报告名称：Complex dynamics on the one-dimensional quantum droplets via time piecewise PINNs

主讲人：陈 勇 教授

邀请人：黄丽丽 助理研究员

时间：2023年11月2日 16 : 30

地点：太阳成集团tyc234cc(中国)官方网站326会议室

主办单位：太阳成集团tyc234cc(中国)官方网站

报告摘要

In this work, we present a novel methodology, termed time piecewise physics-informed neural networks (PINNs), to study the intricate dynamics of one-dimensional quantum droplets by solving the amended GP equation. Our network model exhibits superior training performance in the long time domain compared to conventional PINNs, with each of its subnetwork operating independently and offering high adjustability. By employing time piecewise PINNs with scarce training points, we not only study intrinsic modulations of single droplet and collision between two droplets, but also excite the breather on droplet background. Intriguingly, we obtain an interference pattern from training result of collision between two droplets, which is a significant feature of the interplay of coherent matter waves. The numerical findings demonstrate that in a nonlinear non-integrable system, varying parameters can result in vastly different dynamic behaviors despite sharing the same initial conditions.

 

专家简介

陈勇，华东师范大学，博士生导师，计算机理论所所长，上海市闵行区拔尖人才。长期从事非线性数学物理、可积系统、计算机代数及程序开发、可积深度学习算法，混沌理论、大气和海洋动力学等领域的研究工作。提出了一系列可以机械化实现非线性方程求解的方法，发展了李群理论并成功应用于大气海洋物理模型的研究.提出可积深度学习算法，开发出一系列可机械化实现的非线性发展方程的研究程序。已在SCI收录的国际学术期刊上发表SCI论文300余篇，引用7000余篇次。主持国家自然科学基金面上项目4项，国家自然科学基金重点项目2项(第一参加人和项目负责人)、973项目1项(骨干科学家)、国家自然科学基金长江创新团队项目2项(PI)。