Constraint-oriented biased quantum search for linear constrained combinatorial optimization problems

Quantum Physics arXiv:2512.05205 (quant-ph) [Submitted on 4 Dec 2025] Title:Constraint-oriented biased quantum search for linear constrained combinatorial optimization problems Authors:Sören Wilkening, Timo Ziegler, Maximilian Hess View a PDF of the paper titled Constraint-oriented biased quantum search for linear constrained combinatorial optimization problems, by S\"oren Wilkening and Timo Ziegler and Maximilian Hess View PDF Abstract:In this paper, we extend a previously presented Grover-based heuristic to tackle general combinatorial optimization problems with linear constraints. We further describe the introduced method as a framework that enables performance improvements through circuit optimization and machine learning techniques. Comparisons with state-of-the-art classical solvers further demonstrate the algorithm's potential to achieve a quantum advantage in terms of speed, given appropriate quantum hardware. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2512.05205 [quant-ph] (or arXiv:2512.05205v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2512.05205 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Sören Wilkening [view email] [v1] Thu, 4 Dec 2025 19:21:36 UTC (1,767 KB) Full-text links: Access Paper: View a PDF of the paper titled Constraint-oriented biased quantum search for linear constrained combinatorial optimization problems, by S\"oren Wilkening and Timo Ziegler and Maximilian HessView PDFTeX Source view license Current browse context: quant-ph new | recent | 2025-12 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?)