---
OA_place: repository
OA_type: green
_id: '21672'
abstract:
- lang: eng
  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.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Gaurav
  full_name: Arya, Gaurav
  last_name: Arya
- first_name: William F.
  full_name: Li, William F.
  last_name: Li
- first_name: Charles
  full_name: Roques-Carmes, Charles
  id: e2e68fc9-6505-11ef-a541-eb4e72cc3e82
  last_name: Roques-Carmes
- first_name: Marin
  full_name: Soljačić, Marin
  last_name: Soljačić
- first_name: Steven G.
  full_name: Johnson, Steven G.
  last_name: Johnson
- first_name: Zin
  full_name: Lin, Zin
  last_name: Lin
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>
  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>
  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>.
  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.
  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.
  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>.
  short: G. Arya, W.F. Li, C. Roques-Carmes, M. Soljačić, S.G. Johnson, Z. Lin, ACS
    Photonics (2024).
date_created: 2026-04-09T09:10:41Z
date_published: 2024-04-23T00:00:00Z
date_updated: 2026-04-27T09:23:04Z
day: '23'
ddc:
- '530'
doi: 10.1021/acsphotonics.4c00259
extern: '1'
external_id:
  arxiv:
  - '2201.12348'
keyword:
- end-to-end
- optimization
- metasurface
- imaging
- compressed sensing
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.48550/arXiv.2201.12348
month: '04'
oa: 1
oa_version: Preprint
publication: ACS Photonics
publication_identifier:
  eissn:
  - 2330-4022
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: End-to-end optimization of metasurfaces for imaging with compressed sensing
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
year: '2024'
...