL_STATE, CONTROL_QUBIT, TARGET_QUBIT, theta)\n", + " all_circuits_chsh.extend(circuits_th)\n", + "\n", + "all_circuits = SPAM_circuits(CONTROL_QUBIT, TARGET_QUBIT)\n", + "\n", + "all_circuits.extend(all_circuits_chsh)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run circuits" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# result_id = api.execute(all_circuits, nshots=NUM_SHOTS)[0]\n", + "result_id = 8009" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Your job with id 8009 is completed.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-02-26 18:53:12,720 - qm - INFO - Starting session: 7a9a03f0-150d-4d69-8cf4-728b0a477b00\n" + ] + }, + { + "data": { + "text/plain": [ + "JobData(completed_at='2024-01-16T11:23:16.185946+00:00', created_at='2024-01-16T11:05:08.703698+00:00', description=[, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ], device_id=9, execution_time=186.832845, execution_type='qililab', favourite=False, job_execution_time_mark='2024-01-16T11:20:10.609465+00:00', job_id=8009, job_postprocessing_time_mark='2024-01-16T11:23:16.185402+00:00', job_preprocessing_time_mark='2024-01-16T11:20:09.353101+00:00', job_processing_time_mark='2024-01-16T11:20:09.353239+00:00', job_results_post_time_mark='2024-01-16T11:23:16.185946+00:00', job_results_reading_time_mark='2024-01-16T11:23:14.907559+00:00', job_type='circuit', logs=None, name='-', number_shots=8000, queue_position=0, result=[{'probabilities': {'00': 0.728, '01': 0.096125, '10': 0.152125, '11': 0.02375}}, {'probabilities': {'00': 0.14, '01': 0.019625, '10': 0.741375, '11': 0.099}}, {'probabilities': {'00': 0.133, '01': 0.67725, '10': 0.0315, '11': 0.15825}}, {'probabilities': {'00': 0.030875, '01': 0.146, '10': 0.139125, '11': 0.684}}, {'probabilities': {'00': 0.410625, 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0.214375}}, {'probabilities': {'00': 0.125, '01': 0.376125, '10': 0.3455, '11': 0.153375}}, {'probabilities': {'00': 0.36325, '01': 0.133875, '10': 0.135375, '11': 0.3675}}, {'probabilities': {'00': 0.189875, '01': 0.305875, '10': 0.290625, '11': 0.213625}}, {'probabilities': {'00': 0.13575, '01': 0.332, '10': 0.337375, '11': 0.194875}}, {'probabilities': {'00': 0.1405, '01': 0.358, '10': 0.33375, '11': 0.16775}}, {'probabilities': {'00': 0.3355, '01': 0.157375, '10': 0.146375, '11': 0.36075}}, {'probabilities': {'00': 0.149625, '01': 0.329, '10': 0.339375, '11': 0.182}}, {'probabilities': {'00': 0.113875, '01': 0.3635, '10': 0.372625, '11': 0.15}}, {'probabilities': {'00': 0.1685, '01': 0.317375, '10': 0.310625, '11': 0.2035}}, {'probabilities': {'00': 0.29675, '01': 0.187625, '10': 0.18525, '11': 0.330375}}, {'probabilities': {'00': 0.1295, '01': 0.36075, '10': 0.3465, '11': 0.16325}}, {'probabilities': {'00': 0.106125, '01': 0.365625, '10': 0.39575, '11': 0.1325}}, {'probabilities': {'00': 0.22475, '01': 0.274625, '10': 0.274, '11': 0.226625}}, {'probabilities': {'00': 0.256875, '01': 0.231375, '10': 0.2095, '11': 0.30225}}, {'probabilities': {'00': 0.10425, '01': 0.3865, '10': 0.36, '11': 0.14925}}, {'probabilities': {'00': 0.10875, '01': 0.37875, '10': 0.399, '11': 0.1135}}, {'probabilities': {'00': 0.26625, '01': 0.21925, '10': 0.246, '11': 0.2685}}, {'probabilities': {'00': 0.2035, '01': 0.27125, '10': 0.26475, '11': 0.2605}}, {'probabilities': {'00': 0.104375, '01': 0.385625, '10': 0.35825, '11': 0.15175}}, {'probabilities': {'00': 0.121625, '01': 0.361625, '10': 0.39825, '11': 0.1185}}, {'probabilities': {'00': 0.31475, '01': 0.175625, '10': 0.210125, '11': 0.2995}}, {'probabilities': {'00': 0.163625, '01': 0.321875, '10': 0.306125, '11': 0.208375}}, {'probabilities': {'00': 0.118, '01': 0.374875, '10': 0.354375, '11': 0.15275}}, {'probabilities': {'00': 0.160875, '01': 0.32275, '10': 0.36575, '11': 0.150625}}, {'probabilities': {'00': 0.353375, '01': 0.14575, '10': 0.1835, '11': 0.317375}}, {'probabilities': {'00': 0.14975, '01': 0.35575, '10': 0.322125, '11': 0.172375}}, {'probabilities': {'00': 0.15675, '01': 0.357125, '10': 0.317, '11': 0.169125}}, {'probabilities': {'00': 0.205875, '01': 0.282625, '10': 0.334125, '11': 0.177375}}, {'probabilities': {'00': 0.389125, '01': 0.1235, '10': 0.151375, '11': 0.336}}, {'probabilities': {'00': 0.118625, '01': 0.357625, '10': 0.37825, '11': 0.1455}}, {'probabilities': {'00': 0.19625, '01': 0.2975, '10': 0.296, '11': 0.21025}}, {'probabilities': {'00': 0.259, '01': 0.239125, '10': 0.289625, '11': 0.21225}}, {'probabilities': {'00': 0.386375, '01': 0.108625, '10': 0.15525, '11': 0.34975}}, {'probabilities': {'00': 0.1145, '01': 0.3755, '10': 0.378375, '11': 0.131625}}, {'probabilities': {'00': 0.235, '01': 0.2635, '10': 0.254875, '11': 0.246625}}, {'probabilities': {'00': 0.288625, '01': 0.1885, '10': 0.25625, '11': 0.266625}}, {'probabilities': {'00': 0.386875, '01': 0.10975, '10': 0.164625, '11': 0.33875}}, {'probabilities': {'00': 0.118375, '01': 0.369375, '10': 0.399125, '11': 0.113125}}, {'probabilities': {'00': 0.27325, '01': 0.2215, '10': 0.22925, '11': 0.276}}, {'probabilities': {'00': 0.3355, '01': 0.156, '10': 0.205875, '11': 0.302625}}, {'probabilities': {'00': 0.38025, '01': 0.13025, '10': 0.1735, '11': 0.316}}, {'probabilities': {'00': 0.148375, '01': 0.353, '10': 0.3745, '11': 0.124125}}, {'probabilities': {'00': 0.330125, '01': 0.176375, '10': 0.195125, '11': 0.298375}}, {'probabilities': {'00': 0.378375, '01': 0.123625, '10': 0.156875, '11': 0.341125}}, {'probabilities': {'00': 0.351125, '01': 0.1565, '10': 0.194, '11': 0.298375}}, {'probabilities': {'00': 0.17325, '01': 0.322875, '10': 0.355375, '11': 0.1485}}, {'probabilities': {'00': 0.358375, '01': 0.157125, '10': 0.169375, '11': 0.315125}}, {'probabilities': {'00': 0.389625, '01': 0.111, '10': 0.137625, '11': 0.36175}}, {'probabilities': {'00': 0.307375, '01': 0.193625, '10': 0.2285, '11': 0.2705}}, {'probabilities': {'00': 0.2175, '01': 0.268, '10': 0.315125, '11': 0.199375}}, {'probabilities': {'00': 0.379375, '01': 0.113875, '10': 0.16225, '11': 0.3445}}, {'probabilities': {'00': 0.37625, '01': 0.110875, '10': 0.133625, '11': 0.37925}}, {'probabilities': {'00': 0.256375, '01': 0.238, '10': 0.255, '11': 0.250625}}, {'probabilities': {'00': 0.26675, '01': 0.238, '10': 0.273375, '11': 0.221875}}, {'probabilities': {'00': 0.387125, '01': 0.116125, '10': 0.157375, '11': 0.339375}}], slurm_job_id=None, status='completed', summary='-', updated_at='2024-01-16T11:23:17.600820+00:00', user_id=86)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results = api.get_job(result_id)\n", + "results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Process real data" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Your job with id 8009 is completed.\n" + ] + } + ], + "source": [ + "## retrieve data\n", + "results = api.get_result(result_id)\n", + "data_probabilities = process_returned_dataformat(results, nqubits=2)\n", + "\n", + "## measurement calibration data processing\n", + "spam_data_probabilities = data_probabilities[:4]\n", + "measurement_calibration_weights = np.linalg.inv(spam_data_probabilities)\n", + "\n", + "## chsh circuits data processing\n", + "chsh_data_probabilities = data_probabilities[4:]\n", + "chsh_data_probabilities_theta = chsh_data_probabilities.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "\n", + "## compute witness\n", + "w1_raw, w2_raw = compute_witnesses(chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=True)\n", + "w1_corrected, w2_corrected = compute_witnesses(\n", + " chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run simulation, get ideal witnesses" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Qibo 0.1.12.dev0|INFO|2024-02-26 18:53:13]: Using numpy backend on /CPU:0\n" + ] + } + ], + "source": [ + "circ_list = SPAM_circuits(0, 1)\n", + "ideal_results_spam = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_spam[i] += c.execute().probabilities()\n", + "ideal_measurement_calibration_weights = np.linalg.inv(ideal_results_spam)\n", + "\n", + "circ_list = list(np.copy(all_circuits_chsh))\n", + "ideal_results_chsh = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_chsh[i] += c.execute().probabilities()\n", + "\n", + "ideal_results_chsh_theta = ideal_results_chsh.