Quantum computing for effective nuclear lattice model
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Quantum Physics arXiv:2604.13430 (quant-ph) [Submitted on 15 Apr 2026] Title:Quantum computing for effective nuclear lattice model Authors:Zhushuo Liu, Jia-ai Shi, Bing-Nan Lu, Xiaosi Xu View a PDF of the paper titled Quantum computing for effective nuclear lattice model, by Zhushuo Liu and 2 other authors View PDF HTML (experimental) Abstract:Nuclear lattice effective field theory has become an important framework for quantum many-body calculations in nuclear physics, yet its classical implementation remains increasingly challenging for more general interactions and larger systems. In this work, we develop a quantum-computing framework for a three-dimensional nuclear lattice model. We construct a variational quantum eigensolver framework and systematically compare the Jordan-Wigner and Gray code encodings. Our analysis shows that for the few-body systems considered here, Gray code combined with symmetry reduction yields a substantially more compact qubit representation. Based on this framework, we perform numerical studies for $^{2}\mathrm{H}$, $^{3}\mathrm{H}$, and $^{4}\mathrm{He}$ on finite lattices. The calculated ground-state energies exhibit a clear approach toward the corresponding experimental binding energies as the lattice size increases. These results provide a proof-of-principle foundation for future quantum simulations of nuclear many-body problems. Comments: Subjects: Quantum Physics (quant-ph); Nuclear Theory (nucl-th) Cite as: arXiv:2604.13430 [quant-ph] (or arXiv:2604.13430v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2604.13430 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Xiaosi Xu [view email] [v1] Wed, 15 Apr 2026 03:02:44 UTC (68 KB) Full-text links: Access Paper: View a PDF of the paper titled Quantum computing for effective nuclear lattice model, by Zhushuo Liu and 2 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-04 Change to browse by: nucl-th References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)