2018.5.4-5.10 学术活动预告
2018/5/3 10:24:56 中国科学院数学与系统科学研究院
Speaker:
Professor Franck Sueur, University of Bordeaux, France
Title:
Point vortex dynamics as zero-radius limit of the motion of a rigid body in an irrotational fluid
Time & Venue:
2018.5.4 9:30-11:30 N913
Abstract:
The point vortex system is usually considered as an idealized model where the vorticity of an ideal incompressible two-dimensional fluid is concentrated in a finite number of moving points. In this talk I will present a result obtained in collaboration with O. Glass and A. Munnier which establish that point vortex dynamics can also be obtained as zero-radius limit of the motion of a rigid body in an irrotational fluid.
Title:
一些含有旋度的非线性方程组
Time & Venue:
2018.5.4 10:30-11:30 N913
Abstract:
我们将介绍含有旋度的一些非线性偏微分方程组，包括拟线性Maxwell方程组及Maxwell-Stokes方程组。我们介绍这些系统的物理背景及数学上的难点、介绍边值问题的可解性及解的正则性的一些近年的结果。我们将看到，对于这类方程组的边值问题，解的存在性既依赖于方程的非线性特性，也依赖于边界条件的类型，且常常依赖于区域拓扑。我们还将介绍一些我们未能解决的问题。
Speaker:
Professor Frederic Marbach, University of Rennes, France
Title:
Controllability despite boundary layers
Time & Venue:
2018.5.4 15:00-17:00 N913
Abstract:
Controllability is the question of whether one can find a source-term (the control) to drive the solution of an evolution equation from a given initial state to a prescribed final state. In this lecture, we will study the question of controllability in small time for systems coming from fluid mechanics (Burgers, Navier-Stokes). I will explain why answering this question implies understanding the behavior of boundary layers. Several usual techniques will be used: asymptotic expansions, Coron's return method, energy estimates (Sobolev or analytic). I will also explain a recent technique to build controls that enhance the dissipation of the involved boundary layers.
Speaker:
Jiahua Chen, Department of Statistics, University of British Columbia, BC, Canada
Title:
Density ratio model and empirical likelihood
Time & Venue:
2018.5.4 16:00-17:00 N913
Abstract:
Assuming a model in a statistical application is to impose a distribution family on the data to be analyzed. When a parametric family is assumed, there are often many easy-to-use standard data analysis methods. However, in some applications, the inference conclusions can be heavily dependent on the parametric model assumption and the role of the data is uncomfortably low. Assuming a non-parametric model leaves the inference heavily dependent on data sometime heavily the noisy aspect. The density ratio model overcomes these drawbacks when multiple samples are available.
It connects several population distributions with a semi-parametric structure to avoid strong model assumption while taking the relationship between the populations into consideration. In addition, it permits effective inference procedures through empirical likelihood. In this talk, we provide two examples where properties of the density ratio model under empirical likelihood are profitably explored and superior statistical procedures are obtained.
Speaker:
Sug Woo Shin, Berkeley University
Title:
Endoscopy and cohomology of U(n-1,1)
Time & Venue:
2018.5.9 16:30-17:30 N913
Abstract:
We apply the endoscopic classification of automorphic representations for inner forms of unitary groups to bound the growth of cohomology in congruence towers of locally symmetric spaces associated with U(n-1,1). Our bound is sharper than the bound predicted by Sarnak-Xue for general locally symmetric spaces. This is joint work with Simon Marshall.
来源：中国科学院数学与系统科学研究院
中国科学院数学与系统科学研究院
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