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "w1_ideal, w2_ideal = compute_witnesses(\n", + " ideal_results_chsh_theta, ideal_measurement_calibration_weights, BELL_STATE, raw=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get error bars" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.395, 0.095, 0.116, 0.394])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "NUM_SHOTS = 1000\n", + "stats.multinomial.rvs(NUM_SHOTS, data_probabilities[4]) / NUM_SHOTS\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.410625, 0.099875, 0.112625, 0.376875])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_probabilities[4]" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + 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-0.01738241, 0.48292067, 0.33478989],\n", + " [ 0.13202054, 0.52283894, 0.00259851, 0.19546689],\n", + " [ 0.18127428, 0.48478445, 0.00513615, 0.15398257],\n", + " [ 0.40460154, 0.01152275, 0.51168988, 0.31827832],\n", + " [ 0.2025821 , -0.02737249, 0.49990364, 0.22350602],\n", + " [ 0.24159685, 0.52264117, -0.01919106, 0.28151033],\n", + " [ 0.28021046, 0.49795403, -0.01246289, 0.25050864],\n", + " [ 0.27556704, 0.00787523, 0.53413928, 0.24710779],\n", + " [ 0.13007565, 0.00488546, 0.47970455, 0.13505428],\n", + " [ 0.35068165, 0.48135462, -0.0155544 , 0.34880891],\n", + " [ 0.35944567, 0.49080722, 0.02169299, 0.35657696],\n", + " [ 0.15957824, 0.02143689, 0.51453513, 0.15924025],\n", + " [ 0.03727766, 0.03610329, 0.42936222, 0.0576008 ],\n", + " [ 0.44739002, 0.45178359, 0.01386026, 0.45114659],\n", + " [ 0.41514167, 0.45686403, 0.06515191, 0.40975472],\n", + " [ 0.10328732, 0.0542598 , 0.49182103, 0.08384071],\n", + " [-0.01344523, 0.09565467, 0.35408185, 0.01629444],\n", + " [ 0.52829336, 0.39126417, 0.09998683, 0.47709945],\n", + " [ 0.47752255, 0.38204606, 0.12751545, 0.46535522],\n", + " [ 0.01001311, 0.13197359, 0.41974278, 0.04144422],\n", + " [-0.03098736, 0.19960437, 0.27624046, -0.03186936],\n", + " [ 0.57396495, 0.30561081, 0.16309704, 0.51258439],\n", + " [ 0.48737256, 0.29841975, 0.20857843, 0.51299199],\n", + " [-0.02653195, 0.19638215, 0.352179 , 0.00588689],\n", + " [-0.03252117, 0.28465791, 0.17273405, -0.03095714],\n", + " [ 0.58617098, 0.23029675, 0.28430459, 0.50878544],\n", + " [ 0.50969703, 0.19709857, 0.29194715, 0.51109775],\n", + " [-0.06138665, 0.29044813, 0.25298424, 0.01069686],\n", + " [-0.0081293 , 0.37765968, 0.08828616, -0.00688802],\n", + " [ 0.5784055 , 0.14511802, 0.38396635, 0.49767518],\n", + " [ 0.48034995, 0.11273699, 0.38867643, 0.49144601],\n", + " [-0.04755102, 0.36691227, 0.1396425 , 0.01744103],\n", + " [ 0.06921449, 0.44958313, 0.05296443, 0.0637614 ],\n", + " [ 0.50113977, 0.08318372, 0.42874896, 0.41984165],\n", + " [ 0.4053074 , 0.05408323, 0.44959968, 0.45011082],\n", + " [ 0.02768012, 0.41494878, 0.06665471, 0.06321319],\n", + " [ 0.15497128, 0.51617675, -0.00606696, 0.14566515],\n", + " [ 0.42551855, 0.01348703, 0.53720066, 0.35628633],\n", + " [ 0.32803287, 0.00683638, 0.46891201, 0.34366396],\n", + " [ 0.09477629, 0.4636591 , 0.00295123, 0.15485751],\n", + " [ 0.25667833, 0.51635376, -0.01807247, 0.2227831 ],\n", + " [ 0.32383761, 0.0145056 , 0.54476372, 0.26413917],\n", + " [ 0.24139665, -0.01657833, 0.49875199, 0.27453908],\n", + " [ 0.18049774, 0.48829857, -0.02447571, 0.23828509],\n", + " [ 0.32450721, 0.51434927, -0.0156245 , 0.29805204],\n", + " [ 0.23905283, 0.03342658, 0.58317803, 0.19894866],\n", + " [ 0.14736987, -0.01239485, 0.49359243, 0.19613068],\n", + " [ 0.29415394, 0.46741757, -0.05878309, 0.30769658],\n", + " [ 0.41501223, 0.49570307, 0.0388951 , 0.40307989],\n", + " [ 0.13004654, 0.05908479, 0.5302528 , 0.1172357 ],\n", + " [ 0.07784916, 0.0241514 , 0.45832538, 0.10916756],\n", + " [ 0.3801081 , 0.42208878, -0.02669198, 0.3707976 ],\n", + " [ 0.49942429, 0.44009606, 0.08941476, 0.45636164],\n", + " [ 0.02347082, 0.10821045, 0.4818259 , 0.06073159],\n", + " [ 0.0091501 , 0.07463607, 0.40207088, 0.06898555],\n", + " [ 0.46930633, 0.37807685, 0.02844244, 0.41311463],\n", + " [ 0.52457202, 0.35642877, 0.18127305, 0.50283341],\n", + " [-0.01880767, 0.18829082, 0.38290498, 0.02992784],\n", + " [-0.01730744, 0.14759351, 0.29830882, -0.00567273],\n", + " [ 0.51273049, 0.30916792, 0.14089452, 0.47572335],\n", + " [ 0.50652482, 0.2619389 , 0.27216767, 0.51434034],\n", + " [-0.02778654, 0.25519019, 0.29208682, 0.02194589],\n", + " [-0.01762004, 0.23100388, 0.23492831, -0.00370362],\n", + " [ 0.54111004, 0.25313078, 0.20196308, 0.46901448]])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mock_results = data_probabilities[4:].copy()\n", + "\n", + "mock_results = np.round(np.array([measurement_calibration_weights @ res.T for res in mock_results.reshape(-1,4,4)]).reshape(np.shape(mock_results)),41)\n", + "mock_results\n", + "# plt.imshow(data_probabilities[:4])\n", + "# plt.colorbar()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.46765067, -0.29992837, -0.2083847 , 0.0406624 ],\n", + " [-0.28735369, 0.06020572, 1.59487385, -0.36772588],\n", + " [-0.27639325, 1.44299062, 0.04249003, -0.2090874 ],\n", + " [ 0.05130575, -0.29281552, -0.33966247, 1.58117224]])" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "measurement_calibration_weights" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "def return_mock_results(corrected=False):\n", + " # returns simulated results using distribution from experimental results' probabilities\n", + " mock_results = data_probabilities[4:].copy()\n", + " measurement_calibration_weights = np.linalg.inv(data_probabilities[:4])\n", + " # if corrected:\n", + " # mock_results = np.array([measurement_calibration_weights @ res for res in mock_results.reshape(-1,4,4)]).reshape(np.shape(mock_results))\n", + " \n", + " for i, _ in enumerate(mock_results): \n", + " mock_results[i] = stats.multinomial.rvs(NUM_SHOTS, mock_results[i]) / NUM_SHOTS\n", + "\n", + " if corrected:\n", + " return compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=False)[0]\n", + " return compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=True)[0]\n", + " \n", + " \n", + "\n", + "# generate n copies of random results\n", + "data_hist = np.array([return_mock_results(corrected=True) for _ in range(5000)])\n", + "data_hist_unc = np.array([return_mock_results(corrected=False) for _ in range(5000)])\n", + "\n", + "# get error bars for spam and not spam\n", + "err_bars = np.empty(len(data_hist.T))\n", + "for i, hist in enumerate(data_hist.T):\n", + " mean , var = stats.norm.fit(hist)\n", + " err_bars[i] =np.sqrt(var)\n", + "\n", + "# get error bars for spam and not spam\n", + "err_bars_unc = np.empty(len(data_hist_unc.T))\n", + "for i, hist in enumerate(data_hist_unc.T):\n", + " mean , var = stats.norm.fit(hist)\n", + " err_bars_unc[i] =np.sqrt(var)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1.014, 0.722, 0.18 , -0.222, -0.596, -1.024, -1.412, -1.454,\n", + " -1.388, -1.202, -0.928, -0.562, -0.076, 0.548, 0.884, 1.29 ,\n", + " 1.338, 1.342, 1.28 , 1.062])" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "return_mock_results(corrected=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 2.4471528 , 1.51940172, 0.68087776, -0.647151 , -1.47593564,\n", + " -2.53939871, -2.4678259 , -3.13896587, -2.85356938, -2.90742236,\n", + " -1.91500704, -1.04479214, 0.05472315, 0.9870691 , 1.89327767,\n", + " 2.65040523, 2.9461952 , 2.99777586, 2.74651598, 2.18571683])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "return_mock_results(corrected=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(5000, 20)" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_hist.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# check a single histogram to see its shape\n", + "_ = plt.hist(data_hist[:,8], bins=50) # arguments are passed to np.histogram\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.35316518, 0.35200451, 0.35509225, 0.35414452, 0.35588317,\n", + " 0.35474668, 0.35430235, 0.35505689, 0.35558451, 0.35492617,\n", + " 0.35376629, 0.35744576, 0.35801235, 0.35496243, 0.35743387,\n", + " 0.35681449, 0.35914344, 0.35697054, 0.35757296, 0.35618317])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "err_bars" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fname = f\"chsh_{CONTROL_QUBIT}_{TARGET_QUBIT}_{BELL_STATE}_nshots{NUM_SHOTS}_jobid{result_id}.png\"\n", + "savefig = False\n", + "\n", + "fig, ax = plt.subplots()\n", + "ax.axhline(2, color=\"red\", linestyle=\"--\", label=\"classical bounds\")\n", + "ax.axhline(-2, color=\"red\", linestyle=\"--\")\n", + "ax.axhline(2 * np.sqrt(2), color=\"k\", linestyle=\"-.\", label=\"quantum bounds\")\n", + "ax.axhline(-2 * np.sqrt(2), color=\"k\", linestyle=\"-.\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_ideal, label=\"ideal\")\n", + "# ax.plot(THETA_VALUES, w2_ideal)\n", + "\n", + "ax.plot(THETA_VALUES, w1_raw, \"+-\", ms=3, c=\"C0\", label=\"raw\")\n", + "# ax.plot(THETA_VALUES, w2_raw, \"x\", ms=3, c=\"C1\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_corrected, \"x\", c=\"C0\", label=\"corrected\")\n", + "ax.errorbar(THETA_VALUES, w1_corrected, err_bars, capsize=3, c=\"C0\", ls=\"none\") # \"x--\",\n", + "ax.plot(THETA_VALUES, np.mean(data_hist_unc, axis=0), \"x\", c=\"red\", label=\"uncorrected\")\n", + "\n", + "# ax.errorbar(THETA_VALUES, w1_raw, err_bars_unc, capsize=3, c=\"C0\", ls=\"none\") # \"x--\",\n", + "ax.plot(THETA_VALUES, np.mean(data_hist, axis=0), \".\", c=\"green\", label=\"corrected\")\n", + "\n", + "\n", + "# ax.plot(THETA_VALUES, w2_corrected, \".