QAOA Parameter Transfer for Hypergraphs
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Quantum Physics arXiv:2604.26040 (quant-ph) [Submitted on 28 Apr 2026] Title:QAOA Parameter Transfer for Hypergraphs Authors:Lucas T. Braydwood, Phillip C. Lotshaw View a PDF of the paper titled QAOA Parameter Transfer for Hypergraphs, by Lucas T. Braydwood and Phillip C. Lotshaw View PDF HTML (experimental) Abstract:Variational Quantum Algorithms, including the Quantum Approximate Optimization Algorithm (QAOA), have shown promise in solving optimization problems but rely on costly variational loops that can themselves be hard optimization problems. Many methods have been proposed to mitigate this variational cost, with one of the most common being parameter transfer and concentration where variational parameters for one problem instance or for an average over problem instances can be used as a good set of parameters for another instance. Methods exist for reweighting these parameters based off graph degree and edge weights, but there has been little work on how to do this reweighting to handle higher locality problems where the graph structure turns into a hypergraph structure. In this paper, we analytically derive parameter reweighting rules to transfer parameters between different locality hypergraphs, resulting in a reweighting for the mixing terms in the Hamiltonian which have previously not been considered. These analytics rely on three cycle-free and low-circuit-depth assumptions, but numerics indicate that the results can be used even when these assumptions are not satisfied. The numerics obtain high quality results across a diverse set of hypergraphs with locality less than or equal to five, improving on previous relations that do not reweight the mixing terms. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2604.26040 [quant-ph] (or arXiv:2604.26040v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2604.26040 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Lucas Braydwood [view email] [v1] Tue, 28 Apr 2026 18:23:29 UTC (105 KB) Full-text links: Access Paper: View a PDF of the paper titled QAOA Parameter Transfer for Hypergraphs, by Lucas T. Braydwood and Phillip C. LotshawView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-04 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?)