Integrated platforms and techniques for photonic neural networks
Neural networks (NNs) have been widely applied in computer vision, natural language processing, and beyond. As the miniaturization of semiconductor transistors nears its limits, thereby bringing Moore’s law to an end, photonic neural networks (PNNs), which leverage photons rather than electrons as information carriers, have emerged as promising hardware accelerators for NNs. PNNs offer ultrafast processing speed, ultra-low energy consumption, and extremely high throughput. Moreover, advances in photonic integrated circuits provide compact and reliable hardware platforms for constructing PNNs. Here, we provide an overview of recent advances in integrated PNN components, including linear and nonlinear operators based on diverse optical elements, as well as devices that enable optical fan-in and fan-out. We further summarize the development in on-chip PNN implementations and discuss the future challenges associated with their monolithic integration.
Authors
- Yuhang Song (ORCID: https://orcid.org/0000-0002-7999-0291)
- Xingyuan Xu
- Yunping Bai (ORCID: https://orcid.org/0000-0002-3747-8257)
- Kun Xu (ORCID: https://orcid.org/0000-0002-1663-9998)
- Chaoran Huang
- Shifan Chen (ORCID: https://orcid.org/0000-0001-7404-6456)
- Hongwei Chen (ORCID: https://orcid.org/0000-0002-2952-2203)
- Haoran Zhang (ORCID: https://orcid.org/0000-0002-7485-4549)
- Jian Wang (ORCID: https://orcid.org/0000-0001-5402-1219)
- David J. Moss
Institutions
- Beijing University of Posts and Telecommunications (CN)
- Chinese University of Hong Kong (HK)
- Wuhan National Laboratory for Optoelectronics (CN)
- Huazhong University of Science and Technology (CN)
- Swinburne University of Technology (AU)
- Tsinghua University (CN)
Publication Details
- Journal
- npj Nanophotonics
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1038/s44310-025-00088-z
- Citations
- 1
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- National Natural Science Foundation of China
- Beijing University of Posts and Telecommunications