\", c=\"C1\")\n", + "ax.legend()\n", + "\n", + "ax.set_xlabel(\"$\\\\theta$\")\n", + "ax.set_ylabel(\"witness 1 (blue), witness 2 (orange)\")\n", + "\n", + "ax.set_title(f\"({CONTROL_QUBIT}, {TARGET_QUBIT}), bell: {BELL_STATE}\")\n", + "if savefig:\n", + " fig.savefig(fname, bbox_inches=\"tight\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "LastMile", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/chsh_error_bars_fidelity.ipynb b/chsh_error_bars_fidelity.ipynb index 0efece0..25adf27 100644 --- a/chsh_error_bars_fidelity.ipynb +++ b/chsh_error_bars_fidelity.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 123, + "execution_count": 164, "metadata": {}, "outputs": [], "source": [ @@ -35,7 +35,7 @@ }, { "cell_type": "code", - "execution_count": 124, + "execution_count": 165, "metadata": {}, "outputs": [], "source": [ @@ -47,8 +47,8 @@ "NUM_SHOTS = 8000\n", "\n", "LOAD_RESULTS = False\n", - "mfidelity_qc = 0.88 # measurement fidelity control qubit\n", - "mfidelity_qt = 0.84 # measurement fidelity target qubit" + "mfidelity_qc = 0.87 # measurement fidelity control qubit\n", + "mfidelity_qt = 0.83 # measurement fidelity target qubit" ] }, { @@ -60,7 +60,7 @@ }, { "cell_type": "code", - "execution_count": 125, + "execution_count": 166, "metadata": {}, "outputs": [], "source": [ @@ -166,7 +166,7 @@ }, { "cell_type": "code", - "execution_count": 126, + "execution_count": 167, "metadata": {}, "outputs": [], "source": [ @@ -189,7 +189,7 @@ }, { "cell_type": "code", - "execution_count": 127, + "execution_count": 170, "metadata": {}, "outputs": [], "source": [ @@ -208,51 +208,16 @@ }, { "cell_type": "code", - "execution_count": 128, + "execution_count": 171, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "{\n", - " \"title\": \"Unauthorized\",\n", - " \"status\": 401,\n", - " \"detail\": \"JWTExpired: Error verifying the authorisation access token. Expired at 1709307549, time: 1709307617(leeway: 60) 401 Client Error: for url: https://qilimanjaroqaas.ddns.net:8080/api/v1/jobs/8902\"\n", - "}\n", - "{\"title\":\"Unauthorized\",\"status\":401,\"detail\":\"JWTExpired: Error verifying the authorisation access token. Expired at 1709307549, time: 1709307617(leeway: 60)\"}\n", - "\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n", - "Your job with id 8902 is still pending. Job queue position: 3\n" - ] - } - ], + "outputs": [], "source": [ - "results = None\n", - "while results is None:\n", - " results = api.get_result(result_id)\n", - " sleep(30)\n", - "results" + "if LOAD_RESULTS is False:\n", + " results = None\n", + " while results is None:\n", + " results = api.get_result(result_id)\n", + " sleep(30)\n", + " results" ] }, { @@ -264,7 +229,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 172, "metadata": {}, "outputs": [ { @@ -305,7 +270,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 173, "metadata": {}, "outputs": [], "source": [ @@ -338,23 +303,12 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(80, 4)" - ] - }, - "execution_count": 114, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 174, "metadata": {}, "outputs": [], "source": [ @@ -399,45 +353,45 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 175, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "data a mean 2.3388335670874305, std 0.20652339499392464\n", - "data b mean 1.8922727666204988, std 0.187484891075065\n" + "data a mean 2.338293381525259, std 0.2122201388631369\n", + "data b mean 1.9955295836376918, std 0.19269172473641838\n" ] }, { "data": { "text/plain": [ - "(array([ 3., 1., 7., 5., 7., 5., 12., 14., 14., 16., 15., 25., 25.,\n", - " 28., 26., 33., 31., 41., 31., 42., 43., 40., 33., 42., 40., 42.,\n", - " 38., 40., 45., 40., 32., 34., 25., 24., 18., 11., 10., 14., 5.,\n", - " 9., 4., 7., 8., 4., 4., 4., 2., 0., 0., 1.]),\n", - " array([4.23252829, 4.24083313, 4.24913797, 4.25744281, 4.26574765,\n", - " 4.27405249, 4.28235733, 4.29066217, 4.29896701, 4.30727185,\n", - " 4.31557669, 4.32388153, 4.33218637, 4.34049121, 4.34879605,\n", - " 4.35710089, 4.36540573, 4.37371057, 4.38201541, 4.39032025,\n", - " 4.39862509, 4.40692993, 4.41523477, 4.42353961, 4.43184445,\n", - " 4.44014929, 4.44845412, 4.45675896, 4.4650638 , 4.47336864,\n", - " 4.48167348, 4.48997832, 4.49828316, 4.506588 , 4.51489284,\n", - " 4.52319768, 4.53150252, 4.53980736, 4.5481122 , 4.55641704,\n", - " 4.56472188, 4.57302672, 4.58133156, 4.5896364 , 4.59794124,\n", - " 4.60624608, 4.61455092, 4.62285576, 4.6311606 , 4.63946544,\n", - " 4.64777028]),\n", + "(array([ 2., 2., 4., 1., 4., 13., 5., 15., 10., 13., 22., 25., 28.,\n", + " 36., 40., 39., 50., 47., 44., 54., 51., 57., 48., 42., 35., 44.,\n", + " 38., 29., 39., 29., 17., 28., 22., 20., 11., 10., 4., 4., 3.,\n", + " 5., 4., 0., 0., 1., 0., 3., 0., 1., 0., 1.]),\n", + " array([4.456885 , 4.46679741, 4.47670983, 4.48662224, 4.49653465,\n", + " 4.50644707, 4.51635948, 4.5262719 , 4.53618431, 4.54609673,\n", + " 4.55600914, 4.56592155, 4.57583397, 4.58574638, 4.5956588 ,\n", + " 4.60557121, 4.61548363, 4.62539604, 4.63530845, 4.64522087,\n", + " 4.65513328, 4.6650457 , 4.67495811, 4.68487053, 4.69478294,\n", + " 4.70469535, 4.71460777, 4.72452018, 4.7344326 , 4.74434501,\n", + " 4.75425743, 4.76416984, 4.77408225, 4.78399467, 4.79390708,\n", + " 4.8038195 , 4.81373191, 4.82364433, 4.83355674, 4.84346916,\n", + " 4.85338157, 4.86329398, 4.8732064 , 4.88311881, 4.89303123,\n", + " 4.90294364, 4.91285606, 4.92276847, 4.93268088, 4.9425933 ,\n", + " 4.95250571]),\n", " )" ] }, - "execution_count": 109, + "execution_count": 175, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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8ZLPZuOOOO+KZZ56JV155JU499dRej0+dOjWGDx8ea9euze3bvHlzbNmyJerr6wszMQBQ0vJ656OpqSlWrlwZv/vd72LUqFG5z3FUV1fHscceG9XV1TF37tyYP39+jBkzJqqqquLOO++M+vp6K10AgIjIMz4ee+yxiIi4/PLLe+1vbm6OW2+9NSIiHnrooRg2bFg0NjZGJpOJmTNnxvLlywsyLABQ+vKKj2w2+7nHVFZWxrJly2LZsmV9HgoAGLrc2wUASEp8AABJiQ8AICnxAQAkJT4AgKTEBwCQlPgAAJISHwBAUuIDAEhKfAAASYkPACAp8QEAKbQ1F3uCQUN8AABJiQ8AICnxAQAkJT4AgKTEBwCQlPgoskkLXij2CACQlPgAAJISHwBAUuIDAEhKfAAASYkPACAp8QEAJCU+ACh9bc1u3FZCxAcAkJT4AACSEh8AQFLiAwBISnwAAEmJDwAgKfEBACQlPgCApMQHAJCU+AAAkhIfAEBS4gOA0vN593Jxn5dBTXwAAEmJDwAgKfEBACQlPgCApMQHAJCU+AAAkhIfAEBS4gMASEp8AABJiQ8AICnxAQAkVV7sAQa7SQteKPYIAAx1bc0R0+YUe4pkvPMBACSVd3y89tprcc0118S4ceOirKwsnn322V6PZ7PZuPfee+Pkk0+OY489NhoaGuLdd98t1LwAQInLOz527doV5513Xixbtuygj//sZz+LRx99NB5//PF466234rjjjouZM2fG7t27+z0sAFD68v7Mx6xZs2LWrFkHfSybzcbDDz8c99xzT1x77bUREfGrX/0qampq4tlnn40bbrihf9MCACWvoJ/5+OCDD6KzszMaGhpy+6qrq2P69Omxbt26Qn4rAKBEFXS1S2dnZ0RE1NTU9NpfU1OTe2x/mUwmMplM7uuenp5CjgQADDJFX+2yZMmSqK6uzm0TJkwo6jyTFrxQlOW1lvQCFEBb83+3UlTKs+epoPFRW1sbERFdXV299nd1deUe29/ChQuju7s7t3V0dBRyJABgkClofJx66qlRW1sba9euze3r6emJt956K+rr6w/6nIqKiqiqquq1AQBDV96f+di5c2e89957ua8/+OCD2LBhQ4wZMyYmTpwY8+bNi5/85CdxxhlnxKmnnho/+tGPYty4cTF79uxCzg0AlKi846OtrS2+9rWv5b6eP39+RETccsstsWLFivj+978fu3btim9+85uxY8eOuPTSS+Oll16KysrKwk0NAJSsvOPj8ssvj2w2e8jHy8rK4v7774/777+/X4MBAENT0Ve7AABHF/EBACQlPgCApMQHAJCU+AAAkhIfAEBS4uMw3OMFAApPfAAASYkPACAp8QEAJCU+AICkxAcAkJT4GASscAHgaCI+AICkxAcAkJT4AACSEh8AQFLiAwBISnz8f/uvOCn2CpRif38AGCjiAwBISnwAAEmJDwAgKfEBACQlPgCApMqLPQD/Y4ULQJ7amos9QRqf/j2nzSnuHAXinQ8AICnxAQAkJT4AgKTEBwCQlPgAAJISHwBAUpbaxuBd4jppwQvxt6VXF3sMgOLaf5npUF9eu//f77PLa4fIklvvfAAASYkPACAp8QEAJCU+AICkxAcAkJT4GIQG6+obAIog39U9bc2DfkWQ+AAAkhIfAEBS4gMASEp8AABJiQ8AIKmj/t4un11ZMlhXmbjHC3DUGeSrNegf73wAAEmJDwAgKfEBACQlPgCApMQHAJDUUbfa5bMrWkphBclgXYEDkJwVMAf36XmZNufQj3/62Ocdm4h3PgCApAYsPpYtWxaTJk2KysrKmD59evzxj38cqG8FAJSQAYmP3/zmNzF//vxYtGhRvP3223HeeefFzJkzY/v27QPx7QCAEjIg8fHggw/GbbfdFnPmzImzzz47Hn/88fjCF74QTz311EB8OwCghBT8A6d79uyJ9vb2WLhwYW7fsGHDoqGhIdatW3fA8ZlMJjKZTO7r7u7uiIjo6ekp9GgREbEv85/cn3t6enp9PZgN1PkAGJR2/l+xJxjcPvtvwqfn6tN9B/v6UI8VdKT/vmY2m/38g7MF9o9//CMbEdk333yz1/7vfe972QsvvPCA4xctWpSNCJvNZrPZbENg6+jo+NxWKPpS24ULF8b8+fNzX+/bty/+9a9/xdixY6OsrKyIk/XW09MTEyZMiI6Ojqiqqir2OEOSczywnN+B5xwPPOd44PX1HGez2fj4449j3Lhxn3tswePjhBNOiGOOOSa6urp67e/q6ora2toDjq+oqIiKiope+0aPHl3osQqmqqrKBT/AnOOB5fwOPOd44DnHA68v57i6uvqIjiv4B05HjBgRU6dOjbVr1+b27du3L9auXRv19fWF/nYAQIkZkB+7zJ8/P2655ZaYNm1aXHjhhfHwww/Hrl27Ys6c4v5GNQCg+AYkPq6//vr45z//Gffee290dnbGl770pXjppZeipqZmIL5dEhUVFbFo0aIDfkRE4TjHA8v5HXjO8cBzjgdeinNcls0eyZoYAIDCcG8XACAp8QEAJCU+AICkxAcAkJT4iIglS5bEBRdcEKNGjYqTTjopZs+eHZs3bz7sc1asWBFlZWW9tsrKykQTl57HHnss6urqcr+0pr6+Pl588cXDPmf16tUxZcqUqKysjC9+8Yvx+9//PtG0pSnfc+wa7p+lS5dGWVlZzJs377DHuY777kjOses4P/fdd98B52vKlCmHfc5AXMPiIyJaWlqiqakpWltbY82aNbF379646qqrYteuXYd9XlVVVWzbti23/f3vf080cekZP358LF26NNrb26OtrS1mzJgR1157bbzzzjsHPf7NN9+MG2+8MebOnRt/+tOfYvbs2TF79uzYtGlT4slLR77nOMI13Ffr16+PJ554Iurq6g57nOu47470HEe4jvN1zjnn9Dpfr7/++iGPHbBruDC3kxtatm/fno2IbEtLyyGPaW5uzlZXV6cbagg6/vjjs7/85S8P+tjXv/717NVXX91r3/Tp07Pf+ta3Uow2ZBzuHLuG++bjjz/OnnHGGdk1a9Zkv/rVr2bvuuuuQx7rOu6bfM6x6zg/ixYtyp533nlHfPxAXcPe+TiI7u7uiIgYM2bMYY/buXNnnHLKKTFhwoTP/R8m//PJJ5/EqlWrYteuXYf8lfvr1q2LhoaGXvtmzpwZ69atSzFiyTuScxzhGu6LpqamuPrqqw+4Pg/Gddw3+ZzjCNdxvt59990YN25cnHbaaXHTTTfFli1bDnnsQF3DRb+r7WCzb9++mDdvXlxyySVx7rnnHvK4yZMnx1NPPRV1dXXR3d0dDzzwQFx88cXxzjvvxPjx4xNOXDo2btwY9fX1sXv37hg5cmQ888wzcfbZZx/02M7OzgN+I25NTU10dnamGLVk5XOOXcP5W7VqVbz99tuxfv36IzredZy/fM+x6zg/06dPjxUrVsTkyZNj27ZtsXjx4rjsssti06ZNMWrUqAOOH6hrWHzsp6mpKTZt2nTYn4FFRNTX1/f6H+XFF18cZ511VjzxxBPx4x//eKDHLEmTJ0+ODRs2RHd3d/z2t7+NW265JVpaWg75jyP5y+ccu4bz09HREXfddVesWbPGBxoHSF/Oses4P7Nmzcr9ua6uLqZPnx6nnHJKPP300zF37txkc4iPz7jjjjvi+eefj9deey3vYh4+fHh8+ctfjvfee2+Apit9I0aMiNNPPz0iIqZOnRrr16+PRx55JJ544okDjq2trY2urq5e+7q6uqK2tjbJrKUqn3O8P9fw4bW3t8f27dvj/PPPz+375JNP4rXXXouf//znkclk4phjjun1HNdxfvpyjvfnOs7P6NGj48wzzzzk+Rqoa9hnPiIim83GHXfcEc8880y88sorceqpp+b9Gp988kls3LgxTj755AGYcGjat29fZDKZgz5WX18fa9eu7bVvzZo1h/38Agc63Dnen2v48K644orYuHFjbNiwIbdNmzYtbrrpptiwYcNB/1F0HeenL+d4f67j/OzcuTPef//9Q56vAbuG+/Vx1SHi9ttvz1ZXV2dfffXV7LZt23Lbf/7zn9wx3/jGN7ILFizIfb148eLsyy+/nH3//fez7e3t2RtuuCFbWVmZfeedd4rxVxj0FixYkG1pacl+8MEH2T//+c/ZBQsWZMvKyrJ/+MMfstnsgef3jTfeyJaXl2cfeOCB7F//+tfsokWLssOHD89u3LixWH+FQS/fc+wa7r/9V2K4jgvv886x6zg/3/nOd7Kvvvpq9oMPPsi+8cYb2YaGhuwJJ5yQ3b59ezabTXcN+7FL/PeXM0VEXH755b32Nzc3x6233hoREVu2bIlhw/73RtG///3vuO2226KzszOOP/74mDp1arz55ps+v3AI27dvj5tvvjm2bdsW1dXVUVdXFy+//HJceeWVEXHg+b344otj5cqVcc8998QPf/jDOOOMM+LZZ5897IeAj3b5nmPXcOG5jgee67h/Pvzww7jxxhvjo48+ihNPPDEuvfTSaG1tjRNPPDEi0l3DZdlsNtuvVwAAyIPPfAAASYkPACAp8QEAJCU+AICkxAcAkJT4AACSEh8AQFLiAwBISnwAAEmJDwAgKfEBACQlPgCApP4fylVCkXloAZ4AAAAASUVORK5CYII=", 