Artificial intelligence tasks across numerous applications require accelerators for fast and
low-power execution. Optical computing systems may be able to meet these domain-specific …

Recent years have seen the rapid growth and development of the field of smart photonics,
where machine-learning algorithms are being matched to optical systems to add new …

Complex-valued neural networks have many advantages over their real-valued
counterparts. Conventional digital electronic computing platforms are incapable of executing …

Abstract Machine learning technologies have been extensively applied in high-performance
information-processing fields. However, the computation rate of existing hardware is …

The simultaneous advances in artificial neural networks and photonic integration
technologies have spurred extensive research in optical computing and optical neural …

Artificial intelligence (AI) is gaining strength, and materials science can both contribute to
and profit from it. In a simultaneous progress race, new materials, systems, and processes …

Recent advances in silicon photonic chips have made huge progress in optical computing
owing to their flexibility in the reconfiguration of various tasks. Its deployment of neural …

The rapid development of artificial intelligence (AI) facilitates various applications from all
areas but also poses great challenges in its hardware implementation in terms of speed and …

Programmable photonic circuits of reconfigurable interferometers can be used to implement
arbitrary operations on optical modes, providing a flexible platform for accelerating tasks in …

Programmable optical circuits are an important tool in develo** quantum technologies
such as transceivers for quantum communication and integrated photonic chips for quantum …