Simultaneous temporal and spectral evolution of ultrafast optical pulse propagation using a single bidirectional LSTM network
GR Martins, LCB da Silva, MEV Segatto… - Optical Fiber …, 2024 - Elsevier
Numerical simulations of optical pulse evolution are often a cumbersome task, mostly due to
the presence of nonlinearities, and standard numerical approaches like splitting methods …
the presence of nonlinearities, and standard numerical approaches like splitting methods …
Enhanced bi-LSTM for Modeling Nonlinear Amplification Dynamics of Ultra-Short Optical Pulses
K Saraeva, A Bednyakova - Photonics, 2024 - mdpi.com
Fiber amplifiers are essential devices for optical communication and laser physics, yet the
intricate nonlinear dynamics they exhibit pose significant challenges for numerical modeling …
intricate nonlinear dynamics they exhibit pose significant challenges for numerical modeling …
Predicting nonlinear multi-pulse propagation in optical fibers via a lightweight convolutional neural network
H Sui, H Zhu, H Jia, Q Li, M Ou, B Luo, X Zou, L Yan - Optics Letters, 2023 - opg.optica.org
The nonlinear evolution of ultrashort pulses in optical fiber has broad applications, but the
computational burden of convolutional numerical solutions necessitates rapid modeling …
computational burden of convolutional numerical solutions necessitates rapid modeling …
Design and analysis of recurrent neural networks for ultrafast optical pulse nonlinear propagation
In this work, we analyze different types of recurrent neural networks (RNNs) working under
several different parameters to best model the nonlinear optical dynamics of pulse …
several different parameters to best model the nonlinear optical dynamics of pulse …
Predicting ultrafast nonlinear dynamics in fibre optics with a recurrent neural network
The propagation of ultrashort pulses in optical fibre plays a central role in the development
of light sources and photonic technologies, with applications from fundamental studies of …
of light sources and photonic technologies, with applications from fundamental studies of …
Physics-based deep learning for modeling nonlinear pulse propagation in optical fibers
A physics-based deep learning (DL) method termed Phynet is proposed for modeling the
nonlinear pulse propagation in optical fibers totally independent of the ground truth. The …
nonlinear pulse propagation in optical fibers totally independent of the ground truth. The …
Feed-forward neural network as nonlinear dynamics integrator for supercontinuum generation
The nonlinear propagation of ultrashort pulses in optical fibers depends sensitively on the
input pulse and fiber parameters. As a result, the optimization of propagation for specific …
input pulse and fiber parameters. As a result, the optimization of propagation for specific …
Optical computing with supercontinuum generation in photonic crystal fibers
We introduce a novel photonic neural network using photonic crystal fibers, leveraging
femtosecond pulse supercontinuum generation for optical computing. Investigating its …
femtosecond pulse supercontinuum generation for optical computing. Investigating its …
Deep learning based pulse prediction of nonlinear dynamics in fiber optics
The initial state of a nonlinear optical fiber system plays a vital role in the ultrafast pulse
evolution dynamic. In this work, a data-driven compressed convolutional neural network …
evolution dynamic. In this work, a data-driven compressed convolutional neural network …
Reusability report: Predicting spatiotemporal nonlinear dynamics in multimode fibre optics with a recurrent neural network
Results Temporal results. The datasets generated by the aforementioned TD-BPM contain
1,000 examples of spatiotemporal nonlinear propagation of femtosecond pulses (see …
1,000 examples of spatiotemporal nonlinear propagation of femtosecond pulses (see …