We provide a perspective on the fundamental relationship between physics and
computation, exploring the conditions under which a physical system can be harnessed for …

We demonstrate a silicon photonic Xbar-based general matrix multiplier (Xbar GeMM) for
optical neural network (NN) applications, utilizing a hybrid time-space multiplexing scheme …

This paper introduces an opto-electronic and opto-electronic-opto circuit capable of
generating a Sigmoid shaped non-linear activation function (NLAF) for photonic neural …

We provide a perspective on the fundamental relationship between physics and
computation, exploring the conditions under which a physical system can be harnessed for …

Energy efficiency of electronic digital processors is primarily limited by the energy
consumption of electronic communication and interconnects. The industry is almost …

We experimentally demonstrate a novel time-space-wavelength multiplexed AWGR-based
photonic tensor multiplier that provides a total computational power of 163.8 TeraOP …

The recent explosive compute growth, mainly fueled by the boost of artificial intelligence (AI)
and deep neural networks (DNNs), is currently instigating the demand for a novel computing …