{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T19:07:16Z","timestamp":1789758436330,"version":"4.0.1"},"reference-count":52,"publisher":"American Association for the Advancement of Science (AAAS)","issue":"38","license":[{"start":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T00:00:00Z","timestamp":1789689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.science.org\/content\/page\/science-licenses-journal-article-reuse"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1846273"],"award-info":[{"award-number":["1846273"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1918549"],"award-info":[{"award-number":["1918549"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006502","name":"Defense Sciences Office, DARPA","doi-asserted-by":"publisher","award":["D23AP00158"],"award-info":[{"award-number":["D23AP00158"]}],"id":[{"id":"10.13039\/100006502","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017437","name":"NASA Headquarters","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100017437","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100021086","name":"NTT Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100021086","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100028261","name":"Quad Fellowship","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100028261","id-type":"DOI","asserted-by":"publisher"}]},{"name":"ARO","award":["W911NF-23-1-0048"],"award-info":[{"award-number":["W911NF-23-1-0048"]}]},{"name":"Center for Sensing to Intelligence at Caltech"}],"content-domain":{"domain":["www.science.org"],"crossmark-restriction":true},"short-container-title":["Sci. Adv."],"published-print":{"date-parts":[[2026,9,18]]},"abstract":"<jats:p>Over the past decade, deep learning has led to disruptive advancements with key applications in computer vision, natural language processing, and predictive analytics. With the increasing prevalence and adoption of deep learning algorithms, the quest for hardware solutions that can efficiently process data in real time with high speeds and low latencies has come to the forefront of research. On-chip photonic neural networks offer a promising platform that leverage high bandwidths and low propagation losses associated with light to perform analog deep learning computations. However, nanophotonic circuits are yet to achieve the required linear and nonlinear operations simultaneously in an all-optical and ultrafast fashion. Here, we report a high-speed photonic integrated circuit (PIC)\u2013based reservoir computer using an optical parametric oscillator (OPO) fabricated on thin-film lithium niobate. We apply the PIC-based OPO computing system for a variety of benchmark tasks including chaotic time series prediction, nonlinear error correction in a noisy communication channel, and noisy waveform classification, achieving &gt;93% accuracies at an operating clock rate of \u223c10\u00a0gigahertz in all cases. Our OPO network can allow for subnanosecond latencies when implemented in an end-to-end all-optical fashion, a timescale that is shorter than a single clock cycle in state-of-the-art digital electronic processors. By circumventing the need for optical-electronic-optical conversions, our high-speed PIC-based reservoir system paves the way for the next generation of compact, energy-efficient, all-optical neural networks with ultralow latencies.<\/jats:p>","DOI":"10.1126\/sciadv.aeb3077","type":"journal-article","created":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T18:04:04Z","timestamp":1789754644000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":0,"title":["High-speed reservoir computing using photonic integrated circuit optical parametric oscillators"],"prefix":"10.1126","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2100-5671","authenticated-orcid":true,"given":"Midya","family":"Parto","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA."},{"name":"Physics and Informatics Laboratories, NTT Research Inc., Sunnyvale, CA 94085, USA."},{"name":"CREOL, The College of Optics and Photonics, University of Central Florida, Orlando, FL 32816, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8184-4915","authenticated-orcid":true,"given":"Gordon H. Y.","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Applied Physics, California Institute of Technology, Pasadena, CA 91125, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6135-8581","authenticated-orcid":true,"given":"Ryoto","family":"Sekine","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5980-8774","authenticated-orcid":true,"given":"Robert M.","family":"Gray","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0365-1672","authenticated-orcid":true,"given":"Luis L.","family":"Ledezma","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9073-5745","authenticated-orcid":true,"given":"James","family":"Williams","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5659-8388","authenticated-orcid":true,"given":"Arkadev","family":"Roy","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0470-0050","authenticated-orcid":true,"given":"Alireza","family":"Marandi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA."},{"name":"Department of Applied Physics, California Institute of Technology, Pasadena, CA 91125, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"e_1_3_2_3_2","unstructured":"A. Vaswani N. Shazeer N. Parmar J. Uszkoreit L. Jones A. N. Gomez \u0141. Kaiser I. Polosukhin \u201cAttention is all you need \u201d in Advances in Neural Information Processing Systems (NIPS 2017). p. 30."