Belief Propagation Convergence Prediction for Bivariate Bicycle Quantum Error Correction Codes

TL;DR

This paper introduces a simple modulo-based method to predict whether belief propagation will converge when decoding certain quantum error correction codes, significantly improving decoding efficiency.

Contribution

The authors demonstrate that a single modulo operation on syndrome defect counts can accurately predict BP convergence, a novel approach for quantum LDPC code decoding.

Findings

Modulo w predicts BP convergence with high accuracy (AUC=0.995) at low error rates.

BP failures are mostly due to measurement errors outside the model space, confirmed by error cluster analysis.

Prediction method is invariant across different BP scheduling strategies and decoder variants.

Abstract

Decoding Bivariate Bicycle (BB) quantum error correction codes typically requires Belief Propagation (BP) followed by Ordered Statistics Decoding (OSD) post-processing when BP fails to converge. Whether BP will converge on a given syndrome is currently determined only after running BP to completion. We show that convergence can be predicted in advance by a single modulo operation: if the syndrome defect count is divisible by the code's column weight w, BP converges with high probability (100% at p <= 0.001, degrading to 87% at p = 0.01); otherwise, BP fails with probability >= 90%. The mechanism is structural: each physical data error activates exactly w stabilizers, so a defect count not divisible by w implies the presence of measurement errors outside BP's model space. Validated on five BB codes with column weights w = 2, 3, and 4, mod-w achieves AUC = 0.995 as a convergence classifier at p = 0.001 under phenomenological noise, dominating all other syndrome features (next best: AUC = 0.52). The false positive rate scales empirically as O(p^2.05) (R^2 = 0.98), confirming the analytical bound from Proposition 2. Among BP failures on mod-w = 0 syndromes, 82% contain weight-2 data error clusters, directly confirming the dominant failure mechanism. The prediction is invariant under BP scheduling strategy and decoder variant, including Relay-BP - the strongest known BP enhancement for quantum LDPC codes. These results apply directly to IBM's Gross code [[144, 12, 12]] and Two-Gross code [[288, 12, 18]], targeted for deployment in 2026-2028.