Quantinuum Backend Worker

A Tierkreis worker that provides convenient features to compile and run circuits on Quantinuum backends using pytket.

Installation

pip install tkr-quantinuum-worker

will install an executable Python script tkr_quantinuum_worker into your virtual environment.

Authentication

Important

Accessing backends through require authentication. The worker uses the default mechanisms provided by the pytket-quantinuum Python package. Run the following code before using the Quantinuum worker

from pytket.extensions.quantinuum.backends.api_wrappers import QuantinuumAPI
from pytket.extensions.quantinuum.backends.credential_storage import (
    QuantinuumConfigCredentialStorage,
)
from pytket.extensions.quantinuum.backends.quantinuum import QuantinuumBackend

backend = QuantinuumBackend(
    device_name=<device_name>, #e.g. H2-1E
    api_handler=QuantinuumAPI(token_store=QuantinuumConfigCredentialStorage()),
)
backend.login()

Tasks that require authentication are marked as such in the task list below.

Elementary tasks

The Quantinuum worker exposes the following elementary tasks to the user:

• get_backend_info retrieves the backend info given a configuration dict. Requires authentication.

• backend_pass_from_info constructs a compilation pass using a backend info object.

• backend_default_compilation_pass fetches the default pass given the device name. Requires authentication.

• compile fetches and applies the default compilation pass. Requires authentication.

• compile_circuit_quantinuum and compile_circuits_quantinuum applies a predefined compilation pass to a (list of) circuits.

• run_circuit Runs the circuit on the backend. Requires authentication.

Example

class QuantinuumInput(NamedTuple):
    circuit: TKR[OpaqueType["pytket._tket.circuit.Circuit"]]  # noqa: F821
    n_shots: TKR[int]
    backend: TKR[str]


def compile_run_single():
    g = GraphBuilder(
        QuantinuumInput, TKR[OpaqueType["pytket.backends.backendresult.BackendResult"]]
    )

    compiled_circuit = g.task(
        compile(
            circuit=g.inputs.circuit,
            device_name=g.inputs.backend,
            optimisation_level=g.const(2),
        )
    )
    res = g.task(run_circuit(compiled_circuit, g.inputs.n_shots, g.inputs.backend))
    g.outputs(res)
    return g

circuit = ...your circuit here...

storage = InMemoryStorage(UUID(int=109))
executor = InMemoryExecutor(
    Path(__file__).parent.parent / "tierkreis_workers", storage
)
n_shots = 30
run_graph(
    storage,
    executor,
    g,
    {
        "circuit": circuit,
        "n_shots": n_shots,
        "backend": "<ibmq_backend>", # e.g. ibm_pittsburgh
    },
)
res = read_outputs(g, storage)
print(res)