Pytket worker¶

A Tierkreis worker that interacts with the Quantinuums pytket toolkit.

The pytket worker largely wraps the functionality from tket.

Installation¶

pip install tkr-pytket-worker

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

Authentication¶

Certain backends, such as the Quantinnuum backend require authentication. The worker uses the default mechanisms 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.

To use IBMQ services, the credentials are expected to be stored in a file $HOME/.qiskit/qiskit-ibm.json for more see the Qiskit Documentation

Elementary tasks¶

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

add_measure_all adds final measurements to a circuit.
append_pauli_measurement_impl adds measurements according to a Pauli string to a circuit.
optimise_phase_gadgets applies the phase gadget optimization pass to a circuit.
apply_pass applies a user defined optimization pass.
compile generic compile function with a variety of options
compile_circuit_quantinuum and compile_circuits_quantinuum apply a predefined level 3 optimization for Quantinuum devices to a (list of) circuit.
compile_tket_circuit_ibm and compile_tket_circuits_ibm applies the pytket default pass for IBM devices to a (list of) circuit. Requires IBMQ authentication.
compile_tket_circuit_quantinuum and compile_tket_circuits_quantinuum applies the pytket default pass for Quantinuum devices to a (list of) circuit. Requires Qautninuum Nexus authentication.
to_qasm_str and from_gasm_str transforms a Circuit to/from QASM 2.
to_qir_bytes and from_qir_bytes transforms a Circuit to/from QIR. Requires optional dependencies uv sync --groups qir.
expectation estimates the expectation value from shot counts.
n_qubits returns the number of qubits in a const circuit.

Example¶

An example use is in examples/pytket_graph.py in the Tierkreis repo, which runs on a named IBM backend, e.g. "ibm_torino". For debugging purposes this also showcases how to use the InMemoryExecutor which only works in conjunction with the InMemoryStorage.

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


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

    compiled_circuit = g.task(
        compile_tket_circuit_ibm(
            circuit=g.inputs.circuit,
            backend_name=g.inputs.backend,
            optimization_level=g.const(2),
        )
    )
    res = g.task(submit_single(compiled_circuit, g.inputs.n_shots))
    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": ghz(),
        "n_shots": n_shots,
        "backend": "<ibm_backend>", # e.g. ibm_torino
    },
)
res = read_outputs(g, storage)
print(res)