This tutorial–review on applications of artificial neural networks in photonics targets a broad
audience, ranging from optical research and engineering communities to computer science …

Optical communication systems represent the backbone of modern communication
networks. Since their deployment, different fiber technologies have been used to deal with …

In long-haul optical communication systems, compensating nonlinear effects through digital
signal processing (DSP) is difficult due to intractable interactions between Kerr nonlinearity …

We propose a new machine-learning approach for fiber-optic communication systems
whose signal propagation is governed by the nonlinear Schrödinger equation (NLSE). Our …

In this paper, we review the historical evolution of predictions of the performance of optical
communication systems. We will describe how such predictions were made from the outset …

We investigate the application of dynamic deep neural networks for nonlinear equalization
in long haul transmission systems. Through extensive numerical analysis we identify their …

We explore the potential benefits of digital nonlinearity compensation (NLC) techniques in
fully loaded coherent wavelength-division multiplexed (WDM) transmission systems. After …

In this work, a new data-driven fiber channel modeling method, generative adversarial
network (GAN) is investigated to learn the distribution of fiber channel transfer function. Our …

This work proposes a probabilistic shaping scheme for optical WDM systems, where
nonlinear interference noise depends on the input optical signal power distribution. With …

Next-generation optical communication systems will continue to push the (bandwidth·
distance) product towards its physical limit. To address this enormous demand, the usage of …