Docs preview for PR #3332.

Author: cuda-quantum-bot

pr-3332/_images/qpus.png

@@ -280,3 +280,76 @@ Submitting
     The OQC quantum assembly toolchain (qat) which is used to compile and execute instructions can be found on github as `oqc-community/qat <https://github.com/oqc-community/qat>`__
 
 To see a complete example, take a look at :ref:`OQC examples <oqc-examples>`.
+
+
+Quantum Circuits, Inc.
++++++++++++++++++++++++
+
+.. _qci-backend:
+
+As part of its first phase of integration with CUDA-Q,
+`Quantum Circuits <https://quantumcircuits.com/>`__ offers users the ability to simulate CUDA-Q
+programs using its simulator, AquSim. AquSim is the first simulator that models error detection and
+real-time control of Quantum Circuits' Dual-Rail Cavity Qubit systems, and uses a Monte Carlo
+approach to do so on a shot-by-shot basis.
+
+In this first phase, the supported features include all of the single and two-qubit gates offered by
+CUDA-Q, together with real-time conditional logic enabled by feed-forward capability. AquSim is
+currently wired to support ideal simulations only and noise models will be added in future
+iterations.
+
+With C++ and Python programming supported, users are able to prototype, test and explore quantum
+applications in CUDA-Q in preparation for upcoming releases targeting Quantum Circuits QPUs.
+Examples are provided to get started.
+
+Users who wish to get started with running CUDA-Q on AquSim should visit our
+`Explore <https://quantumcircuits.com/explore/>`__ page to learn more about the Quantum Circuits
+Strategic Quantum Release Program.
+
+Submitting
+`````````````````````````
+
+Until CUDA-Q release 0.13.0 is available, the integration with Quantum Circuits will be supported
+through the nightly build Docker images.
+
+Instructions on how to install and get started with CUDA-Q using Docker can be found :ref:`here <install-docker-image>`.
+
+You may present your user token to Quantum Circuits via CUDA-Q by setting an environment variable
+named :code:`QCI_AUTH_TOKEN` before running your CUDA-Q program.
+
+.. code:: bash
+
+    export QCI_AUTH_TOKEN="example-token"
+
+
+.. tab:: Python
+
+        To set the target to Quantum Circuits, add the following to your Python
+        program:
+
+        .. code:: python
+
+            cudaq.set_target('qci')
+            [... your Python here]
+
+        To run on AquSim, simply execute the script using your Python interpreter.
+
+.. tab:: C++
+
+        When executing programs in C++, they must first be compiled using the
+        CUDA-Q nvq++ compiler, and then submitted to run on AquSim.
+
+        Note that your token is fetched from your environment at run time, not at compile time.
+
+        In the example below, the compilation step shows two flags being passed to the nvq++
+        compiler: the Quantum Circuits target :code:`--target qci`, and the output file
+        :code:`-o example.x`.  The second line executes the program against AquSim. Here are the
+        shell commands in full:
+
+        .. code:: bash
+
+            nvq++ example.cpp --target qci -o example.x
+            ./example.x
+
+To see a complete example of using Quantum Circuits' backends, please take a look at the
+:ref:`Quantum Circuits examples <quantum-circuits-examples>`.

pr-3332/_sources/applications/python/generate_fermionic_ham.ipynb.txt

@@ -16,7 +16,7 @@ Moreover, since quantum kernels are functions, there is more expressibility avai
 standard quantum circuit. We can not only parameterize the kernel, but can also contain classical control
 flow statements (`if`, `for`, `while`, etc.), and classical computations such as additions, multiplication, etc.
 Conditional statements on quantum memory and qubit measurements can be included in quantum kernels to enable 
-dynamic circuits and fast feedback, particularly useful for quantum error correction. To learn more about what
+dynamic circuits and fast feedback, which are particularly useful for quantum error correction. To learn more about what
 language constructs are supported within quantum kernels, take a look at the CUDA-Q 
 :doc:`specification <../../specification/cudaq/kernels>`.
 

pr-3332/_sources/using/backends/hardware/superconducting.rst.txt

@@ -113,28 +113,28 @@ is available, for example, by choosing the target `nvidia-mqpu`:
 .. note::
 
   This kind of parallelization is most effective
-  if you actually have multiple QPU or CPU available. Otherwise, the 
+  if you actually have multiple QPUs or GPUs available. Otherwise, the 
   sampling will still have to execute sequentially due to resource constraints. 
 
