pygsti.tools.errgenproptools.magnus_numerical

pygsti.tools.errgenproptools.magnus_numerical#

magnus_numerical(propagated_errorgen_layers, error_propagator, magnus_order=1)#

Compute effective error generator layer produced by applying the magnus expansions to the list of input error generator matrices. Note this is primarily intended as part of testing and validation infrastructure.

Parameters:

  • propagated_errorgen_layers (list of dictionaries) – List of the error generator layers (in circuit ordering) in the form of dictionaries whose keys are elementary error generator labels and whose values are their corresponding rates. These dictionaries are in the format produced by the ErrorGeneratorPropagator class’s propagate_errorgens method.

  • error_propagator (ErrorGeneratorPropagator) – An ErrorGeneratorPropagator instance to use as part of the Magnus calculation.

  • magnus_order (int, optional (default 1)) – Order of the Magnus expansion to apply (up to 3 is supported currently).

Returns:

A dense numpy array corresponding to the result of Magnus expansion.

Return type:

numpy.ndarray