🤖 AI Summary
This work addresses the challenge that symmetries arising from degeneracy in generalized bicycle quantum LDPC codes hinder conventional iterative decoders from fully exploiting their distance advantage. By characterizing this degenerate structure through graph theory, the paper introduces edge coloring into the decoding process for the first time, proposing isotropic and anisotropic min-sum algorithms based on three strategies: uncolored, block-colored, and edge-colored. Theoretical analysis demonstrates that edge coloring eliminates all automorphisms within low-weight stabilizer subgraphs. Experimental results show that the proposed edge-anisotropic min-sum decoder significantly outperforms existing approaches within a small number of iterations, achieving notable performance gains across multiple generalized bicycle codes.
📝 Abstract
Quantum low-density parity-check (QLDPC) codes provide non vanishing rates, distance scaling with the blocklength of the code, and facilitate fast iterative decoding because of their sparsity. However, in practice iterative decoding fails to exploit the distance of the code, because it cannot resolve the symmetries imposed by degeneracy. In this work, we provide a graph theoretic characterization of degeneracy for the family of generalized bicycle (GB) codes. This viewpoint shows that harmful degenerate error patterns persist whenever they remain related by automorphisms preserved by the decoder. Motivated by symmetry breaking via graph coloring, we compare three coloring approaches: no coloring, block-coloring, and edge-coloring. For GB codes, we show that edge-coloring can eliminate all automorphisms in low-weight stabilizer-induced subgraphs. We practically realize the coloring schemes as isotropic, block- anisotropic and edge-anisotropic min-sum (MS) decoding. Experimental results show that edge anisotropic min-sum decoding obtains improved performance over isotropic and block anisotropic decoding for several GB codes in a small number of iterations.