-More information about parallelizing execution can be found at :ref:`mqpu-platform`  page.
+More information about parallelizing execution can be found on the :ref:`mqpu-platform`  page.
 
 Run
 +++++++++
 
 The `run` method executes a quantum kernel multiple times and returns each individual result. Unlike `sample`, 
-which collects measurement statistics as counts, `run` preserves each individual return value from every 
-execution. This is useful when you need to analyze the distribution of returned values rather than just 
+which collects measurement statistics as counts, `run` preserves each individual return value from each 
+execution. This is useful when you need to analyze the distribution of returned values which may not be possible from just 
 aggregated measurement counts. Additionally, the `run` method also supports returning various types of values 
 from the quantum kernel, including scalar types (bool, int, float and their variants) and user-defined data structures.
 
 .. tab:: Python
 
-  The ``cudaq.run`` method takes a kernel and its arguments as inputs, and returns a list containing 
+  The ``cudaq.run`` method takes a kernel and its arguments as inputs and returns a list containing 
   the result values from each execution. The kernel must return a non-void value.
 
 .. tab:: C++
 
-  The ``cudaq::run`` method takes a kernel and its arguments as inputs, and returns a `std::vector` containing
+  The ``cudaq::run`` method takes a kernel and its arguments as inputs and returns a `std::vector` containing
   the result values from each execution. The kernel must return a non-void value.
 
 Below is an example of a quantum kernel that creates a GHZ state, measures all qubits, and returns the total 
@@ -231,7 +231,7 @@ The observe function allows us to calculate expectation values for a defined qua
 
 Below is an example of a spin operator object consisting of a `Z(0)` operator, or a Pauli Z-operator on the qubit zero. 
 This is followed by the construction of a kernel with a single qubit in an equal superposition. 
-The Hamiltonian is printed to confirm it has been constructed properly.
+The Hamiltonian is printed to confirm that it has been constructed properly.
 
 .. tab:: Python
 
@@ -321,7 +321,7 @@ all of the available targets and ways to accelerate kernel execution, visit the
 
   To compare the performance, we can create a simple timing script that isolates just the call
   to `cudaq::sample`. We are still using the same GHZ kernel as earlier, but the following
-  modification made to the main function:
+  modification is made to the main function:
 
   .. literalinclude:: ../../snippets/cpp/using/time.cpp
     :language: cpp

pr-3332/_sources/using/basics/kernel_intro.rst.txt

@@ -191,6 +191,23 @@ The following code illustrates how to run kernels on Quantinuum's backends.
       :language: cpp
 
 
+.. _quantum-circuits-examples:
+
+Quantum Circuits, Inc.
+========================
+
+The following code illustrates how to run kernels on Quantum Circuits' backends.
+
+.. tab:: Python
+
+   .. literalinclude:: ../../targets/python/qci.py
+      :language: python
+
+.. tab:: C++
+
+   .. literalinclude:: ../../targets/cpp/qci.cpp
+      :language: cpp
+
 .. _quantum-machines-examples:
 
