BeliefMatching v0.1.0

BeliefMatching v0.1.0

An implementation of the belief-matching decoder, which is more accurate than the MWPM decoder (its accuracy approaches that of maximum likelihood decoding). Belief-matching is an efficient decoder (expected linear time) however this implementation is not optimised for speed and is slower than PyMatching v2.

Features

A beliefmatching.BeliefMatching class which can load from stim circuits and detector error models and decode shot data. Methods include:

• beliefmatching.BeliefMatching.from_stim_circuit which loads from a stim.Circuit
• beliefmatching.BeliefMatching.from_detector_error_model which loads from a stim.DetectorErrorModel
• beliefmatching.BeliefMatching.decode which decodes a single shot of detector measurements
• beliefmatching.BeliefMatching.decode_batch which decodes a batch of detector measurements

A beliefmatching.BeliefMatchingSinterDecoder class, which integrates with sinter and subclasses sinter.Decoder

A beliefmatching.detector_error_model_to_check_matrices method, which converts a stim.DetectorErrorModel into a representation as a collection of matrices (a DemMatrices dataclass).