Design of a photonic unitary neural network based on MZI arrays

• Autorzy: Zhang Ye , Wang Ruiting , Zhang Yejin , Su Yanmei , Wang Pengfei , Luo Guangzhen , Zhou Xuliang , Pan Jiaoqing

Identyfikatory

DOI

10.37190/oa240101

• Języki publikacji: EN

Abstrakty

EN

In recent years, optical neural networks have attracted widespread attention, due to their advantages of high speed, high parallelism, high bandwidth, and low power consumption. Photonic unitary neural network is a kind of neural networks that utilize the principles of unitary matrices and photonics to perform computations. In this paper, we design a photonic unitary neural network based on Mach–Zehnder interferometer arrays. The results show that the network has a good performance on both triangular and circular binary classification datasets, where most of the data points are correctly classified. The accuracies achieve 97% and 95% for triangular and circular datasets, with the loss function values of 0.023 and 0.046, respectively.

Słowa kluczowe

EN

optical neural network; unitary matrix; Mach-Zehnder interferometer

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2024
• Tom: Vol. 54, nr 1
• Strony: 5--13
• Opis fizyczny: Bibliogr. 31 poz., rys.

Twórcy

autor

Zhang Ye

• School of Automation, Beijing Information Science and Technology University, Beijing, China

autor

Wang Ruiting

• Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China
• College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China

autor

Zhang Yejin

• Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China
• College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China

autor

Su Yanmei

• Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China

autor

Wang Pengfei

• Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China
• College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China

autor

Luo Guangzhen

• Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China
• College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China

autor

Zhou Xuliang

• Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China
• College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China

autor

Pan Jiaoqing

• Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China
• College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).