Photonics and AI in Information Technologies
Artificial Intelligence (AI) has accelerated the development of information technologies (IT). Through deep learning from previous data, an AI system can predict future events and make decisions. Photonics has played an important role in AI, and AI can help facilitate the design of photonics components and systems. This special issue discusses the current status and future perspectives on photonics and AI in IT covering from materials science, device physics, to systems and applications, including matrix computation devices, nonlinear activation devices, bio-inspired photonic structures, AI for inverse design, reservoir computing systems, deep neural networks and machine learning architectures, LiDAR, robots, unmanned autonomous vehicles, drones, smart data centers, and intelligent communications and computing.
Topics covered include, but are not limited to:
- Artificial materials
- Artificial intelligence
- Inverse design
- Neuromorphic photonics
- Deep neural networks
- Machine learning
Qixiang Cheng, University of Cambridge
Madeleine Glick, Columbia University
Thomas Van Vaerenbergh, Hewlett Packard Labs
APL Photonics Editor
Yikai Su, Shanghai Jiao Tong University
Please note that papers will be published as normal when they are ready in a regular issue of the journal and will populate on a virtual collection page within a few days of publication. Inclusion in the collection will not cause delay in publication.
How to Submit:
- Please submit through the online submission system.
- Under manuscript type → select Article or Letter, as appropriate
- Under manuscript information → Title/Abstract → select “Invited Submission: No”.
- Under manuscript information → Manuscript classification → select “Photonics and AI in Information Technologies”