Thursdays in 901 Van Vleck Hall at 2:25 PM, unless otherwise noted. If you would like to receive announcements about upcoming seminars, please visit this page to sign up for the email list.
Thursday, September 15, Jun Yin, University of Wisconsin - Madison
Some recent results on random matrices with almost independent entries.
In this talk, we are going to introduce some recent work on a large class of random matrices, whose entries are (almost) independent. For example, the Wigner matrix, generalized Wigner matrix, Band random matrix, Covariance matrix and Sparse random matrix. We mainly focus on the local statistics of the eigenvalues and eigenvectors of these random matrix ensembles. We will also introduce some applications of these results and some long-standing open questions.
Thursday, September 22, Philip Matchett Wood, University of Wisconsin - Madison
Survey of the Circular Law
What do the eigenvalues of a random matrix look like? This talk will focus on large square matrices where the entries are independent, identically distributed random variables. In the most basic case, the distribution of the eigenvalues in the complex plane (suitably scaled) approaches the uniform distribution on the unit disk, which is called the circular law. We will discuss some of the methods that have been used to prove the circular law, including recent work that has extended the circular law to the most general situation, and we will also discuss generalizations to situations where the eigenvalue distributions are stable, but non-circular.
Thursday, September 29, Antonio Auffinger, University of Chicago
A simplified proof of the relation between scaling exponents in first passage percolation
In first passage percolation, we place i.i.d. non-negative weights on the nearest-neighbor edges of Z^d and study the induced random metric. A long-standing conjecture gives a relation between two "scaling exponents": one describes the variance of the distance between two points and the other describes the transversal fluctuations of optimizing paths between the same points. In a recent breakthrough work, Sourav Chatterjee proved a version of this conjecture using a strong definition of the exponents. I will discuss work I just completed with Michael Damron, in which we introduce a new and intuitive idea that replaces Chatterjee's main argument and gives an alternative proof of the scaling relation. One advantage of our argument is that it does not require a non-trivial technical assumption of Chatterjee on the weight distribution.
Tuesday, October 4, 2:30 PM, VV901, Gregorio Moreno Flores, University of Wisconsin - Madison
Airy process and the polymer end point distribution
We give an explicit formula for the joint density of the max and argmax of the Airy process minus a parabola. The argmax has a universal distribution which governs the rescaled endpoint of directed polymers in 1+1 dimensions.
Thursday, October 13, No seminar because of the MIDWEST PROBABILITY COLLOQUIUM
Thursday, October 20, Kay Kirkpatrick, University of Illinois at Urbana-Champaign
Thursday, October 27, No seminar this week
Monday, October 31, 2:30pm, Ankit Gupta, Ecole Polytechnique, Centre de Mathematiques Appliqees
Modeling adaptive dynamics for structured populations with functional traits
We develop the framework of adaptive dynamics for populations that are structured by age and functional traits. The functional trait of an individual may express itself differently during the life of an individual according to her age and a random parameter that is chosen at birth to capture the environmental stochasticity. The population evolves through birth, death and selection mechanisms. At each birth, the new individual may be a clone of its parent or a mutant. Starting from an individual based model we use averaging techniques to take the large population and rare mutation limit under a well-chosen time-scale separation. This gives us the Trait Substitution Sequence process that describes the adaptive dynamics in our setting. Assuming small mutation steps we also derive the Canonical Equation which expresses the evolution of advantageous traits as a function-valued ordinary differential equation.
This is joint work with J.A.J Metz (Leiden University) and V.C. Tran (University of Lille).
Friday, November 4, 2:30pm, Michael Cranston, University of California, Irvine
Thursday, November 10, David Anderson, University of Wisconsin - Madison
== Thursday, November 24, No seminar because of THANKSGIVING ==