PhotonRecycling

Photon recycling uses the measured events in which one or two photons were lost to estimate the ideal-photon-number output distribution. The method was introduced in Mills and Mezher [53].

Automatic use with a Computer

Add PhotonRecycling to the computer’s mitigation list:

>>> import perceval as pcvl
>>>
>>> computer.mitigations = [pcvl.PhotonRecycling()]

The mitigation automatically requests the lower-photon events required by the algorithm and returns the corrected distribution through the normal execution result.

Photon recycling is not part of any MitigationFactory preset. It can be enabled explicitly:

>>> factory = pcvl.MitigationFactory(pcvl.MitigationLevel.medium)
>>> factory.set_photon_recycling()
>>> computer.mitigations = factory.build()

Practical considerations

  • The experiment must be unitary and have a fixed input photon count of at least three.

  • The technique estimates a probability distribution, and does not need prior characterization of the computer.

class perceval.runtime.error_mitigation.photon_recycling.PhotonRecycling

Mitigate photon loss by applying photon recycling to computation results.

The automatic layer applies only to compatible unitary experiments with a photon count of at least 3.

extend_computation(computation, imperfections)
Parameters:

  • computation (Computation) – The computation asked by the upper layer

  • imperfections (Imperfections) – The Computer imperfections

Return type:

list[Computation]

Returns:

a list of all computations to execute to apply the mitigation

Applying photon recycling directly

The standalone photon_recycling() function can correct an existing BSCount or BSDistribution when its ideal photon count is known:

>>> mitigated_distribution = pcvl.photon_recycling(
...     noisy_distribution,
...     ideal_photon_count=4,
... )

The input must contain both three-photon and two-photon events for an ideal count of four. Passing a lossless distribution, an incompatible result type, or insufficient loss statistics raises an error.

perceval.runtime.error_mitigation.photon_recycling.photon_recycling(noisy_input, ideal_photon_count)

A classical technique to mitigate errors in the output distribution caused by photon loss in LO quantum circuits (ref: https://arxiv.org/abs/2405.02278)

The input must contain events with one and two fewer photons than the ideal photon count.

Parameters:

  • noisy_input (BSCount | BSDistribution) – Noisy output counts or probability distribution.

  • ideal_photon_count (int) – Expected photon count for a lossless system.

Return type:

BSDistribution

Returns:

Photon-loss-mitigated probability distribution.