Simultaneous multiply-accumulate operations in optical computing by Jacobi time-wave packets

Simultaneous multiply-accumulate operations in optical computing by Jacobi time-wave packets | 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 Simultaneous multiply-accumulate operations in optical computing by Jacobi time-wave packets Thomas Schneider, Janosch Meier, Khaleda Mallik, Abhinand Venugopalan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7572267/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The increasing computational demands of artificial intelligence strain the speed and energy efficiency of electronic processors, particularly for multiply-accumulate (MAC) operations. Current photonic approaches face limitations in scalability and power consumption. Here we demonstrate that multiplexing orthogonal time-wave packets based on Jacobi polynomials enables simultaneous execution of multiple MAC operations within a single clock cycle. Experimentally, this method achieves real-time unscrambling of 2 GBd 6x6 MIMO signals and nonlinear optical vector processing for XOR and XNOR logic gates across multiple 10 GBd wavelength channels. This approach reduces processing steps and hardware complexity, offering a scalable and energy-efficient pathway for optical computing in large-scale neural networks. Our findings suggest that Jacobi polynomial time multiplexing can enhance the performance and integration density of photonic processors for AI applications. Physical sciences/Optics and photonics/Optical techniques Physical sciences/Optics and photonics/Applied optics/Integrated optics Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryOrthogonal.pdf Supplemental Material for: Simultaneous multiply-accumulate operations in optical computing by Jacobi time-wave packets Cite Share Download PDF Status: Under Review 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-7572267","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":512410015,"identity":"f4e5a351-10fd-41bd-95aa-95cca17f9729","order_by":0,"name":"Thomas 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