Numerical methods using and for interacting particle systems

发布时间:2022年11月11日 作者:王小捷   阅读次数:[]

报告题目:Numerical methods using and for interacting particle systems

报告人:李磊 上海交通大学

报告时间:2022年11月14日 10:00-12:40

报告地点:腾讯会议 960 293 673

报告摘要: I will give a brief introduction to our recent works regarding the applications of interacting particle systems in scientific computing. In the first part, I will talk about several algorithms we proposed for sampling and solving PDEs using interacting particle systems, which can be efficiently implemented with the random batch approximation. In particular, the random batch Monte Carlo method, the random batch Ewald method and a particle method for PNP equation will be talked about. The second part goes to the fluctuation suppression and enhancement phenomena in interacting particle systems, which may give some evidence why sampling based on particle systems may be preferred sometimes.

李磊,上海交通大学自然科学研究院和数学科学学院教授,入选海外高层次人才青年项目,2010年本科毕业于清华大学,2015年博士毕业于威斯康星大学麦迪逊分校(UW-Madison)。他的研究方向是数值分析与科学计算(包括 random algorithms for particle systems, numerical SDEs and PDEs,machine learning); 应用分析(包括time fractional differential equations, PDE models, optimal transport)等,主持重点研发青年科学家项目,国家自然科学基金面上项目等科研项目,在研究领域取得重要的研究成果,在SIAM J. Numer. Anal., Math. Comp., SIAM J. Sci. Comput, J. Comput. Phys.等计算数学权威刊物发表40多篇论文。欢迎广大师生踊跃参加!



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