CUDA-Q Hardware Backends ********************************* CUDA-Q supports submission to a set of hardware providers. To submit to a hardware backend, you need an account with the respective provider. IonQ ================================== .. _ionq-backend: Setting Credentials ````````````````````````` Programmers of CUDA-Q may access the `IonQ Quantum Cloud `__ from either C++ or Python. Generate an API key from your `IonQ account `__ and export it as an environment variable: .. code:: bash export IONQ_API_KEY="ionq_generated_api_key" Submission from C++ ````````````````````````` To target quantum kernel code for execution in the IonQ Cloud, pass the flag ``--target ionq`` to the ``nvq++`` compiler. .. code:: bash nvq++ --target ionq src.cpp This will take the API key and handle all authentication with, and submission to, the IonQ QPU(s). By default, quantum kernel code will be submitted to the IonQ simulator. .. note:: A "target" in :code:`cudaq` refers to a quantum compute provider, such as :code:`ionq`. However, IonQ's documentation uses the term "target" to refer to specific QPU's themselves. To execute your kernels on a QPU, pass the ``--ionq-machine`` flag to the ``nvq++`` compiler to specify which machine to submit quantum kernels to: .. code:: bash nvq++ --target ionq --ionq-machine qpu.aria-1 src.cpp ... where ``qpu.aria-1`` is an example of a physical QPU. A list of available QPUs can be found `in the API documentation `__. To see which backends are available with your subscription login to your `IonQ account `__. To emulate the IonQ machine locally, without submitting through the cloud, you can also pass the ``--emulate`` flag to ``nvq++``. This will emit any target specific compiler diagnostics, before running a noise free emulation. .. code:: bash nvq++ --emulate --target ionq src.cpp To see a complete example for using IonQ's backends, take a look at our :doc:`C++ examples <../examples/examples>`. Submission from Python ````````````````````````` The target to which quantum kernels are submitted can be controlled with the ``cudaq::set_target()`` function. .. code:: python cudaq.set_target('ionq') By default, quantum kernel code will be submitted to the IonQ simulator. .. note:: A "target" in :code:`cudaq` refers to a quantum compute provider, such as :code:`ionq`. However, IonQ's documentation uses the term "target" to refer to specific QPU's themselves. To specify which IonQ QPU to use, set the :code:`qpu` parameter. .. code:: python cudaq.set_target("ionq", qpu="qpu.aria-1") where ``qpu.aria-1`` is an example of a physical QPU. A list of available QPUs can be found `in the API documentation `__. To see which backends are available with your subscription login to your `IonQ account `__. To emulate the IonQ machine locally, without submitting through the cloud, you can also set the ``emulate`` flag to ``True``. This will emit any target specific compiler diagnostics, before running a noise free emulation. .. code:: python cudaq.set_target('ionq', emulate=True) The number of shots for a kernel execution can be set through the ``shots_count`` argument to ``cudaq.sample`` or ``cudaq.observe``. By default, the ``shots_count`` is set to 1000. .. code:: python cudaq.sample(kernel, shots_count=10000) To see a complete example for using IonQ's backends, take a look at our :doc:`Python examples <../examples/examples>`. Anyon Technologies/Anyon Computing ================================== .. _anyon-backend: Setting Credentials ``````````````````` Programmers of CUDA-Q may access the Anyon API from either C++ or Python. Anyon requires a credential configuration file with username and password. The configuration file can be generated as follows, replacing the ```` and ```` in the first line with your Anyon Technologies account details. The credential in the file will be used by CUDA-Q to login to Anyon quantum services and will be updated by CUDA-Q with an obtained API token and refresh token. Note, the credential line will be deleted in the updated configuration file. .. code:: bash echo 'credentials: {"username":"","password":""}' > $HOME/.anyon_config Users can also login and get the keys manually using the following commands: .. code:: bash # You may need to run: `apt-get update && apt-get install curl jq` curl -X POST --user ":" -H "Content-Type: application/json" \ https://api.anyon.cloud:5000/login > credentials.json id_token=`cat credentials.json | jq -r '."id_token"'` refresh_token=`cat credentials.json | jq -r '."refresh_token"'` echo "key: $id_token" > ~/.anyon_config echo "refresh: $refresh_token" >> ~/.anyon_config The path to the configuration can be specified as an environment variable: .. code:: bash export CUDAQ_ANYON_CREDENTIALS=$HOME/.anyon_config Submission from C++ ````````````````````````` To target quantum kernel code for execution in the Anyon Technologies backends, pass the flag ``--target anyon`` to the ``nvq++`` compiler. CUDA-Q will authenticate via the Anyon Technologies REST API using the credential in your configuration file. .. code:: bash nvq++ --target anyon -- src.cpp ... To execute your kernels using Anyon Technologies backends, pass the ``--anyon-machine`` flag to the ``nvq++`` compiler as the ``--`` to specify which machine to submit quantum kernels to: .. code:: bash nvq++ --target anyon --anyon-machine telegraph-8q src.cpp ... where ``telegraph-8q`` is an example of a physical QPU (Architecture: Telegraph, Qubit Count: 8). Currently, ``telegraph-8q`` and ``berkeley-25q`` are available for access over CUDA-Q. To emulate the Anyon Technologies machine locally, without submitting through the cloud, you can also pass the ``--emulate`` flag as the ``--`` to ``nvq++``. This will emit any target specific compiler warnings and diagnostics, before running a noise free emulation. .. code:: bash nvq++ --target anyon --emulate src.cpp To see a complete example for using Anyon's backends, take a look at our :doc:`C++ examples <../examples/examples>`. Submission from Python ````````````````````````` The target to which quantum kernels are submitted can be controlled with the ``cudaq.set_target()`` function. To execute your kernels using Anyon Technologies backends, specify which machine to submit quantum kernels to by setting the :code:`machine` parameter of the target. If :code:`machine` is not specified, the default machine will be ``telegraph-8q``. .. code:: python cudaq.set_target('anyon', machine='telegraph-8q') As shown above, ``telegraph-8q`` is an example of a physical QPU. To emulate the Anyon Technologies machine locally, without submitting through the cloud, you can also set the ``emulate`` flag to ``True``. This will emit any target specific compiler warnings and diagnostics, before running a noise free emulation. .. code:: python cudaq.set_target('anyon', emulate=True) The number of shots for a kernel execution can be set through the ``shots_count`` argument to ``cudaq.sample`` or ``cudaq.observe``. By default, the ``shots_count`` is set to 1000. .. code:: python cudaq.sample(kernel, shots_count=10000) To see a complete example for using Anyon's backends, take a look at our :doc:`Python examples <../examples/examples>`. IQM ================================== .. _iqm-backend: Support for submissions to IQM is currently under development. In particular, two-qubit gates can only be performed on adjacent qubits. For more information, we refer to the respective hardware documentation. Support for automatically injecting the necessary operations during compilation to execute arbitrary multi-qubit gates will be added in future versions. Setting Credentials ````````````````````````` Programmers of CUDA-Q may access the IQM Server from either C++ or Python. Following the `quick start guide `__, install `iqm-cortex-cli` and login to initialize the tokens file. The path to the tokens file can either be passed explicitly via an environment variable or it will be loaded automatically if located in the default location :code:`~/.cache/iqm-cortex-cli/tokens.json`. .. code:: bash export IQM_TOKENS_FILE="path/to/tokens.json" Submission from C++ ````````````````````````` To target quantum kernel code for execution on an IQM Server, pass the ``--target iqm`` flag to the ``nvq++`` compiler, along with a specified ``--iqm-machine``. .. note:: The ``--iqm-machine`` is a mandatory argument. This provided architecture must match the device architecture that the program has been compiled against. The hardware architecture for a specific IQM Server may be checked via `https:///cocos/quantum-architecture`. .. code:: bash nvq++ --target iqm --iqm-machine Adonis src.cpp Once the binary for a specific IQM QPU architecture is compiled, it can be executed against any IQM Server with the same QPU architecture: .. code:: bash