 Quantum Machines

pr-3332/_sources/using/basics/run_kernel.rst.txt

@@ -211,6 +211,7 @@
 <li class="toctree-l3"><a class="reference internal" href="../using/examples/hardware_providers.html#orca-computing">ORCA Computing</a></li>
 <li class="toctree-l3"><a class="reference internal" href="../using/examples/hardware_providers.html#pasqal">Pasqal</a></li>
 <li class="toctree-l3"><a class="reference internal" href="../using/examples/hardware_providers.html#quantinuum">Quantinuum</a></li>
+<li class="toctree-l3"><a class="reference internal" href="../using/examples/hardware_providers.html#quantum-circuits-inc">Quantum Circuits, Inc.</a></li>
 <li class="toctree-l3"><a class="reference internal" href="../using/examples/hardware_providers.html#quantum-machines">Quantum Machines</a></li>
 <li class="toctree-l3"><a class="reference internal" href="../using/examples/hardware_providers.html#quera-computing">QuEra Computing</a></li>
 </ul>
@@ -458,16 +459,13 @@
 <li class="toctree-l2"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html">Generating the electronic Hamiltonian</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#Second-Quantized-formulation.">Second Quantized formulation.</a><ul>
 <li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#Computational-Implementation">Computational Implementation</a></li>
-</ul>
-</li>
-<li class="toctree-l3"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(a)-Generate-the-molecular-Hamiltonian-using-Hartree-Fock-molecular-orbitals">(a) Generate the molecular Hamiltonian using Hartree Fock molecular orbitals</a><ul>
-<li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#Active-space-Hamiltonian:">Active space Hamiltonian:</a></li>
-</ul>
-</li>
-<li class="toctree-l3"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(b)-Generate-the-active-space-hamiltonian-using-HF-molecular-orbitals.">(b) Generate the active space hamiltonian using HF molecular orbitals.</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(c)-Generate-the-active-space-Hamiltonian-using-the-natural-orbitals-computed-from-MP2-simulation">(c) Generate the active space Hamiltonian using the natural orbitals computed from MP2 simulation</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(d)-Generate-the-active-space-Hamiltonian-computed-from-the-CASSCF-molecular-orbitals">(d) Generate the active space Hamiltonian computed from the CASSCF molecular orbitals</a><ul>
-<li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#Generate-the-electronic-Hamiltonian-using-ROHF">Generate the electronic Hamiltonian using ROHF</a></li>
+<li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(a)-Generate-the-molecular-Hamiltonian-using-Restricted-Hartree-Fock-molecular-orbitals">(a) Generate the molecular Hamiltonian using Restricted Hartree Fock molecular orbitals</a></li>
+<li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(b)-Generate-the-molecular-Hamiltonian-using-Unrestricted-Hartree-Fock-molecular-orbitals">(b) Generate the molecular Hamiltonian using Unrestricted Hartree Fock molecular orbitals</a></li>
+<li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(a)-Generate-the-active-space-hamiltonian-using-RHF-molecular-orbitals.">(a) Generate the active space hamiltonian using RHF molecular orbitals.</a></li>
+<li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(b)-Generate-the-active-space-Hamiltonian-using-the-natural-orbitals-computed-from-MP2-simulation">(b) Generate the active space Hamiltonian using the natural orbitals computed from MP2 simulation</a></li>
+<li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(c)-Generate-the-active-space-Hamiltonian-computed-from-the-CASSCF-molecular-orbitals">(c) Generate the active space Hamiltonian computed from the CASSCF molecular orbitals</a></li>
+<li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(d)-Generate-the-electronic-Hamiltonian-using-ROHF">(d) Generate the electronic Hamiltonian using ROHF</a></li>
+<li class="toctree-l4"><a class="reference internal" href="../applications/python/generate_fermionic_ham.html#(e)-Generate-electronic-Hamiltonian-using-UHF">(e) Generate electronic Hamiltonian using UHF</a></li>
 </ul>
 </li>
 </ul>
@@ -561,6 +559,7 @@
 <li class="toctree-l4"><a class="reference internal" href="../using/backends/hardware/superconducting.html#anyon-technologies-anyon-computing">Anyon Technologies/Anyon Computing</a></li>
 <li class="toctree-l4"><a class="reference internal" href="../using/backends/hardware/superconducting.html#iqm">IQM</a></li>
 <li class="toctree-l4"><a class="reference internal" href="../using/backends/hardware/superconducting.html#oqc">OQC</a></li>
+<li class="toctree-l4"><a class="reference internal" href="../using/backends/hardware/superconducting.html#quantum-circuits-inc">Quantum Circuits, Inc.</a></li>
 </ul>
 </li>
 <li class="toctree-l3"><a class="reference internal" href="../using/backends/hardware/neutralatom.html">     Neutral Atom QPUs</a><ul>