Neural Networks in Optical Communications and Optical Computing: Implementation, Applications, and Prospects

Dear Colleagues,

In recent years, the convergence of artificial intelligence and photonic technologies has opened new frontiers in the design, optimization, and control of optical networks. Neural networks are increasingly being leveraged to enhance network performance and automate management. Meanwhile, photonic neural networks, built upon the inherent advantages of ultrafast and energy-efficient photonic computing, are emerging as a promising paradigm for real-time signal processing and intelligent decision-making directly in the optical domain. This Special Issue aims to provide a platform for researchers to share their latest advances, experimental demonstrations, and theoretical developments in the integration of neural networks and photonic technologies for optical networking. Contributions addressing innovative architectures, algorithms, devices, and applications are particularly encouraged. Topics of interest include, but are not limited to, the following:

• AI-driven optical network control, optimization, and management;
• Neural network-based fault diagnosis and performance prediction;
• Photonic neural networks for high-speed signal processing;
• Optical computing and machine learning accelerators;
• Hybrid electronic–photonic architectures for intelligent communications;
• Learning-based optical network design and resource allocation;
• Hardware implementations and experimental demonstrations;
• Emerging trends in intelligent, self-adaptive optical networks.

Articles, perspectives, and reviews are all welcome.

Dr. Zhiqun Gu
Dr. Ruikun Wang
Dr. Qiaolun Zhang
Guest Editors

Manuscript Submission Information

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