gulps.analysis.calibration.calibrate

gulps.analysis.calibration.calibrate(base_gate, budget=1, strengths=GRID, local_layer_cost=0.0, workload=None, max_depth=MAX_DEPTH, *, pulse_overhead=0.0)[source]

Choose up to budget powers of base_gate from strengths.

At each step, the search adds the grid point that lowers the score most, then revisits each chosen strength once while holding the others fixed. It stops adding strengths when it reaches budget or exhausts the grid.

Parameters:

  • base_gate (Gate) – The Qiskit gate to power.

  • budget (int) – The maximum number of distinct powers.

  • strengths (Sequence[float]) – The powers to choose from, in (0, 1].

  • local_layer_cost (float) – The cost of one simultaneous local-gate layer. A sentence of n pulses has n + 1 such layers.

  • workload (QuantumCircuit | Sequence[Gate | Operator | ndarray | LocalEquivalenceClass] | None) – A circuit or a list of targets to score instead of the Haar average.

  • max_depth (int) – Maximum two-qubit sentence depth. Candidates that exceed it score infinity; an all-infinite search raises SearchDepthError.

  • pulse_overhead (float) – Fixed cost per entangling pulse, added to its strength. A pulse of strength k costs k + pulse_overhead.

Return type:

Calibration