Ultrafast fibre lasers, characterized by ultrashort pulse duration and broad spectral
bandwidth, have drawn significant attention due to their vast potential across a wide range of …

A physics-informed neural network (PINN) is used to produce a variety of self-trapped
necklace solutions of the (2+ 1)-dimensional nonlinear Schrödinger/Gross-Pitaevskii …

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 …

Deep learning incorporating physics knowledge has become a powerful tool for studying the
dynamic behavior of high-dimensional nonlinear systems. In this paper, the two-stage mini …

Abstract Physics-Informed Neural Networks (PINNs) have established a strong track record
in addressing partial differential equations, catering to both predictive (forward) and …

Simulating the propagation of ultrashort pulses in optical fibers is vital for photonic
technologies such as laser design, high-speed telecommunications, and high-resolution …

Designing and optimizing optical amplifiers to maximize system performance is becoming
increasingly important as optical communication systems strive to increase throughput …

Artificial Intelligence (AI) is a disrupting technology, which has been changing our world.
Photonics is a well-established technology, encompassing the generation, emission …

PINN - Enabled Physical Parameter Identification for Accurate EDFA Gain Modeling Page 1
XXX-X-XXXX-XXXX-X/XX/$XX.00 ©20XX IEEE PINN-Enabled Physical Parameter Identification …

To solve the prediction deterioration in the scenario of the all-fiber electro-optical frequency
combs generation, we propose a modified physics-informed neural network for improved …