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Neural Belief-Propagation Decoders for Quantum Error-Correcting Codes
Ye-Hua Liu1, David Poulin1,2
1Département de Physique & Institut Quantique, Université de Sherbrooke, J1K 2R1 Sherbrooke, Québec, Canada.
Abstract:
Belief-propagation (BP) decoders play a vital role in modern coding theory, but they are not suitable to decode quantum error-correcting codes because of a unique quantum feature called error degeneracy. Inspired by an exact mapping between BP and deep neural networks, we train neural BP decoders for quantum low-density parity-check codes with a loss function tailored to error degeneracy. Training substantially improves the performance of BP decoders for all families of codes we tested and may solve the degeneracy problem which plagues the decoding of quantum low-density parity-check codes.
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