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  • Open Access

BlockBP decoder for the surface code

Aviad Kaufmann*

Itai Arad

  • *Contact author: aviadskaufmann@gmail.com
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Phys. Rev. Research 7, 043025 – Published 7 October, 2025

DOI: https://doi.org/10.1103/z2qt-smfb

Abstract

We present a new decoder for the surface code, which combines the accuracy of the tensor-network decoders with the efficiency and parallelism of the belief-propagation algorithm. Our main idea is to replace the expensive tensor-network contraction step in the tensor-network decoders with the blockBP algorithm—a recent approximate contraction algorithm, based on belief propagation. Our decoder is therefore a belief-propagation decoder that works in the degenerate maximal likelihood decoding framework. Unlike conventional tensor-network decoders, our algorithm can run efficiently in parallel, and may therefore be suitable for real-time decoding. We numerically test our decoder and show that for a large range of lattice sizes and noise levels it delivers a logical error probability that outperforms the Minimal Weight Perfect Matching decoder, sometimes by more than an order of magnitude.

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Phys. Rev. Research 7, 043025– Published 7 October, 2025
  • Received 12 March 2025
  • Accepted 27 August 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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