D'Aloisio, G;
Fortz, S;
Hanna, C;
Fortunato, D;
Bensoussan, A;
Mendiluze Usandizaga, E;
Sarro, F;
(2024)
Exploring LLM-Driven Explanations for Quantum Algorithms.
In:
ESEM '24: Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement.
(pp. pp. 475-481).
ACM
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Abstract
Background: Quantum computing is a rapidly growing new programming paradigm that brings significant changes to the design and implementation of algorithms. Understanding quantum algorithms requires knowledge of physics and mathematics, which can be challenging for software developers. Aims: In this work, we provide a first analysis of how LLMs can support developers' understanding of quantum code. Method: We empirically analyse and compare the quality of explanations provided by three widely adopted LLMs (Gpt3.5, Llama2, and Tinyllama) using two different human-written prompt styles for seven state-of-the-art quantum algorithms. We also analyse how consistent LLM explanations are over multiple rounds and how LLMs can improve existing descriptions of quantum algorithms. Results: Llama2 provides the highest quality explanations from scratch, while Gpt3.5 emerged as the LLM best suited to improve existing explanations. In addition, we show that adding a small amount of context to the prompt significantly improves the quality of explanations. Finally, we observe how explanations are qualitatively and syntactically consistent over multiple rounds. Conclusions: This work highlights promising results, and opens challenges for future research in the field of LLMs for quantum code explanation. Future work includes refining the methods through prompt optimisation and parsing of quantum code explanations, as well as carrying out a systematic assessment of the quality of explanations.
| Type: | Proceedings paper |
|---|---|
| Title: | Exploring LLM-Driven Explanations for Quantum Algorithms |
| Event: | ESEM '24: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3674805.3690753 |
| Publisher version: | https://doi.org/10.1145/3674805.3690753 |
| Language: | English |
| Additional information: | Copyright © 2024 Owner/Author. This work is licensed under a Creative Commons Attribution International 4.0 License. |
| Keywords: | Quantum Computing, Large Language Models, Code Explainability |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10205141 |
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