Bugfix Cirq Datasets and LGST Bug #420
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added 2 commits
April 15, 2024 17:50
Add the (now default) option to convert a from the standard format for outcome labels in cirq (integers) to the standard representation used in pyGSTi (bit strings).
Bugfix for LGST to work with sparse data set formats where the count dicts only contain outcomes with non-zero counts.
sserita
approved these changes
Apr 16, 2024
| # when using a sparse data set format it might not be the case | ||
| # that all effect labels are present (only ones with non-zero counts are) | ||
| # so return 0 for the fraction in that case. | ||
| EVec[0, i] = dsRow_fractions.get((effectLabel,), 0) |
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Perfect, exactly the bugfix I was thinking of!
| convert_int_to_binary : bool, optional (defaut True) | ||
| By default the keys in the cirq Results object are the integers representing | ||
| the bitstrings of the measurements on a set of qubits, in big-endian convention. | ||
| If True this uses the cirq function `cirq.big_endian_int_to_bits` to convert back |
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I was wondering if we were going to get bit by endian-ness... Nice job covering that edge case!
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This PR covers two bugfixes. The first is in the method for adding cirq trials to pygsti datasets which did not behave as expected for 2+ qubits. The default behavior of the histogram method of the cirq
Resultobject, which is used for gathering aggregated counts for each measurement results is to index these results using integers corresponding to the binary string for an outcome. In pygsti we more commonly use the binary strings themselves as the key. To address this we have added new options toadd_cirq_trial_resultwhich controls conversion back to a bit string before adding it to the count dictionary.The second bugfix was to the LGST routine in order to patch in support for datasets with sparse formats wherein we only include outcomes with non-zero counts in the count dict for a circuit. Previously the implementation assumed that the data set was in a dense format with zero entries listed.