iqm.benchmarks.randomized_benchmarking.randomized_benchmarking_common.edge_grab

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iqm.benchmarks.randomized_benchmarking.randomized_benchmarking_common.edge_grab#

iqm.benchmarks.randomized_benchmarking.randomized_benchmarking_common.edge_grab(qubit_set: List[int] | Sequence[int], n_layers: int, backend_arg: IQMBackendBase | str, density_2q_gates: float = 0.25, two_qubit_gate_ensemble: Dict[str, float] | None = None, clifford_sqg_probability=1.0, sqg_gate_ensemble: Dict[str, float] | None = None) → List[IQMCircuit]#

Generate a list of random layers containing single-qubit Cliffords and two-qubit gates, sampled according to the edge-grab algorithm (see arXiv:2204.07568 [quant-ph]).

Parameters:

  • qubit_set (List[int]) – The set of qubits of the backend.

  • n_layers (int) – The number of layers.

  • backend_arg (IQMBackendBase | str) – IQM backend.

  • density_2q_gates (float) – The expected density of 2Q gates in a circuit formed by subsequent application of layers. * Default is 0.25

  • two_qubit_gate_ensemble (Optional[Dict[str, float]]) – A dictionary with keys being str specifying 2Q gates, and values being corresponding probabilities. * Default is None.

  • clifford_sqg_probability (float) – Probability with which to uniformly sample Clifford 1Q gates. * Default is 1.0.

  • sqg_gate_ensemble (Optional[Dict[str, float]]) – A dictionary with keys being str specifying 1Q gates, and values being corresponding probabilities. * Default is None.

Raises:

ValueError – if the probabilities in the gate ensembles do not add up to unity.

Returns:

the list of gate layers, in the form of quantum circuits.

Return type:

List[QuantumCircuit]

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