Current

Probabilistic scaling & propagation of randomness under nonlinear dispersive flow

Abstract

In this talk we will first survey recent developments on the study of random data problems for nonlinear (dispersive) PDEs. Then we will explain how the "correct" scaling heuristics for the critical regularity of wellposedness works in the probabilistical context and how it opened the door to unveil the random structures of nonlinear waves as they propagate. This is joint work with Yu Deng (USC) and Andrea Nahmod (UMass Amherst).


Biography

岳海天,数学博士,2021年至今任教于上海科技大学数学研究所。2018年在美国马萨诸塞大学阿默斯特分校获得数学博士学位,2018-2021年在美国南加州大学进行博后工作。学术研究方向为非线性色散偏微分方程,目前主要关注非线性色散方程的随机初值问题和不变吉布斯测度问题。研究成果发表在包括《Annals of Mathematics》、《Inventiones Mathematicae》和《Communications in Mathematical Physics》等多个国际知名数学期刊上。