QReach: A Reachability Analysis Tool for Quantum Markov Chains

Quantum Physics arXiv:2512.04497 (quant-ph) [Submitted on 4 Dec 2025] Title:QReach: A Reachability Analysis Tool for Quantum Markov Chains Authors:Aochu Dai, Mingsheng Ying View a PDF of the paper titled QReach: A Reachability Analysis Tool for Quantum Markov Chains, by Aochu Dai and Mingsheng Ying View PDF HTML (experimental) Abstract:We present QReach, the first reachability analysis tool for quantum Markov chains based on decision diagrams CFLOBDD (presented at CAV 2023). QReach provides a novel framework for finding reachable subspaces, as well as a series of model-checking subprocedures like image computation. Experiments indicate its practicality in verification of quantum circuits and algorithms. QReach is expected to play a central role in future quantum model checkers. Comments: Subjects: Quantum Physics (quant-ph); Logic in Computer Science (cs.LO) Cite as: arXiv:2512.04497 [quant-ph] (or arXiv:2512.04497v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2512.04497 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Journal reference: Computer Aided Verification (CAV 2024), LNCS 14683, 2024, pp. 520-532 Related DOI: https://doi.org/10.1007/978-3-031-65633-0_23 Focus to learn more DOI(s) linking to related resources Submission history From: Aochu Dai [view email] [v1] Thu, 4 Dec 2025 06:03:53 UTC (95 KB) Full-text links: Access Paper: View a PDF of the paper titled QReach: A Reachability Analysis Tool for Quantum Markov Chains, by Aochu Dai and Mingsheng YingView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2025-12 Change to browse by: cs cs.LO 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?)