[{"intvolume":"        11","quality_controlled":"1","arxiv":1,"language":[{"iso":"eng"}],"date_created":"2026-03-30T12:22:47Z","oa_version":"Preprint","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","date_published":"2024-04-23T00:00:00Z","type":"journal_article","extern":"1","publication_status":"published","date_updated":"2026-04-27T09:03:21Z","article_type":"original","volume":11,"issue":"5","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2201.12348"}],"citation":{"chicago":"Arya, Gaurav, William F. Li, Charles Roques-Carmes, Marin Soljačić, Steven G. Johnson, and Zin Lin. “End-to-End Optimization of Metasurfaces for Imaging with Compressed Sensing.” <i>ACS Photonics</i>. American Chemical Society, 2024. <a href=\"https://doi.org/10.1021/acsphotonics.4c00259\">https://doi.org/10.1021/acsphotonics.4c00259</a>.","apa":"Arya, G., Li, W. F., Roques-Carmes, C., Soljačić, M., Johnson, S. G., &#38; Lin, Z. (2024). End-to-end optimization of metasurfaces for imaging with compressed sensing. <i>ACS Photonics</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acsphotonics.4c00259\">https://doi.org/10.1021/acsphotonics.4c00259</a>","mla":"Arya, Gaurav, et al. “End-to-End Optimization of Metasurfaces for Imaging with Compressed Sensing.” <i>ACS Photonics</i>, vol. 11, no. 5, American Chemical Society, 2024, pp. 2077–87, doi:<a href=\"https://doi.org/10.1021/acsphotonics.4c00259\">10.1021/acsphotonics.4c00259</a>.","ama":"Arya G, Li WF, Roques-Carmes C, Soljačić M, Johnson SG, Lin Z. End-to-end optimization of metasurfaces for imaging with compressed sensing. <i>ACS Photonics</i>. 2024;11(5):2077-2087. doi:<a href=\"https://doi.org/10.1021/acsphotonics.4c00259\">10.1021/acsphotonics.4c00259</a>","ista":"Arya G, Li WF, Roques-Carmes C, Soljačić M, Johnson SG, Lin Z. 2024. End-to-end optimization of metasurfaces for imaging with compressed sensing. ACS Photonics. 11(5), 2077–2087.","short":"G. Arya, W.F. Li, C. Roques-Carmes, M. Soljačić, S.G. Johnson, Z. Lin, ACS Photonics 11 (2024) 2077–2087.","ieee":"G. Arya, W. F. Li, C. Roques-Carmes, M. Soljačić, S. G. Johnson, and Z. Lin, “End-to-end optimization of metasurfaces for imaging with compressed sensing,” <i>ACS Photonics</i>, vol. 11, no. 5. American Chemical Society, pp. 2077–2087, 2024."},"page":"2077-2087","external_id":{"arxiv":["2201.12348"]},"scopus_import":"1","title":"End-to-end optimization of metasurfaces for imaging with compressed sensing","article_processing_charge":"No","oa":1,"month":"04","_id":"21528","status":"public","year":"2024","publication":"ACS Photonics","day":"23","publication_identifier":{"eissn":["2330-4022"]},"OA_place":"repository","doi":"10.1021/acsphotonics.4c00259","publisher":"American Chemical Society","fulldoi":"https://doi.org/10.1021/acsphotonics.4c00259","ddc":["530"],"author":[{"last_name":"Arya","full_name":"Arya, Gaurav","first_name":"Gaurav"},{"full_name":"Li, William F.","first_name":"William F.","last_name":"Li"},{"id":"e2e68fc9-6505-11ef-a541-eb4e72cc3e82","full_name":"Roques-Carmes, Charles","first_name":"Charles","last_name":"Roques-Carmes"},{"last_name":"Soljačić","first_name":"Marin","full_name":"Soljačić, Marin"},{"first_name":"Steven G.","full_name":"Johnson, Steven G.","last_name":"Johnson"},{"full_name":"Lin, Zin","first_name":"Zin","last_name":"Lin"}],"abstract":[{"text":"We present a framework for the end-to-end optimization of metasurface imaging systems that reconstruct targets using compressed sensing, a technique for solving underdetermined imaging problems when the target object exhibits sparsity (e.g., the object can be described by a small number of nonzero values, but the positions of these values are unknown). We nest an iterative, unapproximated compressed sensing reconstruction algorithm into our end-to-end optimization pipeline, resulting in an interpretable, data-efficient method for maximally leveraging metaoptics to exploit object sparsity. We apply our framework to super-resolution imaging and high-resolution depth imaging with a phase-change material. In both situations, our end-to-end framework effectively optimizes metasurface structures for compressed sensing recovery, automatically balancing a number of complicated design considerations to select an imaging measurement matrix from a complex, physically constrained manifold with millions of dimensions. The optimized metasurface imaging systems are robust to noise, significantly improving over random scattering surfaces and approaching the ideal compressed sensing performance of a Gaussian matrix, showing how a physical metasurface system can demonstrably approach the mathematical limits of compressed