发表机构
Arizona State University; The University of Texas at Arlington（亚利桑那州立大学; 阿灵顿得克萨斯大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对量子LDPC码，提出一种结合四元评分与并行比特翻转的序贯BP解码器，通过并行候选延续提升学习型序贯BP的可靠性，并保持低延迟。
AI 中文摘要
量子低密度奇偶校验（QLDPC）码是低开销容错量子计算的有前景候选方案，但其实际应用需要快速、低复杂度且可靠的解码器。置信传播（BP）因其局部消息传递结构而具有吸引力，然而标准的洪泛BP在QLDPC码上常因短环、简并性和对称解码轨迹而遭受收敛失败。学习型序贯BP通过使用强化学习策略选择变量节点更新顺序来改善收敛性，但单一学习轨迹仍可能对不利的局部泡利决策敏感。我们提出了一种学习型并行比特翻转序贯BP解码器，其采用新的四元评分，该评分结合了综合征增益、量化泡利对数似然惩罚以及在假设翻转后状态下的Q表前瞻。我们的解码器首先运行固定迭代次数的学习型序贯BP。如果综合征未满足，则构造四元比特翻转候选，每个候选对应于改变一个量子比特的当前泡利决策。选定的候选从相同的解码器状态初始化独立的学习型序贯BP延续。由于这些延续是独立的，它们可以并行执行，因此测试多个候选主要增加并行硬件资源而非序贯解码延迟。在去极化信道上的代表性QLDPC码仿真表明，所提出的解码器在具有并行低延迟结构的同时，提高了学习型序贯BP的可靠性。
英文摘要
Quantum low-density parity-check (QLDPC) codes are promising candidates for low-overhead fault-tolerant quantum computation, but their practical use requires fast, low-complexity, and reliable decoders. Belief propagation (BP) is attractive because of its local message-passing structure, yet standard flooding BP often suffers from convergence failures on QLDPC codes due to short cycles, degeneracy, and symmetric decoding trajectories. Learned sequential BP improves convergence by using a reinforcement-learning policy to choose variable-node update orders, but a single learned trajectory can still be sensitive to unfavorable local Pauli decisions. We propose a learned parallel bit-flipping sequential BP decoder with a new quaternary score combining syndrome gain, a quantized Pauli log-likelihood penalty, and Q-table lookahead at hypothetical post-flip states. Our decoder first runs learned sequential BP for a fixed number of iterations. If the syndrome is not satisfied, it constructs quaternary bit-flipping candidates, each corresponding to changing the current Pauli decision of one qubit. The selected candidates initialize independent learned sequential BP continuations from the same decoder state. Since these continuations are independent, they can be executed in parallel, so testing several candidates mainly increases parallel hardware resources rather than sequential decoding latency. Simulations on representative QLDPC codes over the depolarizing channel show that the proposed decoder improves the reliability of learned sequential BP while having a parallel low-latency structure.