nvq++ --target iqm --iqm-machine Adonis src.cpp -o program IQM_SERVER_URL="https://demo.qc.iqm.fi/cocos" ./program # Executing the same program against an IQM Server with a different underlying QPU # architecture will result in an error. IQM_SERVER_URL="https:///cocos" ./program To emulate the IQM machine locally, without submitting to the IQM Server, you can also pass the ``--emulate`` flag to ``nvq++``. This will emit any target specific compiler diagnostics, before running a noise free emulation. .. code:: bash nvq++ --emulate --target iqm --iqm-machine Adonis src.cpp To see a complete example for using IQM server backends, take a look at our :doc:`C++ examples <../examples/examples>`. Submission from Python ````````````````````````` The target to which quantum kernels are submitted can be controlled with the ``cudaq::set_target()`` function. .. code:: python cudaq.set_target("iqm", url="https:///cocos", **{"qpu-architecture": "Adonis"}) To emulate the IQM Server locally, without submitting to the IQM Server, you can also set the ``emulate`` flag to ``True``. This will emit any target specific compiler diagnostics, before running a noise free emulation. .. code:: python cudaq.set_target('iqm', emulate=True) The number of shots for a kernel execution can be set through the ``shots_count`` argument to ``cudaq.sample`` or ``cudaq.observe``. By default, the ``shots_count`` is set to 1000. .. code:: python cudaq.sample(kernel, shots_count=10000) To see a complete example for using IQM server backends, take a look at our :doc:`Python examples<../examples/examples>`. OQC ================================== .. _oqc-backend: `Oxford Quantum Circuits `__ (OQC) is currently providing CUDA-Q integration for multiple Quantum Processing Unit types. The 8 qubit ring topology Lucy device and the 32 qubit Kagome lattice topology Toshiko device are both supported via machine options described below. Setting Credentials ````````````````````````` In order to use the OQC devices you will need to register. Registration is achieved by contacting oqc_qcaas_support@oxfordquantumcircuits.com Once registered you will be able to authenticate with your ``email`` and ``password`` There are three environment variables that the OQC target will look for during configuration: 1. ``OQC_URL`` 2. ``OQC_EMAIL`` 3. ``OQC_PASSWORD`` - is mandatory Submission from C++ ````````````````````````` To target quantum kernel code for execution on the OQC platform, provide the flag ``--target oqc`` to the ``nvq++`` compiler. Users may provide their :code:`email` and :code:`url` as extra arguments .. code:: bash nvq++ --target oqc --oqc-email --oqc-url src.cpp -o executable Where both environment variables and extra arguments are supplied, precedent is given to the extra arguments. To run the output, provide the runtime loaded variables and invoke the pre-built executable .. code:: bash OQC_PASSWORD= ./executable To emulate the OQC device locally, without submitting through the OQC QCaaS services, you can pass the ``--emulate`` flag to ``nvq++``. This will emit any target specific compiler warnings and diagnostics, before running a noise free emulation. .. code:: bash nvq++ --emulate --target oqc src.cpp -o executable .. note:: The oqc target supports a ``--oqc-machine`` option. The default is the 8 qubit Lucy device. You can set this to be either ``toshiko`` or ``lucy`` via this flag. .. note:: The OQC quantum assembly toolchain (qat) which is used to compile and execute instructions can be found on github as `oqc-community/qat `__ Submission from Python ````````````````````````` To set which OQC URL, set the :code:`url` parameter. To set which OQC email, set the :code:`email` parameter. To set which OQC machine, set the :code:`machine` parameter. .. code:: python import os import cudaq # ... os.environ['OQC_PASSWORD'] = password cudaq.set_target("oqc", url=url, machine="lucy") You can then execute a kernel against the platform using the OQC Lucy device .. code:: python kernel = cudaq.make_kernel() qvec = kernel.qalloc(2) kernel.h(qvec[0]) kernel.x(qvec[1]) kernel.cx(qvec[0], qvec[1]) kernel.mz(qvec) str(cudaq.sample(kernel=kernel, shots_count=1000)) ORCA Computing ================================== .. _orca-backend: ORCA Computing's PT Series implement the boson sampling model of quantum computation, in which multiple single photons are interfered with