学术报告

学术报告

您当前所在位置: 首页 > 学术报告 > 正文
报告时间 2022年9月22日(周四);下午14:00—15:30 报告地点 腾讯会议ID:515481730
报告人 赵世舜

学术沙龙主题:Calculation of high-order harmonic generation of atoms and molecules by combining timeseries prediction and neural networks

报告人:赵世舜 吉林大学 教授

https://teachers.jlu.edu.cn/__local/D/37/2B/FF30C9550E26695BE28E06EB6B7_504C84D3_217A.jpg

报告时间:2022年9月22日(周四);下午14:00—15:30

报告地点:腾讯会议ID:515481730

报告人简介:赵世舜,教授,吉林大学数学学院,吉林大学获得博士学位,师从于史宁中教授。于2013年-2014年在美国密苏里大学做访问学者,近年来一直从事生存分析、多元统计以及大数据方向的研究。在国内外名杂志已发表论文SCI论文20余篇,包括区间删失的研究、相依区间删失的研究以及特征选择方向的研究。作为项目负责人主持国家自然科学面上项目2项,教育部科研项目1项,省自然科学基金2项。作为主要参加人参加国家自然科学基金项目3项。

报告摘要:High-order harmonic generation (HHG) from the interaction of ultra-intense laser pulses with atoms is an important tabletop short-wave coherent light source. Accurate quantum simulations of it present large computational difficulties due to multi-electron multidimensional effects. In this paper, the time-dependent response of hydrogen atoms is calculated using a time-series prediction scheme, the HHG spectrum is reconstructed very accurately. The accuracy of the forecasting is further improved by using a neural network scheme. This scheme is also applied to the simulation of the harmonic emission on multi-electron systems, and the applicability of the scheme is confirmed by the harmonic calculation of complex systems. This method is expected to simulate the nonlinear dynamic process of multi-electron atoms and molecules irradiated by intense laser pulses quickly and accurately.

上一篇:计算数学及其交叉学科前沿系列讲座报告

下一篇:Comparison theorems on resistance distances of S,T-isomers and its applications

关闭

Baidu
sogou