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

The worker uses the default mechanism provided by the qnexus Python package.

uv run python -c "from qnexus.client.auth import login; login()"

will put the a token in the appropriate filesystem location for subsequent operations to use.

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.

• compile_using_info compiles a circuit using an existing backend info object.

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

• 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)