AI 中文总结
该研究针对现有量子编程语言的缺陷，提出带纠错方案抽象和跨层分析的量子编程语言及资源估计框架，在实用大规模量子算法实现上验证其可实现资源节省与准确估计。
AI 中文摘要
容错量子计算可实现实用量子算法的部署，但纠错会产生大量开销，使资源估计成为核心关注点。现有量子编程语言要么要求程序员处理底层硬件细节，导致容错实现繁琐；要么抽象掉底层纠错方案，降低资源利用和估计的有效性。为解决这些限制并保持可编程性，我们提出一种能实现高效资源利用的量子编程语言，以及用于综合资源分析的资源估计框架。该框架具有程序员可见的纠错方案抽象和跨层程序-硬件分析功能，可系统探索资源权衡。我们在实用大规模量子算法的详细容错实现上评估该方法，包括现有框架中通常视为黑盒的组件。结果表明，我们的框架可实现大量资源节省，同时为容错量子程序提供详细、细粒度且准确的资源估计。
英文摘要
Fault-tolerant quantum computation enables the deployment of practical quantum algorithms but incurs substantial overhead from error correction, making resource estimation a central concern. Beyond case-by-case analyses, existing quantum programming languages either require programmers to manipulate low-level hardware details, rendering fault-tolerant implementations cumbersome, or abstract away the underlying error-correction schemes, reducing the effectiveness of resource utilization and estimation. To address these limitations while preserving programmability, we present a quantum programming language that enables efficient resource utilization, together with a resource-estimation framework for comprehensive resource analysis. Our framework features programmer-visible abstractions of error-correction schemes and cross-layer program-hardware analysis, allowing systematic exploration of resource trade-offs. We evaluate our approach on detailed fault-tolerant implementations of practical large-scale quantum algorithms, including components typically treated as black boxes in existing frameworks. The results demonstrate that our framework enables substantial resource savings while delivering detailed, fine-grained, and accurate resource estimates for fault-tolerant quantum programs.
