article published yes Gaurav Arya author William F. Li author Charles Roques-Carmes author e2e68fc9-6505-11ef-a541-eb4e72cc3e82 Marin Soljačić author Steven G. Johnson author Zin Lin author 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. American Chemical Society2024 eng end-to-endoptimizationmetasurfaceimagingcompressed sensing 2330-4022 2201.1234810.1021/acsphotonics.4c00259 yes 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>. 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. 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> 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> 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>. G. Arya, W.F. Li, C. Roques-Carmes, M. Soljačić, S.G. Johnson, Z. Lin, ACS Photonics (2024). 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. 216722026-04-09T09:10:41Z2026-04-27T09:23:04Z