摘要
Topological codes, a kind of quantum error correction (QEC) code, have been used for current quantum computers due to their local qubit layout and high threshold. With the nearly linear complexity, syndrome-based belief propagation (BP) can be considered as a decoding candidate for topological codes. However, such highly degenerate codes will lead to multiple low-weight errors where the syndrome is identical so that the BP decoding is not able to distinguish it, resulting in a degradation in performance. In this paper, we propose a branch-assisted sign-flipping belief propagation (BSFBP) decoding method for topological codes based on the hypergraph-product (HGP) structure. In our algorithm, we introduce the criteria to enter the new decoding path branched from BP combined with a syndrome residual, which is obtained from the syndrome-pruning process. A sign-flipping (SF) process is also conducted to disturb the log-likelihood ratio (LLR) of the selected variable nodes, which provides diversity in the syndrome residual. Simulation results show that using the proposed BSFBP decoding is able to outperform the BP decoding by about two orders of magnitude.