Artificial Neural Networks (ANNs) are transforming how we understand chemical mixtures,
providing an expressive view of the chemical space and multiscale processes. Their …

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

Calibrating the phase in integrated optical phased arrays (OPAs) is a crucial procedure for
addressing phase errors and achieving the desired beamforming results. In this paper, we …

Recent years have witnessed growing research interest in dual-wavelength mode-locked
fiber lasers for their pivotal role in diverse applications and the exploration of nonlinear …

Neural-network-based reconstruction of digital holograms can improve the speed and the
quality of micro-and macro-object images, as well as reduce the noise and suppress the twin …

We present a novel implementation of conditional long short-term memory recurrent neural
networks that successfully predict the spectral evolution of a pulse in nonlinear periodically …

Photonic neural networks (PNNs) have emerged as a promising platform to address the
energy consumption issue that comes with the advancement of artificial intelligence …

Fibre lasers are distinct in that their optical train is decoupled from the environment,
especially in the all-fibre format. The attractive side of this decoupling is the simplicity of …

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

Due to the presence of air turbulence in free-space optical (FSO) links, random fluctuations
in wavefront phase and amplitude of the optical signal are reduced after it propagates …