Quantum Approach for Market Basket Analysis on Qudit Systems

Quantum Approach for Market Basket Analysis on Qudit Systems | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Quantum Approach for Market Basket Analysis on Qudit Systems Semi O. Ceylan, Sait Can Yücebaş This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8269117/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Quantum computing consists of a set of techniques based on the principles of quantum mechanics. Historically, quantum computing has been built around qubit systems featuring two discrete levels. However, qudit systems involving multiple levels appear to provide a promising solutions to certain difficulties related to noise and information capacity in quantum computing. This study investigate these advantages by extending the quantum approaches of market basket analysis (MBA) on qudit systems. Furthermore, we propose a novel method utilising an adaptive comparator that requires fewer quantum resources in assessing the minimum support threshold, made possible by qudit systems. The proposed quantum MBA method was simulated on an 8-level system for a database containing 9 items and 64 transactions. The experiment results show that the proposed method can perform MBA on the same database using 78,125% less quantum resources compared to existing methods. All simulations conducted in this study utilize the Cirq framework. Quantum Computing Qudit Systems Market Basket Analysis Grover Search Algorithm Dicke States Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 18 May, 2026 Reviews received at journal 25 Mar, 2026 Reviews received at journal 20 Mar, 2026 Reviewers agreed at journal 04 Mar, 2026 Reviewers agreed at journal 28 Feb, 2026 Reviewers invited by journal 27 Feb, 2026 Editor assigned by journal 19 Feb, 2026 Submission checks completed at journal 03 Dec, 2025 First submitted to journal 03 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8269117","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":598686876,"identity":"d76229af-ae44-422c-b1c8-a4a56cc53c34","order_by":0,"name":"Semi O. 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