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Update neutral atom documentation (#2734)
* Update neutral atom docs Signed-off-by: Dobri Y <dyordanov@nvidia.com> * Proper whitespace for docs Signed-off-by: Bettina Heim <heimb@outlook.com> --------- Signed-off-by: Dobri Y <dyordanov@nvidia.com> Signed-off-by: Bettina Heim <heimb@outlook.com> Co-authored-by: Bettina Heim <heimb@outlook.com>
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‎docs/sphinx/using/backends/hardware/neutralatom.rst‎

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@@ -177,56 +177,108 @@ Alternatively, users can set the following environment variables directly.
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export PASQAL_PROJECT_ID=<>
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Submission from Python
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Submitting
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`````````````````````````
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.. tab:: Python
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The target to which quantum kernels are submitted
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can be controlled with the ``cudaq::set_target()`` function.
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The target to which quantum kernels are submitted
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can be controlled with the ``cudaq::set_target()`` function.
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.. code:: python
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.. code:: python
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cudaq.set_target('pasqal')
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cudaq.set_target('pasqal')
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This accepts an optional argument, ``machine``, which is used in the cloud platform to
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select the corresponding Pasqal QPU or emulator to execute on.
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See the `Pasqal cloud portal <https://portal.pasqal.cloud/>`__ for an up to date list.
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The default value is ``EMU_MPS`` which is an open-source tensor network emulator based on the
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Matrix Product State formalism running in Pasqal's cloud platform. You can see the
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documentation for the publicly accessible emulator `here <https://pasqal-io.github.io/emulators/latest/emu_mps/>`__.
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This accepts an optional argument, ``machine``, which is used in the cloud platform to
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select the corresponding Pasqal QPU or emulator to execute on.
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See the `Pasqal cloud portal <https://portal.pasqal.cloud/>`__ for an up to date list.
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The default value is ``EMU_MPS`` which is an open-source tensor network emulator based on the
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Matrix Product State formalism running in Pasqal's cloud platform. You can see the
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documentation for the publicly accessible emulator `here <https://pasqal-io.github.io/emulators/latest/emu_mps/>`__.
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To target the QPU use the FRESNEL machine name. Note that there are restrictions
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regarding the values of the pulses as well as the register layout. We invite you to
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consult our `documentation <https://docs.pasqal.com/cloud/fresnel-job>`__. Note that
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the CUDA-Q integration currently only works with `arbitrary layouts <https://docs.pasqal.com/cloud/fresnel-job/#arbitrary-layouts>`__
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which are implemented with automatic calibration for less than 30 qubits. For jobs
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larger than 30 qubits please use the `atom_sites` to define the layout, and use the
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`atom_filling` to select sites as filled or not filled in order to define the register.
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To target the QPU use the FRESNEL machine name. Note that there are restrictions
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regarding the values of the pulses as well as the register layout. We invite you to
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consult our `documentation <https://docs.pasqal.com/cloud/fresnel-job>`__. Note that
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the CUDA-Q integration currently only works with `arbitrary layouts <https://docs.pasqal.com/cloud/fresnel-job/#arbitrary-layouts>`__
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which are implemented with automatic calibration for less than 30 qubits. For jobs
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larger than 30 qubits please use the `atom_sites` to define the layout, and use the
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`atom_filling` to select sites as filled or not filled in order to define the register.
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Due to the nature of the underlying hardware, this target only supports the
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``evolve`` and ``evolve_async`` APIs.
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The `hamiltonian` must be an `Operator` of the type `RydbergHamiltonian`. The only
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other supported parameters are `schedule` (mandatory) and `shots_count` (optional).
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Due to the nature of the underlying hardware, this target only supports the
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``evolve`` and ``evolve_async`` APIs.
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The `hamiltonian` must be an `Operator` of the type `RydbergHamiltonian`. The only
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other supported parameters are `schedule` (mandatory) and `shots_count` (optional).
