Benchmarking the ORCA PT-2 Boson Sampler using Minimum Dominating Set Problems
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Quantum Physics arXiv:2605.30935 (quant-ph) [Submitted on 29 May 2026] Title:Benchmarking the ORCA PT-2 Boson Sampler using Minimum Dominating Set Problems Authors:Jessica Park, Susan Stepney, Irene D'Amico View a PDF of the paper titled Benchmarking the ORCA PT-2 Boson Sampler using Minimum Dominating Set Problems, by Jessica Park and 1 other authors View PDF HTML (experimental) Abstract:We use boson sampling as part of a gradient-free variational algorithm (the Binary Bosonic Solver) to solve a minimum dominating set problem and compare these results to a number of exact and heuristic classical algorithms. The boson sampling has been performed on the physical PT-2 time-bin interferometer from ORCA Computing. The PT-2 device has been tested here using both a single- and double-loop configuration and the results are compared based on the best found solution and the overall run time. With the parameters used in this experiment, the boson sampler is outperformed by the classical methods, but we hypothesise that this is due to insufficient samples and iterations. We classically simulate boson sampling in a single-loop configuration to break down the runtime for individual algorithmic components, allowing for estimates of when boson sampling may outperform classical methods. This study recommends a watching brief on boson sampling as the complexity of the interferometer is improved and the loss in the hardware is reduced allowing for better performance from the associated algorithms. Subjects: Quantum Physics (quant-ph); Emerging Technologies (cs.ET) Cite as: arXiv:2605.30935 [quant-ph] (or arXiv:2605.30935v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2605.30935 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Jessica Park [view email] [v1] Fri, 29 May 2026 07:24:19 UTC (1,675 KB) Full-text links: Access Paper: View a PDF of the paper titled Benchmarking the ORCA PT-2 Boson Sampler using Minimum Dominating Set Problems, by Jessica Park and 1 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-05 Change to browse by: cs cs.ET 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?)