CUDA-Q Logical：面向容错量子计算的可重定向编译
CUDA-Q Logical: Retargetable Compilation for Fault-Tolerant Quantum Computing
- NVIDIA（英伟达）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对容错量子计算编译中资源估算与编译器工件脱节的问题，提出可重定向编译基础设施CUDA-Q Logical，通过分层保留语义与来源，统一编译与资源分析，实现跨架构比较与成本归因。
AI中文摘要：
实现容错量子计算需要将逻辑程序映射到异构量子纠错（QEC）码和多样化的容错执行模型，调度物理资源，并耦合到实时经典控制与反馈。每个步骤都有专门的工具，但这些工具依赖于手动组合和转换，从而丢弃了假设和来源信息，将资源估算与它们所描述的编译器工件分离开来，使得验证正确性、比较架构或将成本归因于特定设计选择变得困难。我们提出了CUDA-Q Logical，一个用于可重定向容错编译、分析和执行的可扩展编译器基础设施。CUDA-Q Logical与CUDA-Q及其他主流前端互操作，通过受约束的逻辑虚拟机、QEC微码、物理门调度和实时控制计划逐步降低与目标无关的逻辑程序，每一层都保留语义和来源，同时验证组合和资源约束。通过直接从编译器工件推导每个资源估算，该框架统一了编译和资源分析，实现了逐步精化的估算和原则性的跨架构比较，同时允许将QEC码、执行模型、解码器和硬件架构作为模块化扩展引入。在从应用架构研究到qLDPC手术和探测器错误模型组合的工作负载中，我们展示了从调度推导的估算与已建立的独立模型相协调。至关重要的是，这种编译器可见的结构暴露了聚合分析公式隐藏的成本驱动因素，将QEC工件完整地携带到模拟中，并展示了容错量子计算的完整编译流水线。
英文摘要：
Realizing fault-tolerant quantum computing requires mapping logical programs to heterogeneous quantum error correction (QEC) codes and diverse fault-tolerant execution models, scheduling physical resources, and coupling to real-time classical control and feedback. Specialized tools exist for each step but rely on manual composition and translation that discard assumptions and provenance, separating resource estimates from the compiler artifacts they describe, and making it difficult to validate correctness, compare architectures, or attribute costs to specific design choices. We present CUDA-Q Logical, an extensible compiler infrastructure for retargetable fault-tolerant compilation, analysis, and execution. Interoperable with CUDA-Q and other mainstream front-ends, CUDA-Q Logical progressively lowers target-independent logical programs through a constrained logical virtual machine, QEC microcode, physical gate schedules, and real-time control plans, with each layer preserving semantics and provenance, while verifying composition and resource constraints. By deriving every resource estimate directly from compiler artifacts, the framework unifies compilation and resource analysis, enabling successively refined estimates and principled cross-architecture comparison while permitting QEC codes, execution models, decoders, and hardware architectures to be introduced as modular extensions. Across workloads ranging from application-architecture studies to qLDPC surgery and detector-error-model composition, we show that schedule-derived estimates reconcile with established independent models. Crucially, this compiler-visible structure exposes cost drivers hidden by aggregate analytical formulas, carries QEC artifacts intact into simulation, and demonstrates a complete compilation pipeline for fault-tolerant quantum computing.