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For example,
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For example,
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.. code:: python
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.. code:: python
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evolution_result = evolve(RydbergHamiltonian(atom_sites=register,
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amplitude=omega,
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phase=phi,
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delta_global=delta),
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schedule=schedule)
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The number of shots for a kernel execution can be set through the ``shots_count``
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argument to ``evolve`` or ``evolve_async``. By default, the ``shots_count`` is
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set to 100.
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.. code:: python
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cudaq.evolve(RydbergHamiltonian(...), schedule=s, shots_count=1000)
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To see a complete example for using Pasqal's backend, take a look at our :doc:`Python examples <../../examples/hardware_providers>`.
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.. tab:: C++
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evolution_result = evolve(RydbergHamiltonian(atom_sites=register,
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amplitude=omega,
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phase=phi,
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delta_global=delta),
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schedule=schedule)
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To target quantum kernel code for execution on Pasqal QPU or simulators,
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pass the flag ``--target pasqal`` to the ``nvq++`` compiler.
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The number of shots for a kernel execution can be set through the ``shots_count``
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argument to ``evolve`` or ``evolve_async``. By default, the ``shots_count`` is
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set to 100.
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.. code:: bash
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nvq++ --target pasqal src.cpp
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You can also pass the flag ``--pasqal-machine`` to select the corresponding Pasqal QPU or emulator to execute on.
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See the `Pasqal cloud portal <https://portal.pasqal.cloud/>`__ for an up to date list.
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The default value is ``EMU_MPS`` which is an open-source tensor network emulator based on the
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Matrix Product State formalism running in Pasqal's cloud platform. You can see the
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documentation for the publicly accessible emulator `here <https://pasqal-io.github.io/emulators/latest/emu_mps/>`__.
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.. code:: bash
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nvq++ --target pasqal --pasqal-machine EMU_FREE src.cpp
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To target the QPU use the FRESNEL machine name. Note that there are restrictions
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regarding the values of the pulses as well as the register layout. We invite you to
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consult our `documentation <https://docs.pasqal.com/cloud/fresnel-job>`__. Note that
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the CUDA-Q integration currently only works with `arbitrary layouts <https://docs.pasqal.com/cloud/fresnel-job/#arbitrary-layouts>`__
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which are implemented with automatic calibration for less than 30 qubits. For jobs
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larger than 30 qubits please use the `atom_sites` to define the layout, and use the
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`atom_filling` to select sites as filled or not filled in order to define the register.
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Due to the nature of the underlying hardware, this target only supports the
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``evolve`` and ``evolve_async`` APIs.
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The `hamiltonian` must be of the type `rydberg_hamiltonian`. Only
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other parameters supported are `schedule` (mandatory) and `shots_count` (optional).
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For example,
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.. code:: python
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.. code:: cpp
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cudaq.evolve(RydbergHamiltonian(...), schedule=s, shots_count=1000)
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auto evolution_result = cudaq::evolve(
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cudaq::rydberg_hamiltonian(register_sites, omega, phi, delta),
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schedule);
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The number of shots for a kernel execution can be set through the ``shots_count``
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argument to ``evolve`` or ``evolve_async``. By default, the ``shots_count`` is
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set to 100.
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.. code:: cpp
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auto evolution_result = cudaq::evolve(cudaq::rydberg_hamiltonian(...), schedule, 1000);
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To see a complete example for using Pasqal's backend, take a look at our :doc:`C++ examples <../../examples/hardware_providers>`.
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To see a complete example for using Pasqal's backend, take a look at our :doc:`Python examples <../../examples/hardware_providers>`.
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.. note::
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export AWS_SECRET_ACCESS_KEY="<access_key>"
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export AWS_SESSION_TOKEN="<token>"
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Submission from Python
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About Aquila
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`````````````````````````
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The target to which quantum kernels are submitted
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can be controlled with the ``cudaq::set_target()`` function.
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.. code:: python
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cudaq.set_target('quera')
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By default, analog Hamiltonian will be submitted to the Aquila system.
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Aquila is a "field programmable qubit array" operated as an analog
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Hamiltonian simulator on a user-configurable architecture, executing
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programmable coherent quantum dynamics on up to 256 neutral-atom qubits.
