Neural Belief Propagation Decoders for Concatenated Calderbank-Shor-Steane Codes

Quantum low-density parity check (QLDPC) codes have rapidly developed in the field of quantum error correction in recent years. A variety of quantum code families have emerged from numerous research activities. In this paper, we employ concatenated Calderbank-Shor-Steane (CSS) codes, hypergraph product codes, and Bacon-Shor codes to train belief-propagation (BP) and neural BP (NBP) decoders. At the same time, we employ a concatenation scheme in BP and NBP, the amplified construction of CSS codes is realized, and the training of longer length parameter quantum codes is realized. The numerical results show that the concatenated CSS codes demonstrate better error correction performance compared to both hypergraph product codes and Bacon-Shor codes. In addition, the concatenated CSS codes are trained using the concatenation scheme to improve the error correction performance of the decoder.