Docs preview for PR #2542.

pr-2542/_sources/api/default_ops.rst.txt

@@ -650,7 +650,7 @@ defined by the qudit level that represents the qumode. If it is applied to a qum
 where the number of photons is already at the maximum value, the operation has no
 effect.
 
-:math:`U|0\rangle → |1\rangle, U|1\rangle → |2\rangle, U|2\rangle → |3\rangle, \cdots, U|d\rangle → |d\rangle`
+:math:`C|0\rangle → |1\rangle, C|1\rangle → |2\rangle, C|2\rangle → |3\rangle, \cdots, C|d\rangle → |d\rangle`
 where :math:`d` is the qudit level.
 
 .. tab:: Python
@@ -674,7 +674,7 @@ This operation reduces the number of photons in a qumode up to a minimum value o
 0 representing the vacuum state. If it is applied to a qumode where the number of
 photons is already at the minimum value 0, the operation has no effect.
 
-:math:`U|0\rangle → |0\rangle, U|1\rangle → |0\rangle, U|2\rangle → |1\rangle, \cdots, U|d\rangle → |d-1\rangle`
+:math:`A|0\rangle → |0\rangle, A|1\rangle → |0\rangle, A|2\rangle → |1\rangle, \cdots, A|d\rangle → |d-1\rangle`
 where :math:`d` is the qudit level.
 
 .. tab:: Python

pr-2542/_sources/examples/python/executing_photonic_kernels.ipynb.txt

@@ -0,0 +1,171 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Executing Quantum Photonic Circuits \n",
+    "\n",
+    "In CUDA-Q, there are 2 ways in which one can execute quantum photonic kernels: \n",
+    "\n",
+    "1. `sample`: yields measurement counts \n",
+    "3. `get_state`: yields the quantum statevector of the computation \n",
+    "\n",
+    "## Sample\n",
+    "\n",
+    "Quantum states collapse upon measurement and hence need to be sampled many times to gather statistics. The CUDA-Q `sample` call enables this: \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cudaq\n",
+    "import numpy as np\n",
+    "\n",
+    "qumode_count = 2\n",
+    "\n",
+    "# Define the simulation target.\n",
+    "cudaq.set_target(\"orca-photonics\")\n",
+    "\n",
+    "# Define a quantum kernel function.\n",
+    "\n",
+    "\n",
+    "@cudaq.kernel\n",
+    "def kernel(qumode_count: int):\n",
+    "    level = qumode_count + 1\n",
+    "    qumodes = [qudit(level) for _ in range(qumode_count)]\n",
+    "\n",
+    "    # Apply the create gate to the qumodes.\n",
+    "    for i in range(qumode_count):\n",
+    "        create(qumodes[i])  # |00⟩ -> |11⟩\n",
+    "\n",
+    "    # Apply the beam_splitter gate to the qumodes.\n",
+    "    beam_splitter(qumodes[0], qumodes[1], np.pi / 6)\n",
+    "\n",
+    "    # measure all qumodes\n",
+    "    mz(qumodes)\n",
+    "\n",
+    "\n",
+    "result = cudaq.sample(kernel, qumode_count, shots_count=1000)\n",
+    "\n",
+    "print(result)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Get state\n",
+    "\n",
+    "The `get_state` function gives us access to the quantum statevector of the computation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cudaq\n",
+    "import numpy as np\n",
+    "\n",
+    "qumode_count = 2\n",
+    "\n",
+    "# Define the simulation target.\n",
+    "cudaq.set_target(\"orca-photonics\")\n",
+    "\n",
+    "# Define a quantum kernel function.\n",
+    "\n",
+    "\n",
+    "@cudaq.kernel\n",
+    "def kernel(qumode_count: int):\n",
+    "    level = qumode_count + 1\n",
+    "    qumodes = [qudit(level) for _ in range(qumode_count)]\n",
+    "\n",
+    "    # Apply the create gate to the qumodes.\n",
+    "    for i in range(qumode_count):\n",
+    "        create(qumodes[i])  # |00⟩ -> |11⟩\n",
+    "\n",
+    "    # Apply the beam_splitter gate to the qumodes.\n",
+    "    beam_splitter(qumodes[0], qumodes[1], np.pi / 6)\n",
+    "\n",
+    "    # measure some of all qumodes if need to be measured\n",
+    "    # mz(qumodes)\n",
+    "\n",
+    "\n",
+    "# Compute the statevector of the kernel\n",
+    "result = cudaq.get_state(kernel, qumode_count)\n",
+    "\n",
+    "print(np.array(result))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The statevector generated by the `get_state` command follows little-endian convention for associating numbers with their digit string representations, which places the least significant digit on the right. That is, for the example of a 2-qumode system of level 3 (in which possible states are 0, 1, and 2), we have the following translation between integers and digit string:\n",
+    "$$\\begin{matrix} \n",
+    "\\text{Integer} & \\text{digit string representation}\\\\\n",
+    "& \\text{least significant bit on right}\\\\\n",
+    "0 = \\textcolor{blue}{0}*3^1 + \\textcolor{red}{0}*3^0 & \\textcolor{blue}{0}\\textcolor{red}{0} \\\\\n",
+    "1 = \\textcolor{blue}{0}*3^1 + \\textcolor{red}{1}*3^0 & \\textcolor{blue}{0}\\textcolor{red}{1}\\\\\n",
+    "2 = \\textcolor{blue}{0}*3^1 + \\textcolor{red}{2}*3^0 & \\textcolor{blue}{0}\\textcolor{red}{2}\\\\\n",
+    "3 = \\textcolor{blue}{1}*3^1 + \\textcolor{red}{0}*3^0 & \\textcolor{blue}{1}\\textcolor{red}{0} \\\\\n",
+    "4 = \\textcolor{blue}{1}*3^1 + \\textcolor{red}{1}*3^0 & \\textcolor{blue}{1}\\textcolor{red}{1} \\\\\n",
+    "5 = \\textcolor{blue}{1}*3^1 + \\textcolor{red}{2}*3^0 & \\textcolor{blue}{1}\\textcolor{red}{2} \\\\\n",
+    "6 = \\textcolor{blue}{2}*3^1 + \\textcolor{red}{0}*3^0 & \\textcolor{blue}{2}\\textcolor{red}{0} \\\\\n",
+    "7 = \\textcolor{blue}{2}*3^1 + \\textcolor{red}{1}*3^0 & \\textcolor{blue}{2}\\textcolor{red}{1} \\\\\n",
+    "8 = \\textcolor{blue}{2}*3^1 + \\textcolor{red}{2}*3^0 & \\textcolor{blue}{2}\\textcolor{red}{2} \n",
+    "\\end{matrix}\n",
+    "$$\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Parallelization Techniques\n",
+    "\n",
+    "The most intensive task in the computation is the execution of the quantum photonic kernel hence each execution function: `sample`, and `get_state` can be parallelized given access to multiple quantum processing units (multi-QPU). We emulate each QPU with a CPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(cudaq.__version__)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": 4
+}

