In recent years, machine learning, especially various deep neural networks, as an emerging
technique for data analysis and processing, has brought novel insights into the development …

Owing to their compactness, robustness, low cost, high stability, and diffraction-limited beam
quality, mode-locked fiber lasers play an indispensable role in micro/nanomanufacturing …

The estimation of the quality of transmission (QoT) in optical systems with machine learning
(ML) has recently been the focus of a large body of research. We discuss the sources of …

The tandem neural network with a modified loss function is used to inversely design the
nanophotonic device from a desired spectrum, to obtain the corresponding structural …

Optical communication systems, operating in C-band, are reaching their theoretically
achievable capacity limits. An attractive and economically viable solution to satisfy the future …

A wide variety of laser applications, that often require radiation with specific characteristics,
and relative flexibility of laser configurations offer a prospect of designing systems with the …

In this paper, we show that by combining experimental data from different optical fibers, we
can build a fiber-agnostic neural-network to model the Raman amplifier. The fiber-agnostic …

As a crucial nonlinear phenomenon, stimulated Raman scattering (SRS) plays multifaceted
roles involved in forward and inverse problems. In fibre-optic systems, these roles range …

Optical transmission systems with high spectral efficiency require accurate quality of
transmission estimation for optical channel provisioning. However, the wavelength …

By associating machine learning and an analytical model (ie, the Gaussian noise model),
we reduce uncertainties on the output power profile and the noise figure of each amplifier in …