标题： 基于大语言模型的量子代码编译 显示英文标题

标题： LLM-Powered Quantum Code Transpilation

摘要： 存在各种针对不同量子计算平台的软件开发工具包（SDKs）。 这些被称为量子SDKs（QSDKs）。 示例包括但不限于Qiskit、Cirq和PennyLane。 然而，这种多样性给混合量子-经典软件系统的互操作性和跨平台开发带来了重大挑战。 传统的基于规则的编译器在将代码在QSDK之间转换时设计和维护耗时，需要在源代码和目标代码中具备深厚的专业知识和严格的映射关系。 在本研究中，我们探索使用大型语言模型（LLMs）作为一种灵活且自动化的解决方案。 利用它们的预训练知识和上下文推理能力，我们将LLMs定位为与编程语言无关的编译器，能够在保持功能等价性的前提下，将量子程序从一个QSDK转换到另一个QSDK。 我们的方法消除了手动定义转换规则的需要，并为量子软件可移植性提供了一种可扩展的解决方案。 这项工作代表了在量子计算生态系统中实现智能、通用编译迈出的一步。 显示英文摘要

摘要： There exist various Software Development Kits (SDKs) tailored to different quantum computing platforms. These are known as Quantum SDKs (QSDKs). Examples include but are not limited to Qiskit, Cirq, and PennyLane. However, this diversity presents significant challenges for interoperability and cross-platform development of hybrid quantum-classical software systems. Traditional rule-based transpilers for translating code between QSDKs are time-consuming to design and maintain, requiring deep expertise and rigid mappings in the source and destination code. In this study, we explore the use of Large Language Models (LLMs) as a flexible and automated solution. Leveraging their pretrained knowledge and contextual reasoning capabilities, we position LLMs as programming language-agnostic transpilers capable of converting quantum programs from one QSDK to another while preserving functional equivalence. Our approach eliminates the need for manually defined transformation rules and offers a scalable solution to quantum software portability. This work represents a step toward enabling intelligent, general-purpose transpilation in the quantum computing ecosystem.