Decoding correlated errors in quantum LDPC codes.

Maan, Arshpreet Singh; Garcia Herrero, Francisco Miguel; Paler, Alexandru; Savin, Valentin · Nat Commun · 2026

basic_science · Level V

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Abstract

We introduce a decoding framework for correlated errors in quantum LDPC codes under circuit-level noise. Our approach is a graph augmentation and rewiring for inference (GARI) method, which modifies the correlated detector error model by eliminating 4-cycles involving Y-type errors, while preserving the equivalence of the decoding problem. A normalized min-sum decoder with a hybrid serial-layered schedule is applied on the transformed graph, achieving high accuracy with low latency. Performance is further enhanced (on par with XYZ-Relay-BP) through ensemble decoding, where 24 randomized normalized min-sum decoders run in parallel on the transformed graph. For the distance 12 Bivariate Bicycle code the logical error rate of (6.70 ± 1.93) × 10<sup>-9</sup> is achieved at a physical error rate of 10<sup>-3</sup>. Furthermore, preliminary FPGA implementation results show that such high accuracy can be achieved in real time, with a per-round average decoding latency of 273 ns and sub-microsecond latency in 99.99% of the decoding instances.