iqm.benchmarks.randomized_benchmarking.mirror_rb.mirror_rb.generate_pauli_dressed_mrb_circuits

iqm.benchmarks.randomized_benchmarking.mirror_rb.mirror_rb.generate_pauli_dressed_mrb_circuits#

iqm.benchmarks.randomized_benchmarking.mirror_rb.mirror_rb.generate_pauli_dressed_mrb_circuits(qubits: List[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, qiskit_optim_level: int = 1, routing_method: str = 'basic') → Dict[str, List[IQMCircuit]]#
Samples a mirror circuit and generates samples of “Pauli-dressed” circuits,

where for each circuit, random Pauli layers are interleaved between each layer of the circuit

Parameters:

  • qubits (List[int]) – the qubits of the backend

  • pauli_samples_per_circ (int) – the number of pauli samples per circuit

  • depth (int) – the depth (number of canonical layers) of the circuit

  • backend_arg (IQMBackendBase | str) – the backend

  • density_2q_gates (float) – the expected density of 2Q gates

  • two_qubit_gate_ensemble (Optional[Dict[str, float]]) –

  • qiskit_optim_level (int) –

  • routing_method (str) –

Return type:

Dict[str, List[IQMCircuit]]

Returns: