Detector error model probabilities can be recovered from syndrome histories through a Walsh-Hadamard transform, giving a closed-form inverse for individual and aggregated DEM events.
Adaptive weight estimator for quantum error correction in a time-dependent environment
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Estimating detector error models from syndrome data
Detector error model probabilities can be recovered from syndrome histories through a Walsh-Hadamard transform, giving a closed-form inverse for individual and aggregated DEM events.