# LLM-Powered Quantum Code Transpilation

arXiv: https://arxiv.org/abs/2507.12480 · HTML: https://mlsanity.com/paper/2507.12480/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 7 references that are in the map.
- First posted on arXiv 12 Jul 2025.

## Builds on (most cited first, 4 of 4)

- [Unsupervised Translation of Programming Languages](https://mlsanity.com/paper/2006.03511/) (2020)
- [Exploring and Unleashing the Power of Large Language Models in Automated Code Translation](https://mlsanity.com/paper/2404.14646/) (2024)
- [Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives](https://mlsanity.com/paper/2407.14962/) (2024)
- [Verified Code Transpilation with LLMs](https://mlsanity.com/paper/2406.03003/) (2024)

## Built on by (most cited first, 1 of 1)

- [Model-Driven Quantum Code Generation Using Large Language Models and Retrieval-Augmented Generation](https://mlsanity.com/paper/2508.21097/) (2025)

## Abstract (arXiv)

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.