# Non-equilibrium Dynamics and Random Matrices (nedrm)

### On the Boltzmann equation without angular cut-off

Robert Strain
In this talk we will explain several results surrounding global stability problem for the Boltzmann equation 1872 with the physically important collision kernels derived by Maxwell 1867 for the full range of inverse power intermolecular potentials,...

### A rigorous result on many-body localization

I will discuss a proof of many-body localization for a one-dimensional spin chain with random local interactions. The proof depends on a physically reasonable assumption that limits the amount of level attraction in the system. This is joint work...

### The Brownian motion as the limit of a deterministic system of hard-spheres

Thierry Bodineau
We provide a derivation of the brownian motion as the hydrodynamic limit of a diluted deterministic system of hard-spheres (in the Boltzmann-Grad limit). We use the linear Boltzmann equation as an intermediate level of description for one tagged...

### The Sherrington-Kirkpatrick model and its diluted version II

Dmitry Panchenko
I will talk about two types of random processes -- the classical Sherrington-Kirkpatrick (SK) model of spin glasses and its diluted version. One of the main goals in these models is to find a formula for the maximum of the process, or the free...

### The Sherrington-Kirkpatrick model and its diluted version I

Dmitry Panchenko
I will talk about two types of random processes -- the classical Sherrington-Kirkpatrick (SK) model of spin glasses and its diluted version. One of the main goals in these models is to find a formula for the maximum of the process, or the free...

### Many-body Anderson localization

David Huse
I will review some aspects of many-body Anderson localization. Many-body localized systems have a type of integrable Hamiltonian, with an extensive set of operators that are localized in real-space that each commute with the Hamiltonian. The...

### From High Dimensional Data to Big Data

Han Liu
We introduce a new family of robust semiparametric methods for analyzing large, complex, and noisy datasets. Our method is based on the transelliptical distribution family which assumes that the variables follow an elliptical distribution after a...