High precision reconstruction of silicon photonics chaos with stacked CNN-LSTM neural networks

Author:

Cheng Wei12,Feng Junbo3,Wang Yan12,Peng Zheng12,Cheng Hao1,Ren Xiaodong1,Shuai Yubei1,Zang Shengyin1,Liu Hao1,Pu Xun4,Yang Junbo2,Wu Jiagui5ORCID

Affiliation:

1. College of Artificial Intelligence, Southwest University, Chongqing 400715, China

2. Center of Material Science, National University of Defense Technology, Changsha 410073, China

3. United Microelectronics Center Co., Ltd, Chongqing 401332, China

4. College of Computer & Information Science, Southwest University, Chongqing 400715, China

5. School of Physical Science and Technology, Southwest University, Chongqing 400715, China

Abstract

Silicon-based optical chaos has many advantages, such as compatibility with complementary metal oxide semiconductor (CMOS) integration processes, ultra-small size, and high bandwidth. Generally, it is challenging to reconstruct chaos accurately because of its initial sensitivity and high complexity. Here, a stacked convolutional neural network (CNN)-long short-term memory (LSTM) neural network model is proposed to reconstruct optical chaos with high accuracy. Our network model combines the advantages of both CNN and LSTM modules. Further, a theoretical model of integrated silicon photonics micro-cavity is introduced to generate chaotic time series for use in chaotic reconstruction experiments. Accordingly, we reconstructed the one-dimensional, two-dimensional, and three-dimensional chaos. The experimental results show that our model outperforms the LSTM, gated recurrent unit (GRU), and CNN models in terms of MSE, MAE, and R-squared metrics. For example, the proposed model has the best value of this metric, with a maximum improvement of 83.29% and 49.66%. Furthermore, 1D, 2D, and 3D chaos were all significantly improved with the reconstruction tasks.

Funder

National Natural Science Foundation of China

Chongqing Science Funds for Distinguished Young Scientists

Chongqing Postdoctoral Science Foundation Special Funded project

Program for New Century Excellent Talents in University

Guangxi Key Laboratory of Cryptography and Information Security

Hunan Provincial Natural Science Foundation of China

China Postdoctoral Science Foundation

Foundation of NUDT

the Fundamental Research Funds for the Central Universities

Ph.D. Fund of Southwest University

Publisher

AIP Publishing

Subject

Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

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