LLM-Powered Quantum Code Transpilation

• URL: http://arxiv.org/abs/2507.12480v1
• Date: Sat, 12 Jul 2025 21:16:21 GMT
• Title: LLM-Powered Quantum Code Transpilation
• Authors: Nazanin Siavash, Armin Moin,
• Abstract summary: There exist various Software Development Kits (SDKs) tailored to different quantum computing platforms.<n>These are known as Quantum SDKs (QSDKs). Examples include but are not limited to Qiskit, Cirq, and PennyLane.
• Score: 3.9134031118910264
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

Related papers

• Quantum Knowledge Distillation for Large Language Models [10.023534560183919]
  We propose a Quantum knowledge Distillation model for Large Language Models (QD-LLM)<n>In classical simulation, QD-LLM outperforms several mainstream distillation methods on multiple text classification tasks.<n>We deploy the obtained circuits on the Baihua superconducting quantum processor via the Quafu platform to assess practical feasibility.
  arXiv  Detail & Related papers  (2025-05-19T14:56:24Z)
• QADL: Prototype of Quantum Architecture Description Language [5.032368657209642]
  Quantum Software (QSW) uses the principles of quantum mechanics, specifically programming quantum bits (qubits) that manipulate quantum gates, to implement quantum computing systems. We introduce QADL (Quantum Architecture Language), which provides a specification language, design space, and execution environment for QSW architecture.
  arXiv  Detail & Related papers  (2024-10-13T19:09:38Z)
• Quantum Serverless Paradigm and Application Development using the QFaaS Framework [17.398771276317575]
  This chapter introduces the concept of serverless quantum computing with examples using QF. The framework utilizes the serverless computing model to simplify quantum application development and deployment. The chapter provides comprehensive documentation and guidelines for deploying and using QF.
  arXiv  Detail & Related papers  (2024-07-03T06:12:55Z)
• Advancing Quantum Software Engineering: A Vision of Hybrid Full-Stack Iterative Model [5.465644852381506]
  This paper proposes a hybrid full-stack iterative model that integrates quantum and classical computing.<n>It presents a comprehensive lifecycle for quantum software development, encompassing quantum-agnostic coding, testing, deployment, cloud computing services, orchestration, translation, execution, and interpretation phases.
  arXiv  Detail & Related papers  (2024-03-18T11:18:33Z)
• Delegated variational quantum algorithms based on quantum homomorphic encryption [69.50567607858659]
  Variational quantum algorithms (VQAs) are one of the most promising candidates for achieving quantum advantages on quantum devices. The private data of clients may be leaked to quantum servers in such a quantum cloud model. A novel quantum homomorphic encryption (QHE) scheme is constructed for quantum servers to calculate encrypted data.
  arXiv  Detail & Related papers  (2023-01-25T07:00:13Z)
• TeD-Q: a tensor network enhanced distributed hybrid quantum machine learning framework [48.491303218786044]
  TeD-Q is an open-source software framework for quantum machine learning.<n>It seamlessly integrates classical machine learning libraries with quantum simulators.<n>It provides a graphical mode in which the quantum circuit and the training progress can be visualized in real-time.
  arXiv  Detail & Related papers  (2023-01-13T09:35:05Z)
• Open Source Variational Quantum Eigensolver Extension of the Quantum Learning Machine (QLM) for Quantum Chemistry [0.0]
  We introduce a novel open-source QC package, denoted Open-VQE, providing tools for using and developing chemically-inspired adaptive methods. It is able to use the Atos Quantum Learning Machine (QLM), a general programming framework enabling to write, optimize simulate computing programs. Along with OpenVQE, we introduce myQLMFermion, a new open-source module (that includes the key QLM ressources that are important for QC developments)
  arXiv  Detail & Related papers  (2022-06-17T14:24:22Z)
• Recent Advances for Quantum Neural Networks in Generative Learning [98.88205308106778]
  Quantum generative learning models (QGLMs) may surpass their classical counterparts. We review the current progress of QGLMs from the perspective of machine learning. We discuss the potential applications of QGLMs in both conventional machine learning tasks and quantum physics.
  arXiv  Detail & Related papers  (2022-06-07T07:32:57Z)
• QFaaS: A Serverless Function-as-a-Service Framework for Quantum Computing [22.068803245816266]
  We propose a Quantum Function-as-a-Service framework to advance quantum computing. Our framework provides essential components of a quantum serverless platform to simplify the software development and adapt to the quantum cloud computing paradigm. This paper proposes architectural design, principal components, the life cycle of hybrid quantum-classical function, operation workflow, and implementation of QF.
  arXiv  Detail & Related papers  (2022-05-30T04:18:53Z)
• On exploring the potential of quantum auto-encoder for learning quantum systems [60.909817434753315]
  We devise three effective QAE-based learning protocols to address three classically computational hard learning problems. Our work sheds new light on developing advanced quantum learning algorithms to accomplish hard quantum physics and quantum information processing tasks.
  arXiv  Detail & Related papers  (2021-06-29T14:01:40Z)
• A MLIR Dialect for Quantum Assembly Languages [78.8942067357231]
  We demonstrate the utility of the Multi-Level Intermediate Representation (MLIR) for quantum computing. We extend MLIR with a new quantum dialect that enables the expression and compilation of common quantum assembly languages. We leverage a qcor-enabled implementation of the QIR quantum runtime API to enable a retargetable (quantum hardware agnostic) compiler workflow.
  arXiv  Detail & Related papers  (2021-01-27T13:00:39Z)
• Extending C++ for Heterogeneous Quantum-Classical Computing [56.782064931823015]
  qcor is a language extension to C++ and compiler implementation that enables heterogeneous quantum-classical programming, compilation, and execution in a single-source context. Our work provides a first-of-its-kind C++ compiler enabling high-level quantum kernel (function) expression in a quantum-language manner.
  arXiv  Detail & Related papers  (2020-10-08T12:49:07Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.