🤖 AI Summary
To address the high latency and computational complexity of BP-OSD decoding for quantum LDPC codes, this paper proposes a lightweight fully parallel BP decoder. Methodologically, it eliminates external auxiliary algorithms and instead innovatively exploits oscillatory behavior in BP iterations to statistically identify unreliable bits; inspired by Chase decoding, it generates test patterns for efficient speculative post-processing—all operations are fully parallelized. Compared to BP-OSD, the proposed decoder significantly reduces latency and hardware complexity while achieving comparable or superior logical error rates across various bicyclic quantum LDPC codes. The key contribution is the first direct utilization of BP oscillation characteristics for reliability assessment and post-processing triggering—without incurring additional algorithmic overhead—thereby achieving high performance, low latency, and strong hardware efficiency.
📝 Abstract
In this work, we propose a lightweight decoder based solely on belief-propagation (BP), augmented with a speculative post-processing strategy inspired by classical Chase decoding. Our method identifies unreliable bits via BP oscillation statistics, generates a set of modified test patterns, and decodes them in parallel using low-iteration BP. We demonstrate that our approach can achieve logical error rates comparable to or even better than BP-OSD, but has lower latency over its parallelization for a variety of bivariate bicycle codes, which significantly reduces decoding complexity.