iqm.benchmarks.randomized_benchmarking.mirror_rb.mirror_rb.generate_fixed_depth_mrb_circuits#
- iqm.benchmarks.randomized_benchmarking.mirror_rb.mirror_rb.generate_fixed_depth_mrb_circuits(qubits: List[int], circ_samples: int, pauli_samples_per_circ: int, depth: 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, qiskit_optim_level: int = 1, routing_method: str = 'basic', simulation_method: Literal['automatic', 'statevector', 'stabilizer', 'extended_stabilizer', 'matrix_product_state'] = 'automatic') Dict[int, Dict[str, List[IQMCircuit]]] #
Generates a dictionary MRB circuits at fixed depth, indexed by sample number
- Parameters:
qubits (List[int]) – A list of integers specifying physical qubit labels
circ_samples (int) – The number of sets of Pauli-dressed circuit samples
pauli_samples_per_circ (int) – the number of pauli samples per circuit
depth (int) – the depth (number of canonical layers) of the circuits
backend_arg (IQMBackendBase | str) – the backend
density_2q_gates (float) – the expected density of 2Q gates
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.
two_qubit_gate_ensemble –
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.
qiskit_optim_level (int) – Qiskit transpiler optimization level. * Default is 1.
routing_method (str) – Qiskit transpiler routing method. * Default is “basic”.
simulation_method (Literal["automatic", "statevector", "stabilizer", "extended_stabilizer", "matrix_product_state"]) – Qiskit’s Aer simulation method * Default is “automatic”.
- Returns:
A dictionary of lists of Pauli-dressed quantum circuits corresponding to the circuit sample index
- Return type: