标题： 量子纠错中的设计自动化 显示英文标题

标题： Design Automation in Quantum Error Correction

摘要： 量子错误纠正（QEC）通过解决量子态的脆弱性并减轻退相干引起的错误，支撑了实用的容错量子计算（FTQC）。 随着量子设备的扩展，集成稳健的QEC协议是必要的，以将逻辑错误率抑制在阈值以下并确保可靠操作，尽管当前框架存在大量的量子比特开销和硬件效率低下问题。 因此，QEC流程中的设计自动化至关重要，它能够自动合成、转换、布局和验证纠错电路，以减少量子比特占用空间并推动容错边界。 本章全面介绍了QEC中的设计自动化，分为四个主要部分。 第一部分深入探讨了QEC的理论方面，涵盖逻辑与物理量子比特表示、稳定子码构造以及错误综合征提取机制。 第二部分概述了QEC设计流程，详细说明了需要设计自动化的领域。 第三部分综述了设计自动化技术的最新进展，包括算法$T$-门优化、改进的表面码架构以减少量子比特开销，以及基于机器学习的解码器自动化。 最后一部分考察了近期的FTQC架构，将自动化的QEC流水线集成到可扩展的硬件平台中，并讨论端到端的验证方法。 每个部分都辅以近期研究工作的案例分析，说明实际应用和性能权衡。 总体而言，本章旨在使读者全面了解容错量子计算背景下QEC系统设计中的设计自动化。 显示英文摘要

摘要： Quantum error correction (QEC) underpins practical fault-tolerant quantum computing (FTQC) by addressing the fragility of quantum states and mitigating decoherence-induced errors. As quantum devices scale, integrating robust QEC protocols is imperative to suppress logical error rates below threshold and ensure reliable operation, though current frameworks suffer from substantial qubit overheads and hardware inefficiencies. Design automation in the QEC flow is thus critical, enabling automated synthesis, transpilation, layout, and verification of error-corrected circuits to reduce qubit footprints and push fault-tolerance margins. This chapter presents a comprehensive treatment of design automation in QEC, structured into four main sections. The first section delves into the theoretical aspects of QEC, covering logical versus physical qubit representations, stabilizer code construction, and error syndrome extraction mechanisms. In the second section, we outline the QEC design flow, detailing the areas highlighting the need for design automation. The third section surveys recent advancements in design automation techniques, including algorithmic $T$-gate optimization, modified surface code architecture to incorporate lesser qubit overhead, and machine-learning-based decoder automation. The final section examines near-term FTQC architectures, integrating automated QEC pipelines into scalable hardware platforms and discussing end-to-end verification methodologies. Each section is complemented by case studies of recent research works, illustrating practical implementations and performance trade-offs. Collectively, this chapter aims to equip readers with a holistic understanding of design automation in QEC system design in the fault-tolerant landscape of quantum computing.