Belief Propagation Convergence Prediction for Bivariate Bicycle Quantum Error Correction Codes

This project represents a specific algorithmic discovery in the field of Quantum Low-Density Parity-Check (QLDPC) codes, specifically Bivariate Bicycle (BB) codes which are currently favored by researchers (including IBM) for their high rate and performance. The 'moat' here is purely intellectual/mathematical; once the insight (that convergence correlates with the syndrome defect count's divisibility by the column weight) is published, it becomes a commodity heuristic that can be implemented in a single line of code. As a software project, it has no defensibility (0 stars, 1-day-old repo) and serves as a reference implementation for a paper. However, it is highly valuable for specialized quantum hardware teams seeking to optimize decoders by skipping unnecessary BP iterations and moving straight to OSD post-processing. Frontier labs like Google or IBM are more likely to adopt this specific heuristic into their existing decoding stacks than to build a competing product, as this is a niche optimization for a specific class of error-correcting codes.