First Photon Machine Learning

First Photon Machine Learning | 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 First Photon Machine Learning Lili Li, Santosh Kumar, Malvika Garikapati, Yuping Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7236336/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Quantum techniques are expected to revolutionize how information is acquired, exchanged, and processed. Yet it has been a challenge to realize and measure their value in practical settings. We present first photon machine learning as a new paradigm of neural networks and establish the first unambiguous advantage of quantum effects for artificial intelligence. By extending the physics behind the double-slit experiment for quantum particles to a many-slit version, our experiment finds that a single photon can perform image recognition at around $30%$ fidelity, which beats by a large margin the theoretical limit of what a similar classical system can possibly achieve (about 24%). In this experiment, without count the energy consumed for drive spatial light modulators, the entire neural network is implemented in sub-attojoule optics and the equivalent per-calculation energy cost is below $10^{-24}$ joule, highlighting the prospects of quantum optical machine learning for unparalleled advantages in speed, capacity, and energy efficiency. Physical sciences/Optics and photonics Physical sciences/Physics Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-7236336","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":502139672,"identity":"a71a8d24-5922-4ffa-a32b-a490c59ecb87","order_by":0,"name":"Lili Li","email":"","orcid":"","institution":"Stevens Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"Li","suffix":""},{"id":502139673,"identity":"0a508997-a544-4da8-aecd-02f0e26c6b5e","order_by":1,"name":"Santosh Kumar","email":"","orcid":"","institution":"Stevens Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Santosh","middleName":"","lastName":"Kumar","suffix":""},{"id":502139674,"identity":"30dc73bf-a8ba-4ff5-8bc7-5a4ac96bdf3c","order_by":2,"name":"Malvika Garikapati","email":"","orcid":"","institution":"Quantum computing inc","correspondingAuthor":false,"prefix":"","firstName":"Malvika","middleName":"","lastName":"Garikapati","suffix":""},{"id":502139675,"identity":"be66b06a-f931-47b2-ac35-223944b36e1c","order_by":3,"name":"Yuping Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYDACCTD5Tw5JKIEoLQeMGdhI1ZLYQLQWg9s9hp8Lft1Jnz+/+ZjExx11DPzsOQb4tdw5Yyw9s+9Z7oZjbGmSM88cZpDseUNAy40cA2neHubcDWw8xsa8bQfAIoS0GP8GakmXb+P/bPy3rY7BnggtZtI8Pw4nMBzjYXzM2MbMYCBBQIvkjbQya96GNMMNx9IMH/a2HeaROPOsAK8WvhvJm2/z/LGRl28+/ODAz7Y6Of725A14tSgcABKMbQgBHrzKQUC+AUT+IahuFIyCUTAKRjIAANFWSfoPRRYnAAAAAElFTkSuQmCC","orcid":"","institution":"Stevens Institute of Technology","correspondingAuthor":true,"prefix":"","firstName":"Yuping","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2025-07-28 17:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7236336/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7236336/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95526111,"identity":"eed11a5d-1471-41b1-a5fd-9ed852636dbe","added_by":"auto","created_at":"2025-11-10 10:06:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":551457,"visible":true,"origin":"","legend":"","description":"","filename":"FirstPhotonMachineLearningM.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7236336/v1_covered_77396729-ce71-4508-9b51-7145cabf1a0d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"First Photon Machine Learning","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7236336/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7236336/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Quantum techniques are expected to revolutionize how information is acquired, exchanged, and processed. 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