AI & ML
Large Language Models for Quantum Code Translation: An Exploratory Study
arXiv cs.SE0 views
arXiv:2610.34841v1 Announce Type: new Abstract: Quantum software development is challenged by quantum-mechanical semantics and fragmented software development kits (SDKs), which complicate cross-SDK code translation and execution. In this paper, we propose an LLM-based approach for translating executable programs between high-level quantum SDKs. We develop a quantum-aware translation workflow whose prompt design and validation reflect quantum semantics and accommodate the version evolution of quantum ecosystems. We conduct a preliminary evaluation of 4 LLM configurations on 43 tasks, translating Qiskit programs to PennyLane and Q#. LLMs achieve a zero-shot Pass@1 of up to 72.33%, while one-shot prompting further improves the translation effectiveness. These results suggest potential for quantum code translation by LLMs.
Source:https://arxiv.org/abs/2610.34841PreviousSilent and Costly: Characterizing and Detecting Prompt-Caching Mis-Integration in LLM AgentsNextEthics by Configuration: AI Ethics Principles in Coding Agent Instructions
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