deltakit.decode.noise_sources.EdgeProbabilityMatchingNoise

class deltakit.decode.noise_sources.EdgeProbabilityMatchingNoise(edge_filter: Callable[[HyperMultiGraph], Sequence[EdgeT]] | None = None)

Bases: IndependentMatchingNoise

A noise model that defines noise over a decoding graph based on the edge probabilities. A random variable is generated for each edge and an error occurs on the edge if the edge’s p_err is greater than this random variable. Therefore edges with higher p_err have more chance of being selected.

Methods

EdgeProbabilityMatchingNoise.as_exhaustive_sequential_model	Return the equivalent exhaustive model for this noise model.
EdgeProbabilityMatchingNoise.build_batch_error_generator	Given some representation of a code, return a generator of batches of errors for that code.
EdgeProbabilityMatchingNoise.build_split_batch_error_generators	Given some representation of a code, return num_splits number of batch generators of errors for that code and the respective sizes for those generators.
EdgeProbabilityMatchingNoise.empty_filter	Filter that does not change the input.
EdgeProbabilityMatchingNoise.error_generator	Given some representation of a code, return a generator of errors for that code.
EdgeProbabilityMatchingNoise.field_values	Return the values of data that characterises this noise model.
EdgeProbabilityMatchingNoise.get_rng	Return a numpy random number generator, using the member data seed.
EdgeProbabilityMatchingNoise.importance_sampling_decomposition	Decompose this noise model to be used in importance sampling.
EdgeProbabilityMatchingNoise.split_error_generator	Given some representation of a code, return num_splits number of generators of errors for that code and the respective sizes for those generators.