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" ] @@ -471,7 +425,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 176, "metadata": {}, "outputs": [], "source": [ @@ -481,7 +435,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 177, "metadata": {}, "outputs": [ { @@ -490,7 +444,7 @@ "(20,)" ] }, - "execution_count": 93, + "execution_count": 177, "metadata": {}, "output_type": "execute_result" } @@ -501,12 +455,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 178, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] diff --git a/chsh_error_bars_fidelity_clean.ipynb b/chsh_error_bars_fidelity_clean.ipynb index 500cb19..7aa0063 100644 --- a/chsh_error_bars_fidelity_clean.ipynb +++ b/chsh_error_bars_fidelity_clean.ipynb @@ -2,28 +2,42 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 56, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/victor/envs/qililab/lib/python3.10/site-packages/qiboconnection/api.py:217: UserWarning:This method is deprecated and will be removed in the following Qiboconnection release. Use device_id argument in execute() method instead.\n" + ] + } + ], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", - "from qibo.gates import M, X, RY, CZ, I, H\n", + "from qibo.gates import M, RY, CZ, I, H\n", "from qibo.models import Circuit\n", "from qiboconnection.api import API\n", - "import matplotlib.pyplot as plt\n", - "\n", "from qiboconnection.connection import ConnectionConfiguration\n", - "\n", + "from scipy import stats\n", "from benchmarks.utils.qst_qpt_helper_functions import process_returned_dataformat\n", "from time import sleep\n", + "import matplotlib\n", "\n", "from itertools import product\n", - "from scipy.stats import multivariate_normal\n", "api = API(ConnectionConfiguration(username=\"vsanchez\", api_key=\"ea712370-7516-4cbf-91a6-72a82e39ba02\"))\n", - "from scipy import stats\n", + "import logging\n", + "\n", + "api.select_device_id(9)\n", "\n", - "api.select_device_id(9)" + "logger = logging.getLogger()\n", + "handler = logging.StreamHandler()\n", + "formatter = logging.Formatter(\n", + " '%(asctime)s %(name)-12s %(levelname)-8s %(message)s')\n", + "handler.setFormatter(formatter)\n", + "logger.addHandler(handler)\n", + "logger.setLevel(logging.ERROR)" ] }, { @@ -35,20 +49,21 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 57, "metadata": {}, "outputs": [], "source": [ - "CONTROL_QUBIT = 2\n", - "TARGET_QUBIT = 0\n", + "CONTROL_QUBIT = 0\n", + "TARGET_QUBIT = 2\n", "THETA_VALUES = np.linspace(-np.pi, np.pi, num=20)\n", - "BELL_STATE = \"psi_minus\" # phi_plus, phi_minus, psi_plus, psi_minus\n", + "BELL_STATE = \"phi_plus\" # phi_plus, phi_minus, psi_plus, psi_minus\n", "\n", "NUM_SHOTS = 8000\n", + "result_id = 9536\n", "\n", "LOAD_RESULTS = True\n", - "mfidelity_qc = 0.88 # measurement fidelity control qubit\n", - "mfidelity_qt = 0.84 # measurement fidelity target qubit" + "mfidelity_qc = 0.882 # measurement fidelity control qubit\n", + "mfidelity_qt = 0.875 # measurement fidelity target qubit" ] }, { @@ -60,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 58, "metadata": {}, "outputs": [], "source": [ @@ -101,21 +116,7 @@ "\n", " return circuits\n", "\n", - "\n", - "def SPAM_circuits(control_qubit, target_qubit):\n", - " \"\"\"Circuits to get the SPAM matrix in order to perform measurement correction.\"\"\"\n", - " calibration_circuits = []\n", - " for gate_a, gate_b in product([I, X], repeat=2):\n", - " calibration_circuit = Circuit(5)\n", - " calibration_circuit.add(gate_a(control_qubit))\n", - " calibration_circuit.add(gate_b(target_qubit))\n", - " calibration_circuit.add(M(control_qubit, target_qubit))\n", - "\n", - " calibration_circuits.append(calibration_circuit)\n", - " return calibration_circuits\n", - "\n", - "\n", - "def compute_witnesses(chsh_results, measurement_calibration_weights, BELL_STATE, raw=False):\n", + "def compute_witnesses(chsh_results, BELL_STATE, ea=1, eb=1, raw=False):\n", " \"\"\"Returns arrays of computed witness values.\n", "\n", " Args:\n", @@ -134,6 +135,11 @@ " witness1 = np.zeros(len_theta_values)\n", " witness2 = np.zeros(len_theta_values)\n", "\n", + " e_m = np.array([[ea*eb, ea*(1-eb), eb*(1-ea), (1-ea)*(1-eb)],\n", + " [ea*(1-eb), ea*eb, (1-ea)*(1-eb), eb*(1-ea)],\n", + " [eb*(1-ea), (1-ea)*(1-eb), ea*eb, ea*(1-eb)],\n", + " [(1-ea)*(1-eb), ea*(1-eb), eb*(1-ea), ea*eb]])\n", + "\n", " if BELL_STATE in [\"phi_plus\", \"psi_minus\"]:\n", " signs1 = np.array([1, 1, -1, 1])\n", " signs2 = np.array([1, -1, 1, 1])\n", @@ -144,13 +150,11 @@ " for i, chsh_result in enumerate(chsh_results):\n", " if raw is not True:\n", " # apply measurement calibration\n", - " chsh_result = measurement_calibration_weights @ chsh_result.T\n", - " # calculate expectation values from probabilities\n", - " expectations = np.array([1, -1, -1, 1]).T @ chsh_result\n", + " # chsh_result = measurement_calibration_weights @ chsh_result.T\n", + " chsh_result = chsh_result @ np.linalg.inv(e_m)\n", "\n", - " else:\n", - " # calculate expectation values from probabilities\n", - " expectations = chsh_result @ np.array([1, -1, -1, 1])\n", + " # calculate expectation values from probabilities\n", + " expectations = chsh_result @ np.array([1, -1, -1, 1])\n", " # compute witnesses\n", " witness1[i] = signs1.T @ expectations\n", " witness2[i] = signs2.T @ expectations\n", @@ -166,18 +170,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 59, "metadata": {}, "outputs": [], "source": [ - "all_circuits_chsh = []\n", + "all_circuits = []\n", "for theta in THETA_VALUES:\n", " circuits_th = get_chsh_circuits(BELL_STATE, CONTROL_QUBIT, TARGET_QUBIT, theta)\n", - " all_circuits_chsh.extend(circuits_th)\n", - "\n", - "all_circuits = SPAM_circuits(CONTROL_QUBIT, TARGET_QUBIT)\n", - "\n", - "all_circuits.extend(all_circuits_chsh)" + " all_circuits.extend(circuits_th)" ] }, { @@ -189,14 +189,13 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 60, "metadata": {}, "outputs": [], "source": [ - "result_id = 8695\n", "\n", "if LOAD_RESULTS is False:\n", - " result_id = api.execute(all_circuits, nshots=NUM_SHOTS)[0]" + " result_id = api.execute(all_circuits, nshots=NUM_SHOTS)[0]" ] }, { @@ -208,106 +207,300 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 61, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Your job with id 8695 is completed.\n" + "/home/victor/envs/qililab/lib/python3.10/site-packages/qiboconnection/api.py:420: UserWarning:This method is deprecated and will be removed in a future qiboconnection version. Use get_job(job_id).result to retrieve your results instead.