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Express"],"published-print":{"date-parts":[[2026,10,5]]},"abstract":"<jats:p>\n                    In this work, we present a photonic classification architecture based on a Kerr microresonator operating as a nonlinear reservoir. The system exploits chaotic optical frequency comb formation in a high-\n                    <jats:italic>Q<\/jats:italic>\n                    microresonator to transform time-encoded input signals into high-dimensional spectral representations. Using the QR-compressed MNIST handwritten digit dataset, we numerically demonstrate that the proposed architecture improves classification accuracy from 71.67% to 83.88% compared with a purely linear baseline, even when only a small subset of input features is used. We further analyze the influence of key resonator parameters on classification performance. These results highlight the potential of nonlinear microresonator-based frequency comb reservoirs as compact photonic processors for machine-learning tasks with low footprint and simple readout.\n                  <\/jats:p>","DOI":"10.1364\/oe.604117","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T05:00:08Z","timestamp":1789534808000},"page":"37924","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Image classification using spectral features from a Kerr comb photonic reservoir computer"],"prefix":"10.1364","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-3122-4644","authenticated-orcid":true,"given":"Negar","family":"Shaabani Shishavan","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05j0ve876","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5722-0122","authenticated-orcid":true,"given":"Egor","family":"Manuylovich","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05j0ve876","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Morteza","family":"Kamalian-Kopae","sequence":"additional","affiliation":[{"name":"Microsoft Azure Fibre"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Auro M.","family":"Perego","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05j0ve876","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2026,9,29]]},"reference":[{"key":"oe-34-20-37924-R1","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1038\/s42254-023-00645-5","type":"journal-article","volume":"5","author":"McMahon","year":"2023","journal-title":"Nat. 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Further distribution of this work must maintain attribution to the author(s) and the published article\u2019s title, journal citation, and DOI.","name":"copyright","label":"Copyright"}]}}