},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03819-2"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06747-5"},{"key":"e_1_3_2_6_2","doi-asserted-by":"crossref","unstructured":"J. Sevilla L. Heim A. Ho T. Besiroglu M. Hobbhahn P. Villalobos \u201cCompute trends across three eras of machine learning \u201d in 2022 International Joint Conference on Neural Networks (IJCNN) (International Joint Conference on Neural Networks 2022) pp. 1\u20138.","DOI":"10.1109\/IJCNN55064.2022.9891914"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2973-6"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41566-020-00754-y"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1038\/s42254-023-00645-5"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1364\/OE.20.003241"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1364\/OPTICA.506635"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-022-04714-0"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06558-8"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.ade8450"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-024-07078-9"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-94952-5"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-55172-3"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1038\/nphoton.2017.93"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41566-023-01330-w"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41566-023-01233-w"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-1157-8"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-03070-1"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.adi9127"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1515\/nanoph-2022-0137"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-04223-6"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1364\/OPTICA.456108"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.adh4920"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-51509-0"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-42289-0"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41566-025-01753-7"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0469(1963)020<0130:DNF>2.0.CO;2"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.267326"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.1091277"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1364\/OPTICA.2.000438"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1364\/OPTICA.489501"},{"key":"e_1_3_2_36_2","first-page":"851","article-title":"Deep learning in bioinformatics","volume":"18","author":"Min S.","year":"2017","unstructured":"S. Min, B. Lee, S. Yoon, Deep learning in bioinformatics. Brief. Bioinform. 18, 851\u2013869 (2017).","journal-title":"Brief. Bioinform."},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41566-023-01313-x"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.abm4470"},{"key":"e_1_3_2_39_2","unstructured":"G. H. Y. Li M. Parto J. Ge Q.-X. Ji M. Gao Y. Yu J. Williams R. M. Gray C. R. Leefmans N. Englebert K. J. Vahala A. Marandi All-optical computing with beyond 100-GHz clock rates. arXiv:2501.05756 [physics.optics] (2025)."},{"key":"e_1_3_2_40_2","unstructured":"G. H. Y. Li \u201cUltrafast computing with nonlinear photonics \u201d thesis California Institute of Technology (2025)."},{"key":"e_1_3_2_41_2","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.adf9711"},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.35848\/1347-4065\/ab8d4f"},{"key":"e_1_3_2_43_2","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms2368"},{"key":"e_1_3_2_44_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature23011"},{"key":"e_1_3_2_45_2","doi-asserted-by":"publisher","DOI":"10.1038\/s44172-022-00021-8"},{"key":"e_1_3_2_46_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-92257-1"},{"key":"e_1_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.abh0693"},{"key":"e_1_3_2_48_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-1901-0"},{"key":"e_1_3_2_49_2","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.3793-14.2015"},{"key":"e_1_3_2_50_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-024-07687-4"},{"key":"e_1_3_2_51_2","first-page":"041037","article-title":"Large-scale optical reservoir computing for spatiotemporal chaotic systems prediction","volume":"10","author":"Rafayelyan M.","year":"2020","unstructured":"M. Rafayelyan, J. Dong, Y. Tan, F. Krzakala, S. Gigan, Large-scale optical reservoir computing for spatiotemporal chaotic systems prediction. Phys. Rev. X 10, 041037 (2020).","journal-title":"Phys. Rev. X"},{"key":"e_1_3_2_52_2","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2023.3342775"},{"key":"e_1_3_2_53_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2017.2747758"}],"container-title":["Science Advances"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.science.org\/doi\/pdf\/10.1126\/sciadv.aeb3077","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/www.science.org\/doi\/pdf\/10.1126\/sciadv.aeb3077","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T18:06:42Z","timestamp":1789754802000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.science.org\/doi\/10.1126\/sciadv.aeb3077"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,18]]},"references-count":52,"journal-issue":{"issue":"38","published-print":{"date-parts":[[2026,9,18]]}},"alternative-id":["10.1126\/sciadv.aeb3077"],"URL":"https:\/\/doi.org\/10.1126\/sciadv.aeb3077","relation":{},"ISSN":["2375-2548"],"issn-type":[{"value":"2375-2548","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,18]]},"assertion":[{"value":"2025-08-12","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-07","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"eaeb3077"}}