A photonic integrated chip for distinguishing the optical wave packets based on a neural-network

Chu En Lin, Ya Fan Chen, Ching Pao Sun, Chii Chang Chen

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this work, we use an optical-neural network to recognize a series of optical triangular and square wave packets. This chip is designed based on the reservoir computing, consisting of the directional couplers, phase shifters, Mach-Zehnder modulators, spiral waveguide and grating couplers. The non-linear activation function is obtained by the directional couplers. The optimization of the optical reservoir computing system is performed by tuning the voltage on the phase shifters to obtain the largest extinction ratio of the output signals for different input wave packets. The photonic integrated chip is fabricated on silicon-on-insulator and is characterized at an operation frequency of 3 GHz. The results demonstrate that the photonic integrated chip can efficiently distinguish between optical triangular and square wave packets.

Original languageEnglish
Article number107982
JournalResults in Physics
Volume65
DOIs
StatePublished - Oct 2024

Keywords

  • Neural networks
  • pattern recognition
  • reservoir computing
  • silicon photonics
  • waveguide

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