get_ccz2t_costs_from_grid_search

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Grid search over parameters to minimize the space-time volume.

View aliases

Main aliases

`qualtran.surface_code.gidney_fowler_model.get_ccz2t_costs_from_grid_search`

qualtran.surface_code.get_ccz2t_costs_from_grid_search(
    *,
    n_logical_gates: 'GateCounts',
    n_algo_qubits: int,
    phys_err: float = 0.001,
    error_budget: float = 0.01,
    cycle_time_us: float = 1.0,
    factory_iter: Iterable[qualtran.surface_code.MagicStateFactory] = tuple(iter_ccz2t_factories()),
    data_block_iter: Iterable[qualtran.surface_code.DataBlock] = tuple(iter_simple_data_blocks()),
    cost_function: Callable[[qualtran.surface_code.PhysicalCostsSummary], float] = (lambda pc: pc.qubit_hours)
) -> Tuple[qualtran.surface_code.PhysicalCostsSummary, qualtran.surface_code.MagicStateFactory, qualtran.surface_code.SimpleDataBlock]

Args

n_logical_gates

Number of algorithm logical gates.

n_algo_qubits

Number of algorithm logical qubits.

phys_err

The physical error rate of the device. This sets the suppression factor for increasing code distance.

error_budget

The acceptable chance of an error occurring at any point. This includes data storage failures as well as top-level distillation failure.

cycle_time_us

The number of microseconds it takes to execute a surface code cycle.

factory_iter

iterable containing the instances of MagicStateFactory to search over.

data_block_iter

iterable containing the instances of SimpleDataBlock to search over.

cost_function

function of PhysicalCostsSummary to be minimized. Defaults to spacetime volume. Set cost_function = (lambda pc: pc.duration_hr) to mimimize wall time.

Returns

References