Boltzmann Sampling by Diabatic Quantum Annealing

[2409.18126] Boltzmann Sampling by Diabatic Quantum Annealing Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Condensed Matter > Statistical Mechanics arXiv:2409.18126 (cond-mat) [Submitted on 26 Sep 2024 ( v1 ), last revised 14 Apr 2026 (this version, v4)] Title: Boltzmann Sampling by Diabatic Quantum Annealing Authors: Ju-Yeon Gyhm , Gilhan Kim , Hyukjoon Kwon , Yongjoo Baek View a PDF of the paper titled Boltzmann Sampling by Diabatic Quantum Annealing, by Ju-Yeon Gyhm and 3 other authors View PDF HTML (experimental) Abstract: Boltzmann sampling is a central component of many computational frameworks, including numerous algorithms in machine learning. Although quantum annealers have been investigated as potential fast Boltzmann samplers, their dependence on environmental noise makes precise control of the effective temperature difficult, introducing uncertainty into the sampling process. As an alternative, we propose diabatic quantum annealing -- a faster, purely unitary process -- as a controllable Boltzmann sampler in which the effective temperature is determined by the annealing rate. Using the ferromagnetic Ising model and the Sherrington--Kirkpatrick model as test cases, we demonstrate that this method achieves rapid and accurate sampling in the high-temperature regime. Comments: 8 pages, 4 figures Subjects: Statistical Mechanics (cond-mat.stat-mech) Cite as: arXiv:2409.18126 [cond-mat.stat-mech] (or arXiv:2409.18126v4 [cond-mat.stat-mech] for this version) https://doi.org/10.48550/arXiv.2409.18126 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Yongjoo Baek [ view email ] [v1] Thu, 26 Sep 2024 17:59:12 UTC (2,298 KB) [v2] Thu, 20 Mar 2025 03:55:50 UTC (2,362 KB) [v3] Fri, 6 Jun 2025 14:38:46 UTC (430 KB) [v4] Tue, 14 Apr 2026 06:42:51 UTC (517 KB) Full-text links: Access Paper: View a PDF of the paper titled Boltzmann Sampling by Diabatic Quantum Annealing, by Ju-Yeon Gyhm and 3 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cond-mat.stat-mech < prev | next > new | recent | 2024-09 Change to browse by: cond-mat References & Citations NASA ADS Google 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? ) IArxiv recommender toggle IArxiv Recommender ( What is IArxiv? ) 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? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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