State Preparation and Symmetries Demonstrates Improved Variational Quantum Eigensolver Convergence for Quantum Hamiltonians

Quantum Physics arXiv:2510.06702 (quant-ph) [Submitted on 8 Oct 2025] Title:State preparation and symmetries Authors:Ivana Miháliková, Joseph Carlson, Duff Neill, Ionel Stetcu View a PDF of the paper titled State preparation and symmetries, by Ivana Mih\'alikov\'a and 3 other authors View PDF HTML (experimental) Abstract:We demonstrate the importance of symmetries in Variational Quantum Eigensolver (VQE) algorithms to prepare the ground or specific low-lying states of quantum Hamiltonians. We examine two spin problems, one with random all-to-all couplings inspired by neutrino flavor evolution in supernovae, and the standard Heisenberg spin Hamiltonian on a $4 \times 3$ lattice. The neutrino Hamiltonian has the total spin $J$ and third component $J_{\rm{z}}$ as its only symmetries. The Heisenberg model has these symmetries plus translational invariance and reflection symmetry. We demonstrate that the convergence of variational methods is dramatically improved by keeping all symmetries. In both cases a nearly exact solution can be obtained in cases where standard unconstrained variational algorithms fail. Since variational algorithms can use standard Trotter steps as part of the optimization, allowing additional correlations that obey all the symmetries of the Hamiltonian will speed convergence of variational algorithms. This will lead to faster convergence than standard projection algorithms. Subjects: Quantum Physics (quant-ph) Report number: LA-UR-25-29124 Cite as: arXiv:2510.06702 [quant-ph] (or arXiv:2510.06702v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2510.06702 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Ivana Miháliková [view email] [v1] Wed, 8 Oct 2025 06:54:31 UTC (503 KB) Full-text links: Access Paper: View a PDF of the paper titled State preparation and symmetries, by Ivana Mih\'alikov\'a and 3 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2025-10 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?) Links to Code Toggle Papers with Code (What is Papers with Code?) 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?)