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 …
Optical neural networks: progress and challenges
Artificial intelligence has prevailed in all trades and professions due to the assistance of big
data resources, advanced algorithms, and high-performance electronic hardware. However …
data resources, advanced algorithms, and high-performance electronic hardware. However …
Photonic multiplexing techniques for neuromorphic computing
The simultaneous advances in artificial neural networks and photonic integration
technologies have spurred extensive research in optical computing and optical neural …
technologies have spurred extensive research in optical computing and optical neural …
Computing primitive of fully VCSEL-based all-optical spiking neural network for supervised learning and pattern classification
S **ang, Z Ren, Z Song, Y Zhang, X Guo… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
We propose computing primitive for an all-optical spiking neural network (SNN) based on
vertical-cavity surface-emitting lasers (VCSELs) for supervised learning by using biologically …
vertical-cavity surface-emitting lasers (VCSELs) for supervised learning by using biologically …
Integrated neuromorphic photonics: synapses, neurons, and neural networks
Ever‐growing demands of bandwidth, computing speed, and power consumption are now
accelerating the transformation of computing research, as work‐at‐home becomes a new …
accelerating the transformation of computing research, as work‐at‐home becomes a new …
Hardware-algorithm collaborative computing with photonic spiking neuron chip based on an integrated Fabry–Perot laser with a saturable absorber
Photonic neuromorphic computing has emerged as a promising approach to building a low-
latency and energy-efficient non-von Neuman computing system. A photonic spiking neural …
latency and energy-efficient non-von Neuman computing system. A photonic spiking neural …
Photonic spiking neural networks and graphene-on-silicon spiking neurons
Spiking neural networks are known to be superior over artificial neural networks for their
computational power efficiency and noise robustness. The benefits of spiking coupled with …
computational power efficiency and noise robustness. The benefits of spiking coupled with …
Adaptive sigmoid-like and PReLU activation functions for all-optical perceptron
We present an approach for the generation of an adaptive sigmoid-like and PReLU
nonlinear activation function of an all-optical perceptron, exploiting the bistability of an …
nonlinear activation function of an all-optical perceptron, exploiting the bistability of an …
Photonic neuromorphic information processing and reservoir computing
Photonic neuromorphic computing is attracting tremendous research interest now, catalyzed
in no small part by the rise of deep learning in many applications. In this paper, we will …
in no small part by the rise of deep learning in many applications. In this paper, we will …
Optoelectronic Coincidence Detection with Two‐Dimensional Bi2O2Se Ferroelectric Field‐Effect Transistors
JM Yan, JS Ying, MY Yan, ZC Wang… - Advanced Functional …, 2021 - Wiley Online Library
Abstract Information processing with optoelectronic devices provides an alternative way to
efficiently process hybrid optical and electronic signals. Ferroelectric field‐effect transistors …
efficiently process hybrid optical and electronic signals. Ferroelectric field‐effect transistors …