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Complex-valued matrix-vector multiplication using a scalable coherent photonic processor.

Yiwei Xie1, Xiyuan Ke1, Shihan Hong1

  • 1State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang Key Laboratory of Optoelectronic Information Technology, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310058, China.

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Summary
This summary is machine-generated.

We developed a 16-channel photonic processor for ultra-fast matrix-vector multiplication (MVM). This chip-scale device achieves 1.28 tera-operations per second, advancing photonic computing for AI and signal processing.

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Area of Science:

  • Photonics
  • Optical Computing
  • Artificial Intelligence

Background:

  • Matrix-vector multiplication (MVM) is crucial for signal processing and AI.
  • Photonic processors offer potential for higher speed and energy efficiency than electronic counterparts.
  • Existing photonic solutions face challenges in scalability and flexibility.

Purpose of the Study:

  • To propose and demonstrate a novel chip-scale coherent photonic matrix-vector multiplication processor (MVMP).
  • To achieve high-speed computation and functional flexibility for advanced applications.
  • To overcome limitations of current microelectronic and photonic computing approaches.

Main Methods:

  • Integration of a 16-channel programmable on-chip coherent photonic processor.
  • Utilization of low phase error Mach-Zehnder interferometers mesh.
  • Employment of ultralow-loss broadened photonic waveguide delay lines for amplitude and phase encoding.
  • Implementation of high-speed coherent detection.

Main Results:

  • Demonstration of complex-valued matrix-vector multiplication at 1.28 tera-operations per second (TOPS).
  • Achieved high flexibility for arbitrary matrix transformation, parallel image processing, and handwritten digit recognition.
  • Validated the advantages of low-loss and low phase error designs for scalability and functional flexibility.

Conclusions:

  • The proposed MVMP represents a substantial advancement in high-speed and large-scale photonic computing.
  • The integrated design enables significant improvements in computing speed and energy efficiency.
  • This technology holds promise for future AI and signal processing applications.