{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T18:59:42Z","timestamp":1785437982217,"version":"3.56.0"},"reference-count":19,"publisher":"Optica Publishing Group","issue":"13","license":[{"start":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T00:00:00Z","timestamp":1782172800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/doi.org\/10.1364\/OA_License_v2#VOR"},{"start":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T00:00:00Z","timestamp":1782172800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/opg.optica.org\/policies\/opg-tdm-policy.json"}],"content-domain":{"domain":["opg.optica.org"],"crossmark-restriction":false},"short-container-title":["Opt. Lett."],"published-print":{"date-parts":[[2026,7,1]]},"abstract":"<jats:p>In this study, we propose and demonstrate a hardware-efficient photonic\n\t\t\t\t\tneural network processor utilizing low-rank approximation (LRA) in\n\t\t\t\t\tconjunction with mode-division multiplexing (MDM) techniques. By\n\t\t\t\t\texploiting MDM, the architecture requires only a single optical\n\t\t\t\t\tsource, substantially reducing the hardware complexity associated with\n\t\t\t\t\tmulti-source systems. Through LRA, the proposed architecture\n\t\t\t\t\tintegrates two single-mode Mach-Zehnder interferometers (MZIs) and\n\t\t\t\t\tfour mode-insensitive MZIs to construct a 4 \u00d7 2 matrix with the\n\t\t\t\t\trank of 1. Compared to previously photonic neural network processors\n\t\t\t\t\temploying MZIs or microring resonators (MRRs), our approach achieves a\n\t\t\t\t\t25% reduction in the number of optical components through LRA\n\t\t\t\t\tfor the 4 \u00d7 2 matrix configuration. Fabricated on an\n\t\t\t\t\t800\u2009nm silicon nitride platform, the MDM-enabled LRA photonic\n\t\t\t\t\tneural network processor was experimentally validated on a facial\n\t\t\t\t\texpression recognition task and achieved a prediction accuracy of\n\t\t\t\t\t96% on the MNIST dataset. Our work provides a scalable and\n\t\t\t\t\thardware-efficient pathway toward photonic matrix operations,\n\t\t\t\t\tparticularly well-suited for resource-constrained applications.<\/jats:p>","DOI":"10.1364\/ol.600453","type":"journal-article","created":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T12:00:09Z","timestamp":1780315209000},"page":"3589","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hardware-efficient photonic neural network processor by mode-division multiplexing"],"prefix":"10.1364","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8323-861X","authenticated-orcid":true,"given":"Weiwei","family":"Pan","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00a2xv884","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heng","family":"Chen","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00a2xv884","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Gong","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00a2xv884","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4321-5584","authenticated-orcid":true,"given":"Ruoyun","family":"Yao","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00a2xv884","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Ji","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00a2xv884","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2026,6,23]]},"reference":[{"key":"ol-51-13-3589-R1","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","type":"journal-article","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"ol-51-13-3589-R2","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.patcog.2017.10.013","type":"journal-article","volume":"77","author":"Gu","year":"2018","journal-title":"Pattern\n\t\t\t\t\tRecognit."},{"key":"ol-51-13-3589-R3","doi-asserted-by":"publisher","first-page":"3234","DOI":"10.1109\/TITS.2020.2993926","type":"journal-article","volume":"22","author":"Chen","year":"2021","journal-title":"IEEE Trans. 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All rights,\n\t\t\t\t\tincluding for text and data mining (TDM), Artificial Intelligence (AI)\n\t\t\t\t\ttraining, and similar technologies, are\n\t\t\t\t\treserved.","name":"copyright","label":"Copyright"}]}}