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Ultracompact meta-imagers for arbitrary all-optical convolution.

Weiwei Fu1, Dong Zhao1, Ziqin Li1

  • 1Department of Optics and Optical Engineering, University of Science and Technology of China, Hefei, Anhui, 230026, China.

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Summary
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This study introduces a novel all-optical convolutional computing method using a metasurface imager. This approach offers functionality-unlimited kernels for high-speed, low-loss analog convolutions, overcoming limitations of electronic and existing optical methods.

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Area of Science:

  • Optics
  • Artificial Intelligence
  • Metamaterials

Background:

  • Electronic convolutions are slow and energy-intensive.
  • Existing all-optical methods have limited functionality or are bulky.

Purpose of the Study:

  • To develop a new all-optical convolutional computing approach.
  • To enable functionality-unlimited kernels for analog convolutions.

Main Methods:

  • Utilizing a metasurface-singlet or -doublet imager.
  • Modifying the point spread function with a complex-amplitude meta-modulator.

Main Results:

  • Demonstrated real-time, parallel, analog convolutional processing.
  • Successfully performed spatial differentiation, pepper-salt denoising, and edge enhancement.

Conclusions:

  • The metasurface imager offers multi-functionality and high integration for all-optical convolutions.
  • This approach is compatible with digital convolutional neural networks.