Latency-Constrained Hardware-Aware Quantum Error Correction Co-Design with Adaptive Confidence-Gated Neural Decoding for the Rotated Surface Code
用于旋转表面码的具有自适应置信门控神经解码的延迟受限硬件感知量子纠错协同设计
机构 * Department of Physics, Quantum Information and Computation, Indian Institute of Technology Jodhpur（物理系、量子信息与计算系，印度理工学院贾尔普尔）
专题命中 BCI数据与评测 ：neural decoding(title)；分类 cs.LG
AI总结 研究针对旋转表面码实时解码瓶颈，提出自适应置信门控解码框架，经实验验证，该框架能在有限增加解码成本下提升逻辑精度，神经解码器吞吐量在特定条件下饱和，还发布相关资源并区分贡献与未来工作方向。
Comments 29 pages, 18 figures, 12 tables. Source code, trained models, and benchmark data: https://github.com/Sumitchongder/adaptive-qec-decoder
