光纤参数放大器中的脉冲传播建模仿真数据

数据由西南交通大学于2021年9月产生，该成果通过商用光子仿真VPI对光纤进行仿真产生数据驱动由Python构建的脉冲传输长短记忆神经网络，实现对光脉冲在光纤传输场快速建模。最后， Matlab对数据进行做图处理。支撑论文“Modeling pulse propagation in fiber optical parametric amplifier by a long short-term memory network”以及“Physics-based deep learning for modeling nonlinear pulse propagation in optical fibers”The dataset was generated by Southwest Jiaotong University in September 2021. This work obtained simulation data of optical fibers via the commercial photonic simulation platform VPI, then developed a data-driven long short-term memory (LSTM) neural network for pulse transmission using Python, which enables rapid modeling of optical pulse propagation in fiber transmission fields. Finally, Matlab was utilized for plotting and post-processing the dataset. This dataset supports two academic papers: "Modeling pulse propagation in fiber optical parametric amplifier by a long short-term memory network" and "Physics-based deep learning for modeling nonlinear pulse propagation in optical fibers"

搜集汇总

背景与挑战

背景概述

该数据集由西南交通大学于2021年9月生成，通过VPI仿真和Python构建的长短记忆神经网络，模拟光脉冲在光纤参数放大器中的传播过程。数据用于支撑非线性脉冲传播建模的相关研究论文，并以MATLAB等格式进行后处理。