pr-2542/_sources/using/backends/simulators.rst.txt

@@ -591,6 +591,45 @@ To execute a program on the :code:`stim` target, use the following commands:
     can be slower than executing Stim a single time and generating all the shots
     from that single execution.
 
+
+Photonics Simulators
+==================================
+
+The :code:`orca-photonics` target provides a state vector simulator with 
+the :code:`Q++` library. 
+
+The :code:`orca-photonics` target supports supports a double precision simulator that can run in multiple CPUs.
+
+OpenMP CPU-only
+++++++++++++++++++++++++++++++++++
+
+.. _qpp-cpu-photonics-backend:
+
+This target provides a state vector simulator based on the CPU-only, OpenMP threaded `Q++ <https://github.com/softwareqinc/qpp>`_  library.
+
+To execute a program on the :code:`orca-photonics` target, use the following commands:
+
+.. tab:: Python
+
+    .. code:: bash 
+
+        python3 program.py [...] --target orca-photonics
+
+    The target can also be defined in the application code by calling
+
+    .. code:: python 
+
+        cudaq.set_target('orca-photonics')
+
+    If a target is set in the application code, this target will override the :code:`--target` command line flag given during program invocation.
+
+.. tab:: C++
+
+    .. code:: bash 
+
+        nvq++ --library-mode --target orca-photonics program.cpp [...] -o program.x
+
+
 Fermioniq
 ==================================
 

pr-2542/_sources/using/examples/examples.rst.txt

@@ -10,9 +10,11 @@ Examples that illustrate how to use CUDA-Q for application development are avail
       Introduction <introduction.rst>
       Building Kernels <building_kernels.rst>
       Quantum Operations <quantum_operations.rst>
+      Photonic Operations <photonic_operations.rst>
       Measuring Kernels <../../examples/python/measuring_kernels.ipynb>
       Visualizing Kernels <../../examples/python/visualization.ipynb>
       Executing Kernels <../../examples/python/executing_kernels.ipynb>
+      Executing Photonic Kernels <../../examples/python/executing_photonic_kernels.ipynb>
       Computing Expectation Values <expectation_values.rst>
       Multi-Control Synthesis <multi_control.rst>
       Multi-GPU Workflows <multi_gpu_workflows.rst>