Photonic matrix multiplication lights up photonic accelerator and beyond
Matrix computation, as a fundamental building block of information processing in science
and technology, contributes most of the computational overheads in modern signal …
and technology, contributes most of the computational overheads in modern signal …
Artificial intelligence in meta-optics
Recent years have witnessed promising artificial intelligence (AI) applications in many
disciplines, including optics, engineering, medicine, economics, and education. In particular …
disciplines, including optics, engineering, medicine, economics, and education. In particular …
Experimentally realized in situ backpropagation for deep learning in photonic neural networks
Integrated photonic neural networks provide a promising platform for energy-efficient, high-
throughput machine learning with extensive scientific and commercial applications. Photonic …
throughput machine learning with extensive scientific and commercial applications. Photonic …
An optical neural chip for implementing complex-valued neural network
Complex-valued neural networks have many advantages over their real-valued
counterparts. Conventional digital electronic computing platforms are incapable of executing …
counterparts. Conventional digital electronic computing platforms are incapable of executing …
Photonics for artificial intelligence and neuromorphic computing
Research in photonic computing has flourished due to the proliferation of optoelectronic
components on photonic integration platforms. Photonic integrated circuits have enabled …
components on photonic integration platforms. Photonic integrated circuits have enabled …
Inference in artificial intelligence with deep optics and photonics
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 …
low-power execution. Optical computing systems may be able to meet these domain-specific …
Deep learning for the design of photonic structures
Innovative approaches and tools play an important role in shaping design, characterization
and optimization for the field of photonics. As a subset of machine learning that learns …
and optimization for the field of photonics. As a subset of machine learning that learns …
Programmable surface plasmonic neural networks for microwave detection and processing
A range of alternative approaches to traditional digital hardware have been explored for the
implementation of artificial neural networks, including optical neural networks and diffractive …
implementation of artificial neural networks, including optical neural networks and diffractive …
Prospects and applications of photonic neural networks
C Huang, VJ Sorger, M Miscuglio… - … in Physics: X, 2022 - Taylor & Francis
Neural networks have enabled applications in artificial intelligence through machine
learning, and neuromorphic computing. Software implementations of neural networks on …
learning, and neuromorphic computing. Software implementations of neural networks on …
Photonic machine learning with on-chip diffractive optics
Abstract Machine learning technologies have been extensively applied in high-performance
information-processing fields. However, the computation rate of existing hardware is …
information-processing fields. However, the computation rate of existing hardware is …