We introduce a generalized low-density parity-check decoding framework for quantum Tanner codes utilizing soft-output guessing random additive noise decoding (SOGRAND). By soft-output decoding entire component codes, we mitigate trapping sets and cycles, resulting in improved convergence. SOGRAND, combined with ordered statistic decoding (OSD) post-processing, outperforms the standard belief propagation plus OSD baseline by up to three orders of magnitude in logical error rate, providing a way forward for scalable decoding of the emerging class of Tanner-code-based quantum codes.

翻译：我们提出一种基于软输出猜测随机加性噪声译码(SOGRAND)的广义低密度奇偶校验译码框架，用于量子Tanner码。通过对整个分量码进行软输出译码，我们有效缓解了陷阱集与环路问题，从而提升了收敛性能。结合有序统计译码(OSD)后处理的SOGRAND方法，在逻辑错误率上相比标准置信传播加OSD基线方法实现了最多三个数量级的性能提升，为新兴的Tanner码基量子码的可扩展译码提供了可行路径。