each other within a network of beam splitters, and photon detectors measure where the photons leave this network. This process is implemented within a time-bin interferometer (TBI) architecture where photons are created in different time-bins and interfered within a network of delay lines. This can be represented by a circuit diagram, like the one below, where this illustration example corresponds to 4 photons in 8 modes sent into alternating time-bins in a circuit composed of two delay lines in series. .. image:: ../examples/images/orca_tbi.png :width: 400px :align: center Setting Credentials ``````````````````` Programmers of CUDA-Q may access the ORCA API from either C++ or Python. There is an environment variable ``ORCA_ACCESS_URL`` that can be set so that the ORCA target can look for it during configuration. .. code:: bash export ORCA_ACCESS_URL="https://" Sometimes the requests to the PT-1 require an authentication token. This token can be set as an environment variable named ``ORCA_AUTH_TOKEN``. For example, if the token is :code:`AbCdEf123456`, you can set the environment variable as follows: .. code:: bash export ORCA_AUTH_TOKEN="AbCdEf123456" Submission from C++ ````````````````````````` To execute a boson sampling experiment on the ORCA platform, provide the flag ``--target orca`` to the ``nvq++`` compiler. You should then pass the ``--orca-url`` flag set with the previously set environment variable ``$ORCA_ACCESS_URL`` or an :code:`url`. .. code:: bash nvq++ --target orca --orca-url $ORCA_ACCESS_URL src.cpp -o executable or .. code:: bash nvq++ --target orca --orca-url src.cpp -o executable To run the output, invoke the executable .. code:: bash ./executable To see a complete example for using ORCA server backends, take a look at our :doc:`C++ examples <../examples/hardware_providers>`. Submission from Python ````````````````````````` To set which ORCA URL to be used, set the :code:`url` parameter. .. code:: python import os import cudaq # ... orca_url = os.getenv("ORCA_ACCESS_URL", "http://localhost/sample") cudaq.set_target("orca", url=orca_url) You can then execute a time-bin boson sampling experiment against the platform using an ORCA device. .. code:: python bs_angles = [np.pi / 3, np.pi / 6] input_state = [1, 1, 1] loop_lengths = [1] counts = cudaq.orca.sample(input_state, loop_lengths, bs_angles) To see a complete example for using ORCA's backends, take a look at our :doc:`Python examples <../examples/hardware_providers>`. Quantinuum ================================== .. _quantinuum-backend: Setting Credentials ``````````````````` Programmers of CUDA-Q may access the Quantinuum API from either C++ or Python. Quantinuum requires a credential configuration file. The configuration file can be generated as follows, replacing the ``email`` and ``credentials`` in the first line with your Quantinuum account details. .. code:: bash # You may need to run: `apt-get update && apt-get install curl jq` curl -X POST -H "Content Type: application/json" \ -d '{ "email":"@email.com","password":"" }' \ https://qapi.quantinuum.com/v1/login > $HOME/credentials.json id_token=`cat $HOME/credentials.json | jq -r '."id-token"'` refresh_token=`cat $HOME/credentials.json | jq -r '."refresh-token"'` echo "key: $id_token" >> $HOME/.quantinuum_config echo "refresh: $refresh_token" >> $HOME/.quantinuum_config The path to the configuration can be specified as an environment variable: .. code:: bash export CUDAQ_QUANTINUUM_CREDENTIALS=$HOME/.quantinuum_config Submission from C++ ````````````````````````` To target quantum kernel code for execution in the Quantinuum backends, pass the flag ``--target quantinuum`` to the ``nvq++`` compiler. CUDA-Q will authenticate via the Quantinuum REST API using the credential in your configuration file. By default, quantum kernel code will be submitted to the Quantinuum syntax checker. Submission to the syntax checker merely validates the program; the kernels are not executed. .. code:: bash nvq++ --target quantinuum src.cpp ... To execute your kernels, pass the ``--quantinuum-machine`` flag to the ``nvq++`` compiler to specify which machine to submit quantum kernels to: .. code:: bash nvq++ --target quantinuum --quantinuum-machine H1-2 src.cpp ... where ``H1-2`` is an example of a physical QPU. Hardware specific emulators may be accessed by appending an ``E`` to the end (e.g, ``H1-2E``). For