FFSimulator

The FFSimulator is a simulator dedicated to simulate feed-forward experiments.

Like the Simulator, it needs a strong simulation backend to be able to perform simulations. However, the FFSimulator is also able to compute circuits having FFConfigurator or FFCircuitProvider but is unable to compute probability amplitudes.

Thus, only the probs_svd and probs computation methods are available.

>>> import perceval as pcvl
>>> sim = pcvl.FFSimulator(pcvl.SLOSBackend())
>>> ff_not = pcvl.FFCircuitProvider(2, 0, pcvl.Circuit(2)).add_configuration([0, 1], pcvl.PERM([1, 0]))
>>> sim.set_circuit([((0, 1), ff_not)])  # Since non-unitary components can't be added to Circuit, we directly provide a list; the number of modes is implicit
>>> sim.probs(pcvl.BasicState([0, 1, 1, 0]))
{
  |0,1,0,1>: 1.0
}
class perceval.simulators.feed_forward_simulator.FFSimulator(backend)
compute_physical_logical_perf(value)

Tells the simulator to compute or not the physical and logical performances when possible

Parameters:

value (bool) – True to compute the physical and logical performances, False otherwise.

format_results(results, physical_perf, logical_perf)

Format the simulation results by computing the global performance, and returning the physical and logical performances only if needed.

Parameters:

  • results – the simulation results

  • physical_perf – the physical performance

  • logical_perf – the logical performance

keep_heralds(value)

Tells the simulator to keep or discard ancillary modes in output states

Parameters:

value (bool) – True to keep ancillaries/heralded modes, False to discard them (default is keep).

property min_detected_photons_filter: int

The simulated minimum number of photons that a state needs to have to be counted as valid. Includes the expected photons from the heralds.

probs(input_state)

Compute the probability distribution from a BasicState input

Parameters:

input_state (BasicState) – A basic state describing the input to simulate

Return type:

BSDistribution

Returns:

A BSDistribution

probs_svd(input_dist, detectors=None, progress_callback=None)

Compute the probability distribution from a SVDistribution input and as well as performance scores

Parameters:

  • input_dist (SVDistribution) – A state vector distribution describing the input to simulate

  • detectors (Optional[list[IDetector]]) – An optional list of detectors

  • progress_callback (Optional[callable]) – A function with the signature func(progress: float, message: str)

Returns:

A dictionary of the form { “results”: BSDistribution, “global_perf”: float }

  • results is the post-selected output state distribution

  • global_perf is the probability that a state is post-selected

set_min_detected_photons_filter(value)

Set a minimum number of detected photons in the output distribution, counting only the non-heralded modes.

Parameters:

value (int) – The minimum photon count

set_selection(min_detected_photons_filter=None, postselect=None, heralds=None)

Set the min_detected_photons_filter, postselect, and heralds, if defined.

Parameters:

  • min_detected_photons_filter (Optional[int]) – The minimum photon count.

  • postselect (Optional[PostSelect]) – The postselect to apply at the end of the computation.

  • heralds (Optional[dict[int, int]]) – The heralds to apply at the end of the computation. Only the output heralds are considered here. dictionary of the form {mode: expected}