[2309.04120] Boltzmann sampling with quantum annealers via fast Stein correction Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Condensed Matter > Statistical Mechanics arXiv:2309.04120 (cond-mat) [Submitted on 8 Sep 2023] Title: Boltzmann sampling with quantum annealers via fast Stein correction Authors: Ryosuke Shibukawa , Ryo Tamura , Koji Tsuda View a PDF of the paper titled Boltzmann sampling with quantum annealers via fast Stein correction, by Ryosuke Shibukawa and Ryo Tamura and Koji Tsuda View PDF HTML (experimental) Abstract: Despite the attempts to apply a quantum annealer to Boltzmann sampling, it is still impossible to perform accurate sampling at arbitrary temperatures. Conventional distribution correction methods such as importance sampling and resampling cannot be applied, because the analytical expression of sampling distribution is unknown for a quantum annealer. Stein correction (Liu and Lee, 2017) can correct the samples by weighting without the knowledge of the sampling distribution, but the naive implementation requires the solution of a large-scale quadratic program, hampering usage in practical problems. In this letter, a fast and approximate method based on random feature map and exponentiated gradient updates is developed to compute the sample weights, and used to correct the samples generated by D-Wave quantum annealers. In benchmarking problems, it is observed that the residual error of thermal average calculations is reduced significantly. If combined with our method, quantum annealers may emerge as a viable alternative to long-established Markov chain Monte Carlo methods. Comments: 5 pages, 2 figures Subjects: Statistical Mechanics (cond-mat.stat-mech) ; Quantum Physics (quant-ph) Cite as: arXiv:2309.04120 [cond-mat.stat-mech] (or arXiv:2309.04120v1 [cond-mat.stat-mech] for this version) https://doi.org/10.48550/arXiv.2309.04120 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Physical Review Research 6, 043050 (2024) Related DOI : https://doi.org/10.1103/PhysRevResearch.6.043050 Focus to learn more DOI(s) linking to related resources Submission history From: Ryo Tamura [ view email ] [v1] Fri, 8 Sep 2023 04:47:10 UTC (404 KB) Full-text links: Access Paper: View a PDF of the paper titled Boltzmann sampling with quantum annealers via fast Stein correction, by Ryosuke Shibukawa and Ryo Tamura and Koji Tsuda View PDF HTML (experimental) TeX Source view license Current browse context: cond-mat.stat-mech < prev | next > new | recent | 2023-09 Change to browse by: cond-mat quant-ph References & Citations INSPIRE HEP 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