access to the syntax checker for the provided machine, you may append an ``SC`` to the end (e.g, ``H1-1SC``). For a comprehensive list of available machines, login to your `Quantinuum user account `__ and navigate to the "Account" tab, where you should find a table titled "Machines". To emulate the Quantinuum machine locally, without submitting through the cloud, you can also pass the ``--emulate`` flag to ``nvq++``. This will emit any target specific compiler warnings and diagnostics, before running a noise free emulation. .. code:: bash nvq++ --emulate --target quantinuum src.cpp To see a complete example for using Quantinuum's backends, take a look at our :doc:`C++ examples <../examples/examples>`. Submission from Python ````````````````````````` The target to which quantum kernels are submitted can be controlled with the ``cudaq::set_target()`` function. .. code:: python cudaq.set_target('quantinuum') By default, quantum kernel code will be submitted to the Quantinuum syntax checker. Submission to the syntax checker merely validates the program; the kernels are not executed. To execute your kernels, specify which machine to submit quantum kernels to by setting the :code:`machine` parameter of the target. .. code:: python cudaq.set_target('quantinuum', machine='H1-2') where ``H1-2`` is an example of a physical QPU. Hardware specific emulators may be accessed by appending an ``E`` to the end (e.g, ``H1-2E``). For access to the syntax checker for the provided machine, you may append an ``SC`` to the end (e.g, ``H1-1SC``). For a comprehensive list of available machines, login to your `Quantinuum user account `__ and navigate to the "Account" tab, where you should find a table titled "Machines". To emulate the Quantinuum machine locally, without submitting through the cloud, you can also set the ``emulate`` flag to ``True``. This will emit any target specific compiler warnings and diagnostics, before running a noise free emulation. .. code:: python cudaq.set_target('quantinuum', emulate=True) The number of shots for a kernel execution can be set through the ``shots_count`` argument to ``cudaq.sample`` or ``cudaq.observe``. By default, the ``shots_count`` is set to 1000. .. code:: python cudaq.sample(kernel, shots_count=10000) To see a complete example for using Quantinuum's backends, take a look at our :doc:`Python examples <../examples/examples>`. QuEra Computing ================================== .. _quera-backend: Setting Credentials ``````````````````` Programmers of CUDA-Q may access Aquila, QuEra's first generation of quantum processing unit (QPU) via AWS Braket. Hence, users must set AWS credentials using any of the documented `methods `__. One of the simplest ways is to use `AWS CLI `__. .. code:: bash aws configure Alternatively, users can set the following environment variables. .. code:: bash export AWS_DEFAULT_REGION="us-east-1" export AWS_ACCESS_KEY_ID="" export AWS_SECRET_ACCESS_KEY="" export AWS_SESSION_TOKEN="" Submission from C++ ````````````````````````` Not yet supported. Submission from Python ````````````````````````` The target to which quantum kernels are submitted can be controlled with the ``cudaq::set_target()`` function. .. code:: python cudaq.set_target('quera') By default, analog Hamiltonian will be submitted to the Aquila system. Aquila is a "field programmable qubit array" operated as an analog Hamiltonian simulator on a user-configurable architecture, executing programmable coherent quantum dynamics on up to 256 neutral-atom qubits. Refer to QuEra's `whitepaper `__ for details. Due to the nature of the underlying hardware, this target only supports the ``evolve`` and ``evolve_async`` APIs. The `hamiltonian` must be an `Operator` of the type `RydbergHamiltonian`. Only other parameters supported are `schedule` (mandatory) and `shots_count` (optional). For example, .. code:: python evolution_result = evolve(RydbergHamiltonian(atom_sites=register, amplitude=omega, phase=phi, delta_global=delta), schedule=schedule) The number of shots for a kernel execution can be set through the ``shots_count`` argument to ``evolve`` or ``evolve_async``. By default, the ``shots_count`` is set to 100. .. code:: python cudaq.evolve(RydbergHamiltonian(...), schedule=s, shots_count=1000) To see a complete example for using QuEra's backend, take a look at our :doc:`Python examples <../examples/hardware_providers>`.