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GraphDecoder

GraphDecoder(code, S=None) GitHub(opens in a new tab)

Class to construct the graph corresponding to the possible syndromes of a quantum error correction code, and then run suitable decoders.

Parameters

  • code (RepitionCode) – The QEC Code object for which this decoder will be used.
  • S (networkx.Graph) – Graph describing connectivity between syndrome elements. Will be generated automatically if not supplied.

Additional information:

The decoder for the supplied code is initialized by running _make_syndrome_graph(). Since this process can take some time, it is also possible to load in a premade S. However, if this was created for a differently defined code, it won’t work properly.


Methods

get_logical_prob

GraphDecoder.get_logical_prob(results, algorithm='matching')

Parameters

  • results (dict) – A results dictionary, as produced by the
  • code. (process_results method of the) –
  • algorithm (str) – Choice of which decoder to use.

Returns

Dictionary of logical error probabilities for each of the encoded logical states whose results were given in the input.

Return type

dict

make_error_graph

GraphDecoder.make_error_graph(string, subgraphs=None)

Parameters

  • string (str) – A string describing the output from the code.
  • subgraphs (list) – Used when multiple, semi-independent graphs need
  • created. (need to) –

Returns

The subgraph(s) of S which corresponds to the non-trivial syndrome elements in the given string.

Return type

E

matching

GraphDecoder.matching(string)

Parameters

string (str) – A string describing the output from the code.

Returns

A string with corrected logical values,

computed using minimum weight perfect matching.

Return type

str

Additional information:

This function can be run directly, or used indirectly to calculate a logical error probability with get_logical_prob

weight_syndrome_graph

GraphDecoder.weight_syndrome_graph(results)

Generate weighted syndrome graph from result counts.

Parameters

  • results (dict) – A results dictionary, as produced by the
  • code. (process_results method of the) –

Additional information:

Uses results to estimate the probability of the errors that create the pairs of nodes in S. The edge weights are then replaced with the corresponding -log(p/(1-p).

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