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Refer to QuEra's `whitepaper <https://cdn.prod.website-files.com/643b94c382e84463a9e52264/648f5bf4d19795aaf36204f7_Whitepaper%20June%2023.pdf>`__ for details.
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Due to the nature of the underlying hardware, this target only supports the
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``evolve`` and ``evolve_async`` APIs.
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The `hamiltonian` must be an `Operator` of the type `RydbergHamiltonian`. Only
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other parameters supported are `schedule` (mandatory) and `shots_count` (optional).
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Submitting
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`````````````````````````
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.. tab:: Python
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The target to which quantum kernels are submitted
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can be controlled with the ``cudaq::set_target()`` function.
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.. code:: python
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For example,
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cudaq.set_target('quera')
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.. code:: python
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Due to the nature of the underlying hardware, this target only supports the
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``evolve`` and ``evolve_async`` APIs.
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The `hamiltonian` must be an `Operator` of the type `RydbergHamiltonian`. Only
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other parameters supported are `schedule` (mandatory) and `shots_count` (optional).
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For example,
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.. code:: python
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evolution_result = evolve(RydbergHamiltonian(atom_sites=register,
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amplitude=omega,
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phase=phi,
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delta_global=delta),
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schedule=schedule)
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The number of shots for a kernel execution can be set through the ``shots_count``
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argument to ``evolve`` or ``evolve_async``. By default, the ``shots_count`` is
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set to 100.
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.. code:: python
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cudaq.evolve(RydbergHamiltonian(...), schedule=s, shots_count=1000)
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To see a complete example for using QuEra's backend, take a look at our :doc:`Python examples <../../examples/hardware_providers>`.
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.. tab:: C++
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To target quantum kernel code for execution on QuEra's Aquila,
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pass the flag ``--target quera`` to the ``nvq++`` compiler.
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.. code:: bash
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nvq++ --target quera src.cpp
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Due to the nature of the underlying hardware, this target only supports the
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``evolve`` and ``evolve_async`` APIs.
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The `hamiltonian` must be of the type `rydberg_hamiltonian`. Only
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other parameters supported are `schedule` (mandatory) and `shots_count` (optional).
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For example,
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.. code:: cpp
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evolution_result = evolve(RydbergHamiltonian(atom_sites=register,
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amplitude=omega,
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phase=phi,
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delta_global=delta),
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schedule=schedule)
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auto evolution_result = cudaq::evolve(
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cudaq::rydberg_hamiltonian(register_sites, omega, phi, delta),
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schedule);
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The number of shots for a kernel execution can be set through the ``shots_count``
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argument to ``evolve`` or ``evolve_async``. By default, the ``shots_count`` is
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set to 100.
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The number of shots for a kernel execution can be set through the ``shots_count``
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argument to ``evolve`` or ``evolve_async``. By default, the ``shots_count`` is
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set to 100.
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.. code:: python
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.. code:: cpp
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cudaq.evolve(RydbergHamiltonian(...), schedule=s, shots_count=1000)
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auto evolution_result = cudaq::evolve(cudaq::rydberg_hamiltonian(...), schedule, 1000);
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To see a complete example for using QuEra's backend, take a look at our :doc:`Python examples <../../examples/hardware_providers>`.
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To see a complete example for using QuEra's backend, take a look at our :doc:`C++ examples <../../examples/hardware_providers>`.
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.. note::
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‎docs/sphinx/using/examples/hardware_providers.rst‎

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@@ -125,6 +125,11 @@ The following code illustrates how to run kernels on Pasqal's backends.
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.. literalinclude:: ../../targets/python/pasqal.py
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:language: python
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.. tab:: C++
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.. literalinclude:: ../../targets/cpp/pasqal.cpp
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:language: cpp
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Quantinuum
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==================================
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.. literalinclude:: ../../targets/python/quera_basic.py
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:language: python
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.. tab:: C++
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.. literalinclude:: ../../targets/cpp/quera_basic.cpp
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:language: cpp
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