🤖 AI Summary
Quantum LDPC codes suffer from degraded performance under belief propagation (BP) decoding due to short cycles and degeneracy in their Tanner graphs. This work proposes a general auxiliary node framework that introduces auxiliary variable and check nodes into the decoding graph of CSS quantum codes, thereby enhancing the design flexibility of the graphical structure. The framework unifies and extends existing techniques such as four-cycle elimination and subcode integration, enabling efficient BP decoding under circuit-level noise. The resulting graph-derived subcode-integrated decoder substantially reduces the logical error rate per decoding round and outperforms conventional BP decoding on four-cycle-free graphs.
📝 Abstract
Many recently proposed Calderbank-Shor-Steane (CSS) quantum low-density parity-check (QLDPC) codes have sparse decoding graphs, enabling syndrome-based belief propagation (BP) decoding at low complexity. Their construction, however, often results in properties that impair BP performance, such as short cycles and degeneracy. In this work, we propose a general framework for introducing auxiliary variable nodes (AVNs) and auxiliary check nodes (ACNs) into the decoding graph of CSS codes, compatible with the standard stabilizer measurement framework. This provides an additional degree of freedom in the design of the decoding graph itself and can be used to tackle the aforementioned shortcomings. We show that recently proposed techniques, 4-cycle removal and subcode ensemble decoding, can be interpreted as instances of this framework. For 4-cycle removal, we find that the gains depend strongly on the BP iteration count and check-node message scaling. Building on this framework, we further propose a graph-derived subcode ensemble decoder and demonstrate under circuit-level noise that it substantially reduces the per-round logical error rate compared with BP on the corresponding 4-cycle-free decoding graph.