sensing.","lang":"eng"}],"keyword":["end-to-end","optimization","metasurface","imaging","compressed sensing"],"OA_type":"green"},{"publisher":"American Chemical Society","doi":"10.1021/acsphotonics.4c00259","OA_place":"repository","ddc":["530"],"fulldoi":"https://doi.org/10.1021/acsphotonics.4c00259","day":"23","publication_identifier":{"eissn":["2330-4022"]},"year":"2024","_id":"21672","month":"04","status":"public","publication":"ACS Photonics","title":"End-to-end optimization of metasurfaces for imaging with compressed sensing","scopus_import":"1","oa":1,"article_processing_charge":"No","OA_type":"green","keyword":["end-to-end","optimization","metasurface","imaging","compressed sensing"],"abstract":[{"text":"We present a framework for the end-to-end optimization of metasurface imaging systems that reconstruct targets using compressed sensing, a technique for solving underdetermined imaging problems when the target object exhibits sparsity (i.e. the object can be described by a small number of non-zero values, but the positions of these values are unknown). We nest an iterative, unapproximated compressed sensing reconstruction algorithm into our end-to-end optimization pipeline, resulting in an interpretable, data-efficient method for maximally leveraging metaoptics to exploit object sparsity. We apply our framework to super-resolution imaging and high-resolution depth imaging with a phase-change material. In both situations, our end-to-end framework computationally discovers optimal metasurface structures for compressed sensing recovery, automatically balancing a number of complicated design considerations to select an imaging measurement matrix from a complex, physically constrained manifold with millions ofdimensions. The optimized metasurface imaging systems are robust to noise, significantly improving over random scattering surfaces and approaching the ideal compressed sensing performance of a Gaussian matrix, showing how a physical metasurface system can demonstrably approach the mathematical limits of compressed sensing.","lang":"eng"}],"author":[{"last_name":"Arya","full_name":"Arya, Gaurav","first_name":"Gaurav"},{"full_name":"Li, William F.","first_name":"William F.","last_name":"Li"},{"first_name":"Charles","id":"e2e68fc9-6505-11ef-a541-eb4e72cc3e82","full_name":"Roques-Carmes, Charles","last_name":"Roques-Carmes"},{"last_name":"Soljačić","first_name":"Marin","full_name":"Soljačić, Marin"},{"last_name":"Johnson","first_name":"Steven G.","full_name":"Johnson, Steven G."},{"last_name":"Lin","first_name":"Zin","full_name":"Lin, Zin"}],"article_type":"original","publication_status":"published","extern":"1","date_updated":"2026-04-27T09:23:04Z","date_published":"2024-04-23T00:00:00Z","type":"journal_article","arxiv":1,"quality_controlled":"1","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","oa_version":"Preprint","date_created":"2026-04-09T09:10:41Z","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2201.12348"}],"external_id":{"arxiv":["2201.12348"]},"citation":{"ama":"Arya G, Li WF, Roques-Carmes C, Soljačić M, Johnson SG, Lin Z. End-to-end optimization of metasurfaces for imaging with compressed sensing. <i>ACS Photonics</i>. 2024. doi:<a href=\"https://doi.org/10.1021/acsphotonics.4c00259\">10.1021/acsphotonics.4c00259</a>","ista":"Arya G, Li WF, Roques-Carmes C, Soljačić M, Johnson SG, Lin Z. 2024. End-to-end optimization of metasurfaces for imaging with compressed sensing. ACS Photonics.","apa":"Arya, G., Li, W. F., Roques-Carmes, C., Soljačić, M., Johnson, S. G., &#38; Lin, Z. (2024). End-to-end optimization of metasurfaces for imaging with compressed sensing. <i>ACS Photonics</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acsphotonics.4c00259\">https://doi.org/10.1021/acsphotonics.4c00259</a>","mla":"Arya, Gaurav, et al. “End-to-End Optimization of Metasurfaces for Imaging with Compressed Sensing.” <i>ACS Photonics</i>, American Chemical Society, 2024, doi:<a href=\"https://doi.org/10.1021/acsphotonics.4c00259\">10.1021/acsphotonics.4c00259</a>.","ieee":"G. Arya, W. F. Li, C. Roques-Carmes, M. Soljačić, S. G. Johnson, and Z. Lin, “End-to-end optimization of metasurfaces for imaging with compressed sensing,” <i>ACS Photonics</i>. American Chemical Society, 2024.","short":"G. Arya, W.F. Li, C. Roques-Carmes, M. Soljačić, S.G. Johnson, Z. Lin, ACS Photonics (2024).","chicago":"Arya, Gaurav, William F. Li, Charles Roques-Carmes, Marin Soljačić, Steven G. Johnson, and Zin Lin. “End-to-End Optimization of Metasurfaces for Imaging with Compressed Sensing.” <i>ACS Photonics</i>. American Chemical Society, 2024. <a href=\"https://doi.org/10.1021/acsphotonics.4c00259\">https://doi.org/10.1021/acsphotonics.4c00259</a>."}}]