\n" ] }, { "data": { "text/plain": [ - "[{'probabilities': {'00': 0.7305, '01': 0.1315, '10': 0.1175, '11': 0.0205}},\n", - " {'probabilities': {'00': 0.158, '01': 0.717, '10': 0.0315, '11': 0.0935}},\n", - " {'probabilities': {'00': 0.1545, '01': 0.027, '10': 0.6985, '11': 0.12}},\n", - " {'probabilities': {'00': 0.0265, '01': 0.158, '10': 0.131, '11': 0.6845}},\n", - " {'probabilities': {'00': 0.429, '01': 0.088, '10': 0.0855, '11': 0.3975}},\n", - " {'probabilities': {'00': 0.26, '01': 0.2575, '10': 0.2405, '11': 0.242}},\n", - " {'probabilities': {'00': 0.27, '01': 0.263, '10': 0.254, '11': 0.213}},\n", - " {'probabilities': {'00': 0.392, '01': 0.1325, '10': 0.114, '11': 0.3615}},\n", - " {'probabilities': {'00': 0.4215, '01': 0.0925, '10': 0.099, '11': 0.387}},\n", - " {'probabilities': {'00': 0.2315, '01': 0.296, '10': 0.281, '11': 0.1915}},\n", - " {'probabilities': {'00': 0.3145, '01': 0.2135, '10': 0.2085, '11': 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{'probabilities': {'00': 0.39975,\n", + " '01': 0.153125,\n", + " '10': 0.111,\n", + " '11': 0.336125}},\n", + " {'probabilities': {'00': 0.318125,\n", + " '01': 0.229625,\n", + " '10': 0.203125,\n", + " '11': 0.249125}},\n", + " {'probabilities': {'00': 0.2645,\n", + " '01': 0.25575,\n", + " '10': 0.250125,\n", + " '11': 0.229625}},\n", + " {'probabilities': {'00': 0.122875,\n", + " '01': 0.399125,\n", + " '10': 0.397875,\n", + " '11': 0.080125}},\n", + " {'probabilities': {'00': 0.412875,\n", + " '01': 0.13825,\n", + " '10': 0.11075,\n", + " '11': 0.338125}},\n", + " {'probabilities': {'00': 0.271375,\n", + " '01': 0.27925,\n", + " '10': 0.2545,\n", + " '11': 0.194875}},\n", + " {'probabilities': {'00': 0.221625,\n", + " '01': 0.298,\n", + " '10': 0.298875,\n", + " '11': 0.1815}},\n", + " {'probabilities': {'00': 0.1415,\n", + " '01': 0.375375,\n", + " '10': 0.395625,\n", + " '11': 0.0875}},\n", + " {'probabilities': {'00': 0.40775, '01': 0.1405, '10': 0.10975, '11': 0.342}},\n", + " {'probabilities': {'00': 0.22025,\n", + " '01': 0.30925,\n", + " '10': 0.31175,\n", + " '11': 0.15875}},\n", + " {'probabilities': {'00': 0.1825,\n", + " '01': 0.34125,\n", + " '10': 0.326875,\n", + " '11': 0.149375}},\n", + " {'probabilities': {'00': 0.174, '01': 0.3575, '10': 0.35725, '11': 0.11125}},\n", + " {'probabilities': {'00': 0.381, '01': 0.145375, '10': 0.139, '11': 0.334625}},\n", + " {'probabilities': {'00': 0.181,\n", + " '01': 0.33875,\n", + " '10': 0.353125,\n", + " '11': 0.127125}},\n", + " {'probabilities': {'00': 0.16475,\n", + " '01': 0.370875,\n", + " '10': 0.346375,\n", + " '11': 0.118}},\n", + " {'probabilities': {'00': 0.22275,\n", + " '01': 0.31175,\n", + " '10': 0.30825,\n", + " '11': 0.15725}},\n", + " {'probabilities': {'00': 0.327875,\n", + " '01': 0.18325,\n", + " '10': 0.18525,\n", + " '11': 0.303625}},\n", + " {'probabilities': {'00': 0.1475,\n", + " '01': 0.363375,\n", + " '10': 0.3875,\n", + " '11': 0.101625}},\n", + " {'probabilities': {'00': 0.1515,\n", + " '01': 0.390125,\n", + " '10': 0.36275,\n", + " '11': 0.095625}},\n", + " {'probabilities': {'00': 0.270375,\n", + " '01': 0.26825,\n", + " '10': 0.270625,\n", + " '11': 0.19075}},\n", + " {'probabilities': {'00': 0.298375,\n", + " '01': 0.21775,\n", + " '10': 0.22425,\n", + " '11': 0.259625}},\n", + " {'probabilities': {'00': 0.129125, '01': 0.394875, '10': 0.4, '11': 0.076}},\n", + " {'probabilities': {'00': 0.1545, '01': 0.3975, '10': 0.3655, '11': 0.0825}},\n", + " {'probabilities': {'00': 0.3265,\n", + " '01': 0.217625,\n", + " '10': 0.21625,\n", + " '11': 0.239625}},\n", + " {'probabilities': {'00': 0.255375,\n", + " '01': 0.264375,\n", + " '10': 0.2615,\n", + " '11': 0.21875}},\n", + " {'probabilities': {'00': 0.13525,\n", + " '01': 0.38925,\n", + " '10': 0.39575,\n", + " '11': 0.07975}}]" ] }, - "execution_count": 6, + "execution_count": 61, "metadata": {}, "output_type": "execute_result" } @@ -316,7 +509,7 @@ "results = None\n", "while results is None:\n", " results = api.get_result(result_id)\n", - " sleep(30)\n", + " sleep(1)\n", "results" ] }, @@ -329,14 +522,45 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "def get_basis_elements_dict(nqubits):\n", + " basis_elements = {}\n", + " for i, x in enumerate(product(['0', '1'], repeat = nqubits)):\n", + " basis_elements[''.join(x)] = i\n", + " return basis_elements\n", + "\n", + "def process_returned_dataformat(results, nqubits=2):\n", + " \"\"\"Organises the results returned by qiboconnection into a matrix.\n", + "\n", + " Args:\n", + " results (list): list of result objects returned by qiboconnection\n", + " nqubits (int, optional): number of qubits. Defaults to 2.\n", + "\n", + " Returns:\n", + " res (array): matrix of dimensions (len(results), 2**nqubits) containing the\n", + " probabilities with which each bitstring was found for each circuit.\n", + " \"\"\"\n", + " res = np.zeros((len(results), 2**nqubits))\n", + " basis_elements_dict = get_basis_elements_dict(nqubits)\n", + " for i, result in enumerate(results):\n", + " for key, val in result[\"probabilities\"].items():\n", + " res[i, basis_elements_dict[key]] = val\n", + " return res" + ] + }, + { + "cell_type": "code", + "execution_count": 63, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Your job with id 8695 is completed.\n" + "/home/victor/envs/qililab/lib/python3.10/site-packages/qiboconnection/api.py:420: UserWarning:This method is deprecated and will be removed in a future qiboconnection version. Use get_job(job_id).result to retrieve your results instead.\n" ] } ], @@ -344,20 +568,10 @@ "## retrieve data\n", "results = api.get_result(result_id)\n", "data_probabilities = process_returned_dataformat(results, nqubits=2)\n", - "\n", - "## measurement calibration data processing\n", - "spam_data_probabilities = data_probabilities[:4]\n", - "measurement_calibration_weights = np.linalg.inv(spam_data_probabilities)\n", - "\n", - "## chsh circuits data processing\n", - "chsh_data_probabilities = data_probabilities[4:]\n", - "chsh_data_probabilities_theta = chsh_data_probabilities.reshape(len(THETA_VALUES), 4, 4)\n", - "\n", - "\n", "## compute witness\n", - "w1_raw, w2_raw = compute_witnesses(chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=True)\n", + "w1_raw, w2_raw = compute_witnesses(data_probabilities.reshape(len(THETA_VALUES), 4, 4), BELL_STATE, raw=True)\n", "w1_corrected, w2_corrected = compute_witnesses(\n", - " chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=False\n", + " data_probabilities.reshape(len(THETA_VALUES), 4, 4), BELL_STATE, ea=mfidelity_qc, eb=mfidelity_qt, raw=False\n", ")" ] }, @@ -370,33 +584,17 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 64, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[Qibo 0.1.12.dev0|INFO|2024-03-01 00:59:47]: Using numpy backend on /CPU:0\n" - ] - } - ], + "outputs": [], "source": [ - "circ_list = SPAM_circuits(0, 1)\n", - "ideal_results_spam = np.zeros((len(circ_list), 4))\n", - "for i, c in enumerate(circ_list):\n", - " ideal_results_spam[i] += c.execute().probabilities()\n", - "ideal_measurement_calibration_weights = np.linalg.inv(ideal_results_spam)\n", - "\n", - "circ_list = list(np.copy(all_circuits_chsh))\n", + "circ_list = list(np.copy(all_circuits))\n", "ideal_results_chsh = np.zeros((len(circ_list), 4))\n", "for i, c in enumerate(circ_list):\n", " ideal_results_chsh[i] += c.execute().probabilities()\n", "\n", - "ideal_results_chsh_theta = ideal_results_chsh.reshape(len(THETA_VALUES), 4, 4)\n", - "\n", "w1_ideal, w2_ideal = compute_witnesses(\n", - " ideal_results_chsh_theta, ideal_measurement_calibration_weights, BELL_STATE, raw=False\n", + " ideal_results_chsh.reshape(len(THETA_VALUES), 4, 4), BELL_STATE, ea=1, eb=1, raw=False\n", ")" ] }, @@ -409,30 +607,19 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 65, "metadata": {}, "outputs": [], "source": [ "def return_mock_results(data_probabilities, ea=1, eb=1):\n", " # returns simulated results using distribution from experimental results' probabilities\n", " mock_results = np.empty(shape=data_probabilities.shape)\n", - " # measurement_calibration_weights = np.linalg.inv(data_probabilities[:4])\n", - "\n", - " e_m = np.array([[ea*eb, ea*(1-eb), eb*(1-ea), (1-ea)*(1-eb)],\n", - " [ea*(1-eb), ea*eb, (1-ea)*(1-eb), eb*(1-ea)],\n", - " [eb*(1-ea), (1-ea)*(1-eb), ea*eb, ea*(1-eb)],\n", - " [(1-ea)*(1-eb), ea*(1-eb), eb*(1-ea), ea*eb]])\n", - " \n", - " for i, _ in enumerate(mock_results): \n", - " mock_results[i] = (stats.multinomial.rvs(NUM_SHOTS, data_probabilities[i]) / NUM_SHOTS) @ np.linalg.inv(e_m)\n", - "\n", - " measurement_calibration_weights = np.linalg.inv(data_probabilities[:4])\n", - " mock_results = mock_results[4:]\n", + " for i, _ in enumerate(mock_results):\n", + " mock_results[i] = (stats.multinomial.rvs(NUM_SHOTS, data_probabilities[i]) / NUM_SHOTS)\n", "\n", + " return list((compute_witnesses(mock_results.reshape(-1, 4, 4), BELL_STATE, ea=mfidelity_qc, eb=mfidelity_qt, raw=False) +\n", + " compute_witnesses(mock_results.reshape(-1, 4, 4), BELL_STATE, raw=True)))\n", "\n", - " return list((compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=False) +\n", - " compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=True)))\n", - " \n", "def get_err_bars(mock_results):\n", " data_hist = np.stack(mock_results)\n", " err_bars = np.empty(len(data_hist.T))\n", @@ -442,32 +629,7 @@ " return err_bars\n", "\n", "# generate n copies of random results\n", - "err_w1, err_w2, err_w1_unc, err_w2_unc = [get_err_bars(mock_results) for mock_results in zip(*[return_mock_results(data_probabilities, ea=mfidelity_qc, eb=mfidelity_qt) for _ in range(800)])]" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "data_a = np.array([return_mock_results(data_probabilities) for _ in range(1000)])\n", - "data_b =np.array([return_mock_results(data_probabilities, ea=mfidelity_qc, eb=mfidelity_qc) for _ in range(1000)])\n", - "\n", - "err_sys_w1 = []\n", - "for data_spam, data_fid in zip(data_a[:,0,:].T, data_b[:,2,:].T):\n", - " mean_spam, var_spam = stats.norm.fit(data_spam)\n", - " mean_fid, var_fid = stats.norm.fit(data_fid)\n", - " err_sys_w1.append(mean_fid - mean_spam)\n", - " \n", - "err_sys_w2 = []\n", - "for data_spam, data_fid in zip(data_a[:,1,:].T, data_b[:,3,:].T):\n", - " mean_spam, var_spam = stats.norm.fit(data_spam)\n", - " mean_fid, var_fid = stats.norm.fit(data_fid)\n", - " err_sys_w2.append(mean_fid - mean_spam)\n", - " \n", - "err_total_w1 = np.array([[err1, np.sqrt(err1**2+err2**2)] if err2 > 0 else [np.sqrt(err1**2 + err2**2), err1] for err1, err2 in zip(err_w1, err_sys_w1)])\n", - "err_total_w2 = np.array([[err1, np.sqrt(err1**2+err2**2)] if err2 > 0 else [np.sqrt(err1**2 + err2**2), err1] for err1, err2 in zip(err_w2, err_sys_w2)])" + "err_w1, err_w2, err_w1_unc, err_w2_unc = [get_err_bars(mock_results) for mock_results in zip(*[return_mock_results(data_probabilities, ea=mfidelity_qc, eb=mfidelity_qt) for _ in range(1000)])]" ] }, { @@ -479,14 +641,14 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 66, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] }, "metadata": {}, @@ -494,43 +656,34 @@ } ], "source": [ + "matplotlib.rcParams.update({'font.size': 14})\n", + "\n", "fname = f\"chsh_{CONTROL_QUBIT}_{TARGET_QUBIT}_{BELL_STATE}_nshots{NUM_SHOTS}_jobid{result_id}.png\"\n", "savefig = False\n", - "\n", - "fig, (ax0, ax1) = plt.subplots(1,2, sharey=True, figsize=(12, 6))\n", - "\n", - "ax0.plot(THETA_VALUES, w1_ideal, c=\"C0\", label=\"ideal\")\n", - "ax0.plot(THETA_VALUES, w1_corrected, \".\", c=\"C0\", label=\"corrected\")\n", - "ax0.plot(THETA_VALUES, w1_raw, \"x\", ms=3, c=\"C0\", label=\"raw\")\n", - "ax0.errorbar(THETA_VALUES, w1_corrected, err_total_w1.T, capsize=3, c=\"C0\", ls=\"none\")\n", + "bell_names = {\"phi_plus\": \"|$\\\\Phi^+\\\\rangle$\", \"phi_minus\": \"|$\\\\Phi^-\\\\rangle$\", \"psi_plus\": \"|$\\\\Psi^+\\\\rangle$\", \"psi_minus\": \"|$\\\\Psi^- \\\\rangle$\",}\n", + "fig, ax0 = plt.subplots(1, 1, figsize=(10, 6))\n", + "\n", + "# ideal\n", + "ax0.plot(THETA_VALUES, w1_ideal, c=\"grey\", label=\"ideal\")\n", + "# raw data\n", + "ax0.plot(THETA_VALUES, w1_raw, \"x\", c=\"C1\", label=\"raw data\")\n", + "ax0.errorbar(THETA_VALUES, w1_raw, err_w1_unc, capsize=3, c=\"C1\", ls=\"none\")\n", + "# corrected data\n", + "ax0.plot(THETA_VALUES, w1_corrected, \".\", c=\"C0\", label=\"RO corrected data\")\n", + "ax0.errorbar(THETA_VALUES, w1_corrected, err_w1, capsize=3, c=\"C0\", ls=\"none\")\n", "ax0.set_ylabel(\"witness 1\")\n", "\n", + "ax0.axhline(2, color=\"red\", linestyle=\"--\", label=\"classical bounds\")\n", + "ax0.axhline(-2, color=\"red\", linestyle=\"--\")\n", + "ax0.axhline(2 * np.sqrt(2), color=\"k\", linestyle=\"-.\", label=\"quantum bounds\")\n", + "ax0.axhline(-2 * np.sqrt(2), color=\"k\", linestyle=\"-.\")\n", + "ax0.set_xlabel(\"$\\\\theta$\")\n", + "ax0.legend()\n", "\n", - "ax1.plot(THETA_VALUES, w2_ideal,c=\"C1\", label=\"ideal\")\n", - "ax1.plot(THETA_VALUES, w2_corrected, \".\", c=\"C1\", label=\"corrected\")\n", - "ax1.plot(THETA_VALUES, w2_raw, \"x\", ms=3, c=\"C1\", label=\"raw\")\n", - "ax1.errorbar(THETA_VALUES, w2_corrected, err_total_w2.T, capsize=3, c=\"C1\", ls=\"none\")\n", - "ax1.set_ylabel(\"witness 2\")\n", - "\n", - "for ax in ax0, ax1:\n", - " ax.axhline(2, color=\"red\", linestyle=\"--\", label=\"classical bounds\")\n", - " ax.axhline(-2, color=\"red\", linestyle=\"--\")\n", - " ax.axhline(2 * np.sqrt(2), color=\"k\", linestyle=\"-.\", label=\"quantum bounds\")\n", - " ax.axhline(-2 * np.sqrt(2), color=\"k\", linestyle=\"-.\")\n", - " ax.set_xlabel(\"$\\\\theta$\")\n", - " ax.legend()\n", - "\n", - "fig.suptitle(f\"({CONTROL_QUBIT},{TARGET_QUBIT}), chsh bell: {BELL_STATE}\")\n", + "fig.suptitle(f\"CHSH {bell_names[BELL_STATE]} q({CONTROL_QUBIT},{TARGET_QUBIT})\")\n", "if savefig:\n", " fig.savefig(fname, bbox_inches=\"tight\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/chsh_error_bars_m.ipynb b/chsh_error_bars_m.ipynb new file mode 100644 index 0000000..b96a301 --- /dev/null +++ b/chsh_error_bars_m.ipynb @@ -0,0 +1,515 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from qibo.gates import M, X, RY, CZ, I, H\n", + "from qibo.models import Circuit\n", + "from qiboconnection.api import API\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from qiboconnection.connection import ConnectionConfiguration\n", + "\n", + "from benchmarks.utils.qst_qpt_helper_functions import process_returned_dataformat\n", + "\n", + "from itertools import product\n", + "from scipy.stats import multivariate_normal\n", + "api = API(ConnectionConfiguration(username=\"vsanchez\", api_key=\"ea712370-7516-4cbf-91a6-72a82e39ba02\"))\n", + "from scipy import stats\n", + "\n", + "api.select_device_id(9)" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [], + "source": [ + "def get_chsh_circuits(bell_state, control_qubit, target_qubit, theta):\n", + " assert bell_state in (\n", + " \"phi_plus\",\n", + " \"phi_minus\",\n", + " \"psi_plus\",\n", + " \"psi_minus\",\n", + " ), \"bell_state should be phi_plus, phi_minus, psi_plus, psi_minus\"\n", + " nqubits = max(control_qubit, target_qubit) + 1\n", + "\n", + " circuits = []\n", + " for gate_a, gate_b in product([I, H], repeat=2):\n", + " circuit = Circuit(nqubits)\n", + "\n", + " if bell_state == \"phi_plus\" or bell_state == \"psi_minus\":\n", + " G1 = RY(control_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G1 = RY(control_qubit, theta=np.pi / 2)\n", + " if bell_state == \"phi_plus\" or bell_state == \"phi_minus\":\n", + " G2_prime = RY(target_qubit, theta=-np.pi / 2)\n", + " else:\n", + " G2_prime = RY(target_qubit, theta=np.pi / 2)\n", + " ## build bell state\n", + " circuit.add(G1)\n", + " circuit.add(RY(target_qubit, theta=np.pi / 2))\n", + " circuit.add(CZ(control_qubit, target_qubit))\n", + " circuit.add(G2_prime)\n", + "\n", + " ## decoder part\n", + " circuit.add(RY(control_qubit, theta=theta))\n", + " circuit.add(gate_a(control_qubit))\n", + " circuit.add(gate_b(target_qubit))\n", + " circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " circuits.append(circuit)\n", + "\n", + " return circuits\n", + "\n", + "\n", + "def SPAM_circuits(control_qubit, target_qubit):\n", + " \"\"\"Circuits to get the SPAM matrix in order to perform measurement correction.\"\"\"\n", + " calibration_circuits = []\n", + " for gate_a, gate_b in product([I, X], repeat=2):\n", + " calibration_circuit = Circuit(5)\n", + " calibration_circuit.add(gate_a(control_qubit))\n", + " calibration_circuit.add(gate_b(target_qubit))\n", + " calibration_circuit.add(M(control_qubit, target_qubit))\n", + "\n", + " calibration_circuits.append(calibration_circuit)\n", + " return calibration_circuits\n", + "\n", + "\n", + "def compute_witnesses(chsh_results, measurement_calibration_weights, BELL_STATE, raw=False, spam_err=None):\n", + " \"\"\"Returns arrays of computed witness values.\n", + "\n", + " Args:\n", + " chsh_results (array): matrix containing the probabilities the chsh circuits. It must be\n", + " of dimensions len(theta_values) x 4 (decoder circuits) x 4 (probabilities)\n", + " measurement_calibration_weights (array): measurement calibration matrix.\n", + " BELL_STATE (string): can be \"phi_plus\", \"phi_minus\", \"psi_plus\" or \"psi_minus\". It needs\n", + " to be specified because the witness isn't the same for all 4 Bell states.\n", + " raw (bool): whether or not calculate the witnesses from the raw data instead of applying the\n", + " measurement corrections. Defaults to False.\n", + " Returns:\n", + " witness1 (array): array length len(theta_values) containing the first witness\n", + " witness2 (array): array length len(theta_values) containing the second witness\n", + " \"\"\"\n", + " len_theta_values = np.shape(chsh_results)[0]\n", + " witness1 = np.zeros(len_theta_values)\n", + " witness2 = np.zeros(len_theta_values)\n", + "\n", + " if BELL_STATE in [\"phi_plus\", \"psi_minus\"]:\n", + " signs1 = np.array([1, 1, -1, 1])\n", + " signs2 = np.array([1, -1, 1, 1])\n", + " else:\n", + " signs1 = np.array([-1, 1, 1, 1])\n", + " signs2 = np.array([1, 1, 1, -1])\n", + "\n", + " for i, chsh_result in enumerate(chsh_results):\n", + " if raw is not True:\n", + " # apply measurement calibration\n", + " chsh_result = measurement_calibration_weights @ chsh_result.T\n", + " # calculate expectation values from probabilities\n", + " expectations = np.array([1, -1, -1, 1]).T @ chsh_result\n", + " else:\n", + " # calculate expectation values from probabilities\n", + " expectations = chsh_result @ np.array([1, -1, -1, 1])\n", + " # compute witnesses\n", + " witness1[i] = signs1.T @ expectations\n", + " witness2[i] = signs2.T @ expectations\n", + " expectations_err = np.sum(chsh_result * (spam_err / measurement_calibration_weights)) if spam_err is not None else None\n", + "\n", + " return witness1, witness2, expectations_err" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "CONTROL_QUBIT = 2\n", + "TARGET_QUBIT = 0\n", + "THETA_VALUES = np.linspace(-np.pi, np.pi, num=20)\n", + "BELL_STATE = \"psi_minus\"\n", + "\n", + "NUM_SHOTS = 8000" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Build circuits for CHSH and measurement correction" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "all_circuits_chsh = []\n", + "for theta in THETA_VALUES:\n", + " circuits_th = get_chsh_circuits(BELL_STATE, CONTROL_QUBIT, TARGET_QUBIT, theta)\n", + " all_circuits_chsh.extend(circuits_th)\n", + "\n", + "all_circuits = SPAM_circuits(CONTROL_QUBIT, TARGET_QUBIT)\n", + "\n", + "all_circuits.extend(all_circuits_chsh)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run circuits" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "spam_ids = [api.execute(SPAM_circuits(CONTROL_QUBIT, TARGET_QUBIT), nshots=1000)[0] for _ in range(20)]\n", + "# spam_ids = [8714,8715,8716,8717,8718,8719,8720,8721,8722,8723]" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "{\n", + " \"title\": \"Unauthorized\",\n", + " \"status\": 401,\n", + " \"detail\": \"JWTExpired: Error verifying the authorisation access token. Expired at 1709130237, time: 1709130396(leeway: 60) 401 Client Error: for url: https://qilimanjaroqaas.ddns.net:8080/api/v1/jobs/8775\"\n", + "}\n", + "{\"title\":\"Unauthorized\",\"status\":401,\"detail\":\"JWTExpired: Error verifying the authorisation access token. Expired at 1709130237, time: 1709130396(leeway: 60)\"}\n", + "\n", + "Your job with id 8775 is completed.\n", + "Your job with id 8776 is completed.\n", + "Your job with id 8777 is completed.\n", + "Your job with id 8778 is completed.\n", + "Your job with id 8779 is completed.\n", + "Your job with id 8780 is completed.\n", + "Your job with id 8781 is completed.\n", + "Your job with id 8782 is completed.\n", + "Your job with id 8783 is completed.\n", + "Your job with id 8784 is completed.\n", + "Your job with id 8785 is completed.\n", + "Your job with id 8786 is completed.\n", + "Your job with id 8787 is completed.\n", + "Your job with id 8788 is completed.\n", + "Your job with id 8789 is completed.\n", + "Your job with id 8790 is completed.\n", + "Your job with id 8791 is completed.\n", + "Your job with id 8792 is completed.\n", + "Your job with id 8793 is completed.\n", + "Your job with id 8794 is completed.\n" + ] + } + ], + "source": [ + "spam_probs = [process_returned_dataformat(api.get_result(result_id), nqubits=2) for result_id in spam_ids]" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0.72745, 0.138 , 0.11175, 0.0228 ],\n", + " [0.12935, 0.7448 , 0.01975, 0.1061 ],\n", + " [0.11455, 0.02235, 0.7215 , 0.1416 ],\n", + " [0.02425, 0.1191 , 0.1386 , 0.71805]])" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "# result_id = api.execute(all_circuits, nshots=NUM_SHOTS)[0]\n", + "result_id = 8695" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "{\n", + " \"title\": \"Unauthorized\",\n", + " \"status\": 401,\n", + " \"detail\": \"JWTExpired: Error verifying the authorisation access token. Expired at 1709128245, time: 1709129530(leeway: 60) 401 Client Error: for url: https://qilimanjaroqaas.ddns.net:8080/api/v1/jobs/8695\"\n", + "}\n", + "{\"title\":\"Unauthorized\",\"status\":401,\"detail\":\"JWTExpired: Error verifying the authorisation access token. Expired at 1709128245, time: 1709129530(leeway: 60)\"}\n", + "\n", + "Your job with id 8695 is completed.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-02-28 15:12:10,283 - qm - INFO - Starting session: 48d1396e-53b6-4a74-9283-3ca0c91dcecc\n" + ] + }, + { + "data": { + "text/plain": [ + "JobData(completed_at='2024-02-27T15:40:53.374527+00:00', created_at='2024-02-27T15:39:18.481184+00:00', description=[, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ], device_id=9, execution_time=91.898192, execution_type='qililab', favourite=False, job_execution_time_mark='2024-02-27T15:39:22.266350+00:00', job_id=8695, job_postprocessing_time_mark='2024-02-27T15:40:53.373992+00:00', job_preprocessing_time_mark='2024-02-27T15:39:21.476335+00:00', job_processing_time_mark='2024-02-27T15:39:21.476469+00:00', 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0.3145, '01': 0.2135, '10': 0.2085, '11': 0.2635}}, {'probabilities': {'00': 0.3725, '01': 0.1255, '10': 0.123, '11': 0.379}}, {'probabilities': {'00': 0.3935, '01': 0.1275, '10': 0.13, '11': 0.349}}, {'probabilities': {'00': 0.1745, '01': 0.333, '10': 0.3315, '11': 0.161}}, {'probabilities': {'00': 0.362, '01': 0.182, '10': 0.1585, '11': 0.2975}}, {'probabilities': {'00': 0.3805, '01': 0.1465, '10': 0.1465, '11': 0.3265}}, {'probabilities': {'00': 0.3455, '01': 0.148, '10': 0.1695, '11': 0.337}}, {'probabilities': {'00': 0.1365, '01': 0.3505, '10': 0.3815, '11': 0.1315}}, {'probabilities': {'00': 0.374, '01': 0.1395, '10': 0.1185, '11': 0.368}}, {'probabilities': {'00': 0.367, '01': 0.1695, '10': 0.169, '11': 0.2945}}, {'probabilities': {'00': 0.3175, '01': 0.2065, '10': 0.218, '11': 0.258}}, {'probabilities': {'00': 0.138, '01': 0.367, '10': 0.3855, '11': 0.1095}}, {'probabilities': {'00': 0.41, '01': 0.1075, '10': 0.113, '11': 0.3695}}, {'probabilities': {'00': 0.3, '01': 0.215, '10': 0.219, '11': 0.266}}, {'probabilities': {'00': 0.2505, '01': 0.2425, '10': 0.2705, '11': 0.2365}}, {'probabilities': {'00': 0.1305, '01': 0.3705, '10': 0.391, '11': 0.108}}, {'probabilities': {'00': 0.4295, '01': 0.103, '10': 0.0885, '11': 0.379}}, {'probabilities': {'00': 0.275, '01': 0.262, '10': 0.248, '11': 0.215}}, {'probabilities': {'00': 0.2155, '01': 0.2785, '10': 0.316, '11': 0.19}}, {'probabilities': {'00': 0.136, '01': 0.3615, '10': 0.385, '11': 0.1175}}, {'probabilities': {'00': 0.397, '01': 0.095, '10': 0.129, '11': 0.379}}, {'probabilities': {'00': 0.206, '01': 0.298, '10': 0.2825, '11': 0.2135}}, {'probabilities': {'00': 0.168, '01': 0.3415, '10': 0.341, '11': 0.1495}}, {'probabilities': {'00': 0.1705, '01': 0.3445, '10': 0.3285, '11': 0.1565}}, {'probabilities': {'00': 0.379, '01': 0.1425, '10': 0.146, '11': 0.3325}}, {'probabilities': {'00': 0.1715, '01': 0.331, '10': 0.3375, '11': 0.16}}, {'probabilities': {'00': 0.1185, '01': 0.393, '10': 0.3705, '11': 0.118}}, {'probabilities': {'00': 0.1955, '01': 0.293, '10': 0.3325, '11': 0.179}}, {'probabilities': {'00': 0.348, '01': 0.17, '10': 0.172, '11': 0.31}}, {'probabilities': {'00': 0.1315, '01': 0.3505, '10': 0.3735, '11': 0.1445}}, {'probabilities': {'00': 0.1105, '01': 0.39, '10': 0.3995, '11': 0.1}}, {'probabilities': {'00': 0.2345, '01': 0.271, '10': 0.2655, '11': 0.229}}, {'probabilities': {'00': 0.2975, '01': 0.207, '10': 0.214, '11': 0.2815}}, {'probabilities': {'00': 0.132, '01': 0.369, '10': 0.367, '11': 0.132}}, {'probabilities': {'00': 0.109, '01': 0.4015, '10': 0.3915, '11': 0.098}}, {'probabilities': {'00': 0.249, '01': 0.2275, '10': 0.243, '11': 0.2805}}, {'probabilities': {'00': 0.236, '01': 0.259, '10': 0.263, '11': 0.242}}, {'probabilities': {'00': 0.1435, '01': 0.3635, '10': 0.369, '11': 0.124}}, {'probabilities': {'00': 0.129, '01': 0.374, '10': 0.3955, '11': 0.1015}}, {'probabilities': {'00': 0.322, '01': 0.1865, '10': 0.199, '11': 0.2925}}, {'probabilities': {'00': 0.2125, '01': 0.2735, '10': 0.3415, '11': 0.1725}}, {'probabilities': {'00': 0.152, '01': 0.363, '10': 0.377, '11': 0.108}}, {'probabilities': {'00': 0.164, '01': 0.351, '10': 0.3805, '11': 0.1045}}, {'probabilities': {'00': 0.3605, '01': 0.163, '10': 0.1555, '11': 0.321}}, {'probabilities': {'00': 0.148, '01': 0.333, '10': 0.375, '11': 0.144}}, {'probabilities': {'00': 0.172, '01': 0.332, '10': 0.345, '11': 0.151}}, {'probabilities': {'00': 0.202, '01': 0.318, '10': 0.3215, '11': 0.1585}}, {'probabilities': {'00': 0.3955, '01': 0.125, '10': 0.1225, '11': 0.357}}, {'probabilities': {'00': 0.1305, '01': 0.3745, '10': 0.3755, '11': 0.1195}}, {'probabilities': {'00': 0.196, '01': 0.302, '10': 0.317, '11': 0.185}}, {'probabilities': {'00': 0.2605, '01': 0.2595, '10': 0.267, '11': 0.213}}, {'probabilities': {'00': 0.3805, '01': 0.114, '10': 0.1235, '11': 0.382}}, {'probabilities': {'00': 0.1165, '01': 0.396, '10': 0.402, '11': 0.0855}}, {'probabilities': {'00': 0.238, '01': 0.251, '10': 0.2955, '11': 0.2155}}, {'probabilities': {'00': 0.2875, '01': 0.2215, '10': 0.237, '11': 0.254}}, {'probabilities': {'00': 0.3925, '01': 0.117, '10': 0.123, '11': 0.3675}}, {'probabilities': {'00': 0.124, '01': 0.407, '10': 0.3805, '11': 0.0885}}, {'probabilities': {'00': 0.29, '01': 0.23, '10': 0.229, '11': 0.251}}, {'probabilities': {'00': 0.3785, '01': 0.164, '10': 0.167, '11': 0.2905}}, {'probabilities': {'00': 0.373, '01': 0.138, '10': 0.143, '11': 0.346}}, {'probabilities': {'00': 0.14, '01': 0.362, '10': 0.398, '11': 0.1}}, {'probabilities': {'00': 0.323, '01': 0.1745, '10': 0.1805, '11': 0.322}}, {'probabilities': {'00': 0.3905, '01': 0.1355, '10': 0.1225, '11': 0.3515}}, {'probabilities': {'00': 0.354, '01': 0.166, '10': 0.1715, '11': 0.3085}}, {'probabilities': {'00': 0.1745, '01': 0.3405, '10': 0.342, '11': 0.143}}, {'probabilities': {'00': 