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 …

We show using numerical simulations that data driven discovery using sparse regression
can be used to extract the governing differential equation model of ideal four-wave mixing in …

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 …

The nonlinear evolution of ultrashort pulses in optical fiber has broad applications, but the
computational burden of convolutional numerical solutions necessitates rapid modeling …

A high-accuracy, high-speed, and low-cost M^ 2 factor estimation method for few-mode
fibers based on a shallow neural network is presented in this work. Benefiting from the …

The ultrashort pulse evolution in fiber optical parametric amplifier (FOPA) systems is a highly
complex nonlinear dynamic. Here, the long short-term memory network (LSTM) is applied to …

With a great ability to solve regression problems, the artificial neural network has become a
powerful tool to facilitate advancing ultrafast laser research. In this contribution, we …

We deploy a supervised machine-learning model based on a neural network to predict the
temporal and spectral reshaping of a simple sinusoidal modulation into a pulse train having …

摘要常规数值求解方法在表征光纤中超短脉冲的非线性传输过程时存在计算量大,
效率低等局限. 随着人工智能的快速发展, 深度学习技术展现出了强大的计算能力 …