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Express"],"published-print":{"date-parts":[[2026,2,9]]},"abstract":"<jats:p>\n                    All-optical computing offers ultra-high speed, low-power consumption, and parallel processing capabilities, crucial for overcoming Moore's Law limitations. However, conventional single-wavelength diffractive deep neural networks (D\n                    <jats:sup>2<\/jats:sup>\n                    NN) face significant challenges in achieving synergistic optimization between high-precision optical edge-feature extraction and classification tasks. Here, an edge-detecting spin-differential diffractive neural network (ESD-DNN) is proposed for single-wavelength all-optical object classification. The network architecture is implemented through a Pancharatnam-Berry phase gradient metasurface to achieve rapid edge-feature extraction, while classification inference is accomplished by utilizing a spin-differential mechanism based on left-\/right-handed circularly polarized (LCP\/RCP) components. Through end-to-end optimization of the diffractive layers, the ESD-DNN achieves co-optimization of edge-feature extraction and classification, significantly improving accuracy while reducing computational costs. Numerical validations reveal that the single-layer ESD-DNN attains 97.5% (MNIST) and 87.5% (Fashion-MNIST) classification accuracy, surpassing traditional single-wavelength D\n                    <jats:sup>2<\/jats:sup>\n                    NN by 10.2% and 5.2%, respectively. Meanwhile, it achieves 5-fold higher computational efficiency while reducing time complexity by 80% compared to a four-layer D\n                    <jats:sup>2<\/jats:sup>\n                    NN. Remarkably, under extreme conditions such as moderate turbulence intensity or thermal lensing effects, the network maintains &gt;90% classification accuracy (MNIST), demonstrating its exceptional environmental robustness. These findings pave the way for applications in artificial intelligence, satellite remote sensing, intelligent industrial inspection, and space optical communications.\n                  <\/jats:p>","DOI":"10.1364\/oe.579508","type":"journal-article","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T06:00:11Z","timestamp":1768197611000},"page":"3494","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["All-optical object classification using an edge-detecting spin-differential diffractive network"],"prefix":"10.1364","volume":"34","author":[{"given":"Yetao","family":"Shu","sequence":"first","affiliation":[{"name":"China Academy of Engineering Physics"},{"name":"Nanjing University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9345-5992","authenticated-orcid":true,"given":"Laixi","family":"Sun","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhai","family":"Li","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tong","family":"Fu","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yubin","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong","family":"Wu","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0695-2291","authenticated-orcid":true,"given":"Wenhua","family":"Gu","sequence":"additional","affiliation":[{"name":"Nanjing University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Li","sequence":"additional","affiliation":[{"name":"Nanjing University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Wang","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodong","family":"Yuan","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2026,1,26]]},"reference":[{"key":"oe-34-3-3494-R1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1364\/OL.2.000001","type":"journal-article","volume":"2","author":"Goodman","year":"1978","journal-title":"Opt. 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