Efficient near-optimal decoding of the surface code through ensembling

• URL: http://arxiv.org/abs/2401.12434v3
• Date: Fri, 15 Mar 2024 05:49:46 GMT
• Title: Efficient near-optimal decoding of the surface code through ensembling
• Authors: Noah Shutty, Michael Newman, Benjamin Villalonga,
• Abstract summary: Harmonized ensembles of MWPM-based decoders achieve lower logical error rates than their individual counterparts. We conclude that harmonization provides a viable path towards highly accurate real-time decoding.
• Score: 1.7272067657096395
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We introduce harmonization, an ensembling method that combines several "noisy" decoders to generate highly accurate decoding predictions. Harmonized ensembles of MWPM-based decoders achieve lower logical error rates than their individual counterparts on repetition and surface code benchmarks, approaching maximum-likelihood accuracy at large ensemble sizes. We can use the degree of consensus among the ensemble as a confidence measure for a layered decoding scheme, in which a small ensemble flags high-risk cases to be checked by a larger, more accurate ensemble. This layered scheme can realize the accuracy improvements of large ensembles with a relatively small constant factor of computational overhead. We conclude that harmonization provides a viable path towards highly accurate real-time decoding.

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