Learning Neural Decoding with Parallelism and Self-Coordination for Quantum Error Correction

• URL: http://arxiv.org/abs/2509.03815v1
• Date: Thu, 04 Sep 2025 02:02:27 GMT
• Title: Learning Neural Decoding with Parallelism and Self-Coordination for Quantum Error Correction
• Authors: Kai Zhang, Situ Wang, Linghang Kong, Fang Zhang, Zhengfeng Ji, Jianxin Chen,
• Abstract summary: Existing implementations of neural network decoders lack the parallelism required to decode the syndrome stream generated by a superconducting logical qubit in real time.<n>We address this issue by training a recurrent, transformer-based neural network specifically tailored for sliding-window decoding.<n>This approach enables the network to self-coordinate across neighboring windows, facilitating high-accuracy parallel decoding of arbitrarily long memory experiments.
• Score: 7.184133388805955
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Fast, reliable decoders are pivotal components for enabling fault-tolerant quantum computation. Neural network decoders like AlphaQubit have demonstrated significant potential, achieving higher accuracy than traditional human-designed decoding algorithms. However, existing implementations of neural network decoders lack the parallelism required to decode the syndrome stream generated by a superconducting logical qubit in real time. Moreover, integrating AlphaQubit with sliding window-based parallel decoding schemes presents non-trivial challenges: AlphaQubit is trained solely to output a single bit corresponding to the global logical correction for an entire memory experiment, rather than local physical corrections that can be easily integrated. We address this issue by training a recurrent, transformer-based neural network specifically tailored for sliding-window decoding. While our network still outputs a single bit per window, we derive training labels from a consistent set of local corrections and train on various types of decoding windows simultaneously. This approach enables the network to self-coordinate across neighboring windows, facilitating high-accuracy parallel decoding of arbitrarily long memory experiments. As a result, we resolve the throughput limitation that previously prohibited the application of AlphaQubit-type decoders in fault-tolerant quantum computation.

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