All-optical complex field imaging using diffractive processors

Jingxi Li; Yuhang Li; Tianyi Gan; Che-Yung Shen; Mona Jarrahi; Aydogan Ozcan

doi:10.1038/s41377-024-01482-6

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All-optical complex field imaging using diffractive processors

Original Articles

- All-optical complex field imaging using diffractive processors
- Light: Science & Applications Vol. 13, Issue 6, Pages: 1122-1139(2024)
- Affiliations：
  
  1.Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095, USA
  2.Bioengineering Department, University of California, Los Angeles, CA 90095, USA
  3.California NanoSystems Institute (CNSI), University of California, Los Angeles, CA 90095, USA
- Author bio：
  
  Aydogan Ozcan (ozcan@ucla.edu)
- Funds：
- DOI：10.1038/s41377-024-01482-6
  CLC：
- Received：29 January 2024，
  
  Revised：2024-05-11，
  
  Accepted：13 May 2024，
  
  Published Online：28 May 2024，
  
  Published：30 June 2024
- Accepted：
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Li, J. X. et al. All-optical complex field imaging using diffractive processors., Light: Science & Applications, 13, 1122-1139 (2024).
DOI：

Li, J. X. et al. All-optical complex field imaging using diffractive processors., Light: Science & Applications, 13, 1122-1139 (2024). DOI： 10.1038/s41377-024-01482-6.

摘要

Abstract

Complex field imaging

which captures both the amplitude and phase information of input optical fields or objects

can offer rich structural insights into samples

such as their absorption and refractive index distributions. However

conventional image sensors are intensity-based and inherently lack the capability to directly measure the phase distribution of a field. This limitation can be overcome using interferometric or holographic methods

often supplemented by iterative phase retrieval algorithms

leading to a considerable increase in hardware complexity and computational demand. Here

we present a complex field imager design that enables snapshot imaging of both the amplitude and quantitative phase information of input fields using an intensity-based sensor array without any digital processing. Our design utilizes successive deep learning-optimized diffractive surfaces that are structured to collectively modulate the input complex field

forming two independent imaging channels that perform amplitude-to-amplitude and phase-to-intensity transformations between the input and output planes within a compact optical design

axially spanning ~100 wavelengths. The intensity distributions of the output fields at these two channels on the sensor plane directly correspond to the amplitude and quantitative phase profiles of the input complex field

eliminating the need for any digital image reconstruction algorithms. We experimentally validated the efficacy of our complex field diffractive imager designs through 3D-printed prototypes operating at the terahertz spectrum

with the output amplitude and phase channel images closely aligning with our numerical simulations. We envision that this complex field imager will have various applications in security

biomedical imaging

sensing and material science

among others.

关键词

Keywords

references

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