0.36, '01': 0.155, '10': 0.169, '11': 0.316}}, {'probabilities': {'00': 0.4215, '01': 0.1015, '10': 0.0985, '11': 0.3785}}, {'probabilities': {'00': 0.2985, '01': 0.2175, '10': 0.2285, '11': 0.2555}}, {'probabilities': {'00': 0.1995, '01': 0.323, '10': 0.301, '11': 0.1765}}, {'probabilities': {'00': 0.397, '01': 0.132, '10': 0.1305, '11': 0.3405}}, {'probabilities': {'00': 0.427, '01': 0.0735, '10': 0.1035, '11': 0.396}}, {'probabilities': {'00': 0.2765, '01': 0.232, '10': 0.256, '11': 0.2355}}, {'probabilities': {'00': 0.2695, '01': 0.2455, '10': 0.2685, '11': 0.2165}}, {'probabilities': {'00': 0.407, '01': 0.1275, '10': 0.123, '11': 0.3425}}], slurm_job_id=18148, status='completed', summary='chsh demo for the APS march meeting', updated_at='2024-02-27T15:40:54.221663+00:00', user_id=31)" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results = api.get_job(result_id)\n", + "results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Process real data" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "{\n", + " \"title\": \"Unauthorized\",\n", + " \"status\": 401,\n", + " \"detail\": \"JWTExpired: Error verifying the authorisation access token. Expired at 1709130696, time: 1709131398(leeway: 60) 401 Client Error: for url: https://qilimanjaroqaas.ddns.net:8080/api/v1/jobs/8695\"\n", + "}\n", + "{\"title\":\"Unauthorized\",\"status\":401,\"detail\":\"JWTExpired: Error verifying the authorisation access token. Expired at 1709130696, time: 1709131398(leeway: 60)\"}\n", + "\n", + "Your job with id 8695 is completed.\n" + ] + } + ], + "source": [ + "## retrieve data\n", + "results = api.get_result(result_id)\n", + "data_probabilities = process_returned_dataformat(results, nqubits=2)\n", + "\n", + "## measurement calibration data processing\n", + "# spam_data_probabilities = data_probabilities[:4]\n", + "spam_data_probabilities = np.mean(spam_probs, axis=0)\n", + "measurement_calibration_weights = np.linalg.inv(spam_data_probabilities)\n", + "\n", + "## chsh circuits data processing\n", + "chsh_data_probabilities = data_probabilities[4:]\n", + "chsh_data_probabilities_theta = chsh_data_probabilities.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "\n", + "## compute witness\n", + "w1_raw, w2_raw, _ = compute_witnesses(chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=True)\n", + "w1_corrected, w2_corrected, spam_err = compute_witnesses(\n", + " chsh_data_probabilities_theta, measurement_calibration_weights, BELL_STATE, raw=False, spam_err = np.std(spam_probs, axis=0)\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run simulation, get ideal witnesses" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Qibo 0.1.12.dev0|INFO|2024-02-28 15:16:10]: Using numpy backend on /CPU:0\n" + ] + } + ], + "source": [ + "circ_list = SPAM_circuits(0, 1)\n", + "ideal_results_spam = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_spam[i] += c.execute().probabilities()\n", + "ideal_measurement_calibration_weights = np.linalg.inv(ideal_results_spam)\n", + "\n", + "circ_list = list(np.copy(all_circuits_chsh))\n", + "ideal_results_chsh = np.zeros((len(circ_list), 4))\n", + "for i, c in enumerate(circ_list):\n", + " ideal_results_chsh[i] += c.execute().probabilities()\n", + "\n", + "ideal_results_chsh_theta = ideal_results_chsh.reshape(len(THETA_VALUES), 4, 4)\n", + "\n", + "w1_ideal, w2_ideal = compute_witnesses(\n", + " ideal_results_chsh_theta, ideal_measurement_calibration_weights, BELL_STATE, raw=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get error bars" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "# def return_mock_results():\n", + "# # returns simulated results using distribution from experimental results' probabilities\n", + "# mock_results = data_probabilities[4:].copy()\n", + "# measurement_calibration_weights = np.linalg.inv(data_probabilities[:4]) \n", + "# for i, _ in enumerate(mock_results): \n", + "# mock_results[i] = stats.multinomial.rvs(NUM_SHOTS, mock_results[i]) / NUM_SHOTS\n", + "\n", + "# return list((compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=False) +\n", + "# compute_witnesses(mock_results.reshape(-1, 4, 4), measurement_calibration_weights, BELL_STATE, raw=True)))\n", + " \n", + "# def get_err_bars(mock_results):\n", + "# data_hist = np.stack(mock_results)\n", + "# err_bars = np.empty(len(data_hist.T))\n", + "# for i, hist in enumerate(data_hist.T):\n", + "# _ , var = stats.norm.fit(hist)\n", + "# err_bars[i] =np.sqrt(var)\n", + "# return err_bars\n", + "\n", + "# # generate n copies of random results\n", + "# err_w1, err_w2, err_w1_unc, err_w2_unc = [get_err_bars(mock_results) for mock_results in zip(*[return_mock_results() for _ in range(NUM_SHOTS)])]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fname = f\"chsh_{CONTROL_QUBIT}_{TARGET_QUBIT}_{BELL_STATE}_nshots{NUM_SHOTS}_jobid{result_id}.png\"\n", + "savefig = False\n", + "\n", + "fig, ax = plt.subplots()\n", + "ax.axhline(2, color=\"red\", linestyle=\"--\", label=\"classical bounds\")\n", + "ax.axhline(-2, color=\"red\", linestyle=\"--\")\n", + "ax.axhline(2 * np.sqrt(2), color=\"k\", linestyle=\"-.\", label=\"quantum bounds\")\n", + "ax.axhline(-2 * np.sqrt(2), color=\"k\", linestyle=\"-.\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_ideal, label=\"ideal\")\n", + "ax.plot(THETA_VALUES, w2_ideal)\n", + "\n", + "ax.plot(THETA_VALUES, w1_raw, \"x\", ms=3, c=\"C0\", label=\"raw\")\n", + "ax.errorbar(THETA_VALUES, w1_raw, err_w1_unc, capsize=3, c=\"C0\", ls=\"none\")\n", + "\n", + "ax.plot(THETA_VALUES, w2_raw, \"x\", ms=3, c=\"C1\")\n", + "ax.errorbar(THETA_VALUES, w2_raw, err_w2_unc, capsize=3, c=\"C1\", ls=\"none\")\n", + "\n", + "ax.plot(THETA_VALUES, w1_corrected, \".\", c=\"C0\", label=\"corrected\")\n", + "ax.errorbar(THETA_VALUES, w1_corrected, np.sqrt(err_w1**2 + spam_err**2), capsize=3, c=\"C0\", ls=\"none\")\n", + "\n", + "ax.plot(THETA_VALUES, w2_corrected, \".\", c=\"C1\")\n", + "ax.errorbar(THETA_VALUES, w2_corrected, np.sqrt(err_w2**2 + spam_err**2), capsize=3, c=\"C1\", ls=\"none\")\n", + "\n", + "ax.legend()\n", + "\n", + "ax.set_xlabel(\"$\\\\theta$\")\n", + "ax.set_ylabel(\"witness 1 (blue), witness 2 (orange)\")\n", + "\n", + "ax.set_title(f\"({CONTROL_QUBIT}, {TARGET_QUBIT}), bell: {BELL_STATE}\")\n", + "if savefig:\n", + " fig.savefig(fname, bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "LastMile", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From b193c8ed5364150cf64cafdde570a741bd2b7bb2 Mon Sep 17 00:00:00 2001 From: victor Date: Mon, 2 Sep 2024 18:02:21 +0200 Subject: [PATCH 3/3] update --- chsh_error_bars_fidelity_clean.ipynb | 37 +++++++++++++++++----------- 1 file changed, 23 insertions(+), 14 deletions(-) diff --git a/chsh_error_bars_fidelity_clean.ipynb b/chsh_error_bars_fidelity_clean.ipynb index 7aa0063..6da34d7 100644 --- a/chsh_error_bars_fidelity_clean.ipynb +++ b/chsh_error_bars_fidelity_clean.ipynb @@ -2,13 +2,15 @@ "cells": [ { "cell_type": "code", - "execution_count": 56, + "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ + "/home/victor/qilimanjaro/qiboconnection-portfolio/benchmarks/utils/qst_qpt_helper_functions.py:107: DeprecationWarning:invalid escape sequence '\\o'\n", + "/home/victor/qilimanjaro/qiboconnection-portfolio/benchmarks/utils/qst_qpt_helper_functions.py:202: DeprecationWarning:invalid escape sequence '\\o'\n", "/home/victor/envs/qililab/lib/python3.10/site-packages/qiboconnection/api.py:217: UserWarning:This method is deprecated and will be removed in the following Qiboconnection release. Use device_id argument in execute() method instead.\n" ] } @@ -49,7 +51,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -75,7 +77,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -170,7 +172,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -189,7 +191,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -207,7 +209,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -500,7 +502,7 @@ " '11': 0.07975}}]" ] }, - "execution_count": 61, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -522,7 +524,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -553,7 +555,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -584,14 +586,14 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "circ_list = list(np.copy(all_circuits))\n", "ideal_results_chsh = np.zeros((len(circ_list), 4))\n", "for i, c in enumerate(circ_list):\n", - " ideal_results_chsh[i] += c.execute().probabilities()\n", + " ideal_results_chsh[i] += c.execute().probabilities(qubits=[TARGET_QUBIT, CONTROL_QUBIT])\n", "\n", "w1_ideal, w2_ideal = compute_witnesses(\n", " ideal_results_chsh.reshape(len(THETA_VALUES), 4, 4), BELL_STATE, ea=1, eb=1, raw=False\n", @@ -607,7 +609,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -641,12 +643,12 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -684,6 +686,13 @@ "if savefig:\n", " fig.savefig(fname, bbox_inches=\"tight\")" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": {