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A small microring array that performs large complex-valued matrix-vector multiplication.

Junwei Cheng1, Yuhe Zhao1, Wenkai Zhang1

  • 1Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, 430074, China.

Frontiers of Optoelectronics
|January 13, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel photonic chip for complex-valued matrix-vector multiplication, enabling advanced computations in artificial intelligence and signal processing. The technology extends beyond real-valued operations, paving the way for more powerful optical computing accelerators.

Keywords:
Complex-valued computingMicroring arrayPhotonic matrix–vector multiplicationSignal/image processing

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Area of Science:

  • Photonics
  • Optical Computing
  • Artificial Intelligence

Background:

  • Photonic matrix-vector multiplication is crucial for neural networks and signal processing.
  • Conventional methods are limited to real-valued operations, hindering complex-valued applications like discrete Fourier transform.

Purpose of the Study:

  • To develop a systematic solution for complex-valued matrix computation using microring arrays.
  • To extend photonic matrix computation from small-scale to large-scale applications.

Main Methods:

  • Utilizing matrix decomposition and matrix partition techniques.
  • Implementing a photonic complex matrix-vector multiplier chip based on microring arrays.

Main Results:

  • Demonstrated support for arbitrary large-scale and complex-valued matrix computation.
  • Successfully performed Walsh-Hardmard transform, discrete cosine transform, discrete Fourier transform, and image convolutional processing.
  • Showcased a path to overcome limitations of complex-valued accelerators in incoherent optical architectures.

Conclusions:

  • The proposed integrated photonic platform holds significant potential for large-scale, complex-valued artificial intelligence computing and signal processing.
  • This work advances the capabilities of optical computing for sophisticated computational tasks.