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量子计算系统与软件综述

A Review of Quantum Computing Systems and Software

  • 摘要:
    研究背景 量子计算被视为突破传统计算瓶颈的重要方向,在物理模拟、组合优化与部分机器学习任务中展现出潜在的计算优势。然而,当前量子硬件仍面临高噪声、受限的门操作速度与规模化挑战,导致电路可执行深度与保真度受到明显约束。在此背景下,量子计算的发展不再仅依赖单一层面的器件改进或算法创新,而是需要从体系结构视角理解“硬件—系统—编译—编程接口—应用”之间的协同关系:硬件连通性与误差模型直接影响编译策略与门分解的选择,系统层的调度、标定与纠错机制影响整体运行稳定性,而软件层的验证与修复方法则进一步保障了程序的可靠性。
    目的 本文旨在从跨层体系结构视角,系统梳理量子计算硬件与软件的关键技术脉络,构建一个覆盖硬件架构、量子应用、编程接口、编译流程与系统服务的统一分析框架,从而揭示各层之间的依赖关系与性能瓶颈。文章围绕跨层协同设计与端到端优化开展系统化梳理,明确现阶段发展瓶颈、统一评估指标体系,并为可扩展量子计算平台的演进提供方法论依据与支撑。
    方法 文章采用“跨层综述与定量对比分析”相结合的研究框架。首先,构建分层分析体系,将量子计算研究划分为硬件架构、应用、编程接口、编译流程与系统服务五个层级,并以超导与中性原子平台为代表,提炼关键硬件约束——包括连通性、门集、噪声与时延特性。在此基础上,在软件层面对典型量子应用场景展开梳理与讨论:总结主流 SDK 与编程语言接口,重点梳理验证与程序修复方法,分析可编程性与可靠性提升路径;围绕量子编译核心技术,包括逻辑到物理比特映射、幺正矩阵分解、门级优化及噪声缓解等,并明确它们与硬件特性之间的耦合关系;在系统层面,进一步探讨调度、标定与纠错等服务如何影响运行稳定性与吞吐效率。最后,在对代表性方法进行统一口径的量化比较与综合讨论中,结合量子门数量、线路深度与执行时延等核心指标,识别跨层瓶颈,进而提出面向硬件—软件协同设计的关键挑战与未来发展方向。
    结果 本文采用跨层次的视角,从应用程序与编程框架到编译器与操作系统,围绕量子计算的关键环节进行了工程实践导向的综述与对比分析。文章依据各工具在生态中的实际定位梳理了主流方案,并通过可复现的实验与统一的评价指标,为读者提供了清晰的总结与方法学规范。通过回顾已有工作,文章充分展现了量子计算如何通过硬件迭代与周边软件生态系统的协同推动而不断发展。
    结论 本文对量子计算系统与软件在不同层级的研究进行了归纳总结与分析,涵盖从应用、编程框架到编译器与操作系统的全栈环节。研究表明,量子计算的进步不仅依赖于硬件扩展,更得益于软硬件协同设计的生态系统。应用层通过量子算法利用并行性,编程框架提供抽象表达,编译器完成从逻辑到物理电路的映射与优化,而运行时系统则提供校准、调度和纠错等关键服务,共同保障量子硬件的可靠运行。未来,实现可扩展的量子优势需持续推动跨层协同设计,将算法创新、智能编译与自适应控制系统深度融合,使软件与系统成为释放量子算力的核心驱动力。

     

    Abstract: Quantum computing is an emerging paradigm that leverages quantum mechanics to solve problems difficult for classical computing. Realizing reliable quantum advantage requires not only hardware, but also a full software stack ranging from algorithms to operating systems. This paper provides a structured review of quantum computing systems and software, examining the current state and future directions of the field. We first introduce the architectures of quantum computing using superconducting and neutral atom systems as examples. At the software level, we begin by analyzing potential quantum applications, including physical simulation, optimization, and artificial intelligence. We then review current quantum programming interfaces, including software development kits (SDKs), verification, and program repair methods. Following these interfaces, this review introduces quantum compilation passes for quantum programs, such as mapping, decomposition, and noise mitigation, that transform logical algorithms into efficient, hardware-executable instructions. At the system level, we explore quantum operating system services such as scheduling, calibration, and error correction, which directly control quantum devices. Then, we present quantitative comparisons of gate count, circuit depth, and execution latency across various software-level methods. Finally, we discuss major challenges of quantum hardware and software, including high error rates, low operation speeds, and limited scalability. By integrating research across these levels, this review provides a comprehensive overview of quantum systems and software architectures, and highlights the significance of co-design between hardware and software.

     

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