Entanglement detection with classical deep neural networks

Entanglement detection with classical deep neural networks | 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 Article Entanglement detection with classical deep neural networks Julio Ureña, Antonio Sojo, Jara Juana Bermejo-Vega, Daniel Manzano This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4257844/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract In this study, we introduce an autonomous method for addressing the detection and classification of quantum entanglement, a core element of quantum mechanics that has yet to be fully understood. We employ a multi-layer perceptron to effectively identify entanglement in both twoand three-qubit systems. Our technique yields impressive detection results, achieving nearly perfect accuracy for two-qubit systems and over 90% accuracy for three-qubit systems. Additionally, our approach successfully categorizes three-qubit entangled states into distinct groups with a success rate of up to 77%. These findings indicate the potential for our method to be applied to larger systems, paving the way for advancements in quantum information processing applications. Physical sciences/Physics/Quantum physics/Quantum information Physical sciences/Mathematics and computing/Computer science Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 05 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 10 Jun, 2024 Reviews received at journal 02 Jun, 2024 Reviews received at journal 31 May, 2024 Reviews received at journal 27 May, 2024 Reviewers agreed at journal 26 May, 2024 Reviewers agreed at journal 24 May, 2024 Reviewers agreed at journal 15 May, 2024 Reviewers invited by journal 15 May, 2024 Editor assigned by journal 15 May, 2024 Editor invited by journal 15 May, 2024 Submission checks completed at journal 15 May, 2024 First submitted to journal 12 Apr, 2024 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. 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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-4257844","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":304434752,"identity":"62f686b8-aeb8-4887-899b-0ec4283c8412","order_by":0,"name":"Julio Ureña","email":"","orcid":"","institution":"University of Valencia","correspondingAuthor":false,"prefix":"","firstName":"Julio","middleName":"","lastName":"Ureña","suffix":""},{"id":304434753,"identity":"caf04c82-5402-4709-bb7a-48c9f5603609","order_by":1,"name":"Antonio Sojo","email":"","orcid":"","institution":"University of Granada","correspondingAuthor":false,"prefix":"","firstName":"Antonio","middleName":"","lastName":"Sojo","suffix":""},{"id":304434754,"identity":"3cd77ed0-3a7f-4efb-9ab2-62e62e65e1ec","order_by":2,"name":"Jara Juana Bermejo-Vega","email":"","orcid":"","institution":"University of Granada","correspondingAuthor":false,"prefix":"","firstName":"Jara","middleName":"Juana","lastName":"Bermejo-Vega","suffix":""},{"id":304434756,"identity":"3afd26bd-e4bb-4225-89ac-10d08d2532d5","order_by":3,"name":"Daniel Manzano","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYBADOdK1GJOuJbGBaKW67WcPf/i5wya9X7r94ccvFfcYDM6vfcDw4Q9uLWZn8hIMe8+k5c6cc8ZYWuZMMYPBjecGjDPb8Gg5kGOQwNt2OHfDjRwGacm2BKCWYwzMvHjcaXb+jcHBv22H0w1upD/+LfkPquUPPofdyDFsBtqSYHAjwUzyYwNQy/k2BmYGNnxa3hgzy7alGc6ckWNmzXAsgUfyBhvDwV58fjmfY/zxbZuNPL9E+uObP2oS5PjOH2N88AOPw1AAMw8DAw+DRALDASI1MDAw/gCR/MRrGAWjYBSMgpEBAG6LVXRDAtyLAAAAAElFTkSuQmCC","orcid":"","institution":"University of Granada","correspondingAuthor":true,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Manzano","suffix":""}],"badges":[],"createdAt":"2024-04-12 12:42:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4257844/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4257844/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-68213-0","type":"published","date":"2024-08-05T15:57:43+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62298908,"identity":"cb858d4e-03b0-493f-8028-f1d2966205a9","added_by":"auto","created_at":"2024-08-12 16:17:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2521916,"visible":true,"origin":"","legend":"","description":"","filename":"v1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4257844/v1_covered_772b7f7a-baba-406e-87fa-e7698842fe27.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Entanglement detection with classical deep neural networks","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4257844/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4257844/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this study, we introduce an autonomous method for addressing the detection and classification of quantum entanglement, a core element of quantum mechanics that has yet to be fully understood. 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