Influence of nonlinear node operating states on the performance of photonic reservoir computing

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Authors: Tong Zhao, Baofeng Feng, 崔天培, Zhimin Bai, Pengfa Chang, Lijun Qiao, Xiaopeng Fan
Cited by: 1
References: 32

Abstract

Photonic reservoir computing (PRC) has attracted significant attention in artificial intelligence and information processing owing to its advantages of high speed, low power consumption, and inherent parallelism. The operating state of the nonlinear node strongly influences the computational performance of the PRC, yet most existing studies rely almost exclusively on the traditional operating point located in the steady-state region before the Hopf bifurcation. In this work, we adopt a dual-delay optical feedback structure to create another bifurcation pathway in which the system can transition directly from the steady state toward a quasi-periodic regime, bypassing the periodic state. We compare the steady state located before this quasi-periodic bifurcation with the conventional pre-Hopf steady state, and analyze their respective impacts on reservoir performance. The results highlight the importance of selecting an appropriate operating state for specific tasks and provide new insights for nonlinear optimization in PRC systems.

Fields of Study & Subjects

Neural Networks and Reservoir Computing Advanced Memory and Neural Computing Photonic and Optical Devices

Publication details

Journal / source
Optics Express
Publisher
Optica Publishing Group
Volume
34
Issue
10
Pages
18690–18690
Publication date
6 May 2026
Language
EN