Previous Conferences & Workshops

Dec
04
2013

Non-equilibrium Dynamics and Random Matrices

KPZ line ensemble
Ivan Corwin
11:00am|S-101

We construct a \(\mathrm{KPZ}_t\) line ensemble -- a natural number indexed collection of random continuous curves which satisfies a resampling invariance called the H-Brownian Gibbs property (with \(H(x)=e^x\)) and whose lowest indexed curve is...

Dec
03
2013

Non-equilibrium Dynamics and Random Matrices

Polynomial chaos and scaling limits of disordered systems
Nikolaos Zygouras
2:00pm|S-101

Inspired by recent work of Alberts, Khanin and Quastel, we formulate general conditions ensuring that a sequence of multi-linear polynomials of independent random variables (called polynomial chaos expansions) converges to a limiting random variable...

Dec
03
2013

Computer Science/Discrete Mathematics Seminar II

Multi-party Interactive Coding
10:30am|S-101

We will discuss interactive coding in the setting where there are n parties attempting to compute a joint function of their inputs using error-prone pairwise communication channels. We will present a general protocol that allows one to achieve only...

Dec
02
2013

Members’ Seminar

From Gromov to the Moon
2:00pm|S-101

I will present some recent applications of symplectic geometry to the restricted three body problem. More specifically, I will discuss how Gromov's original study of pseudoholomorphic curves in the complex projective plane has led to the...

Dec
02
2013

Computer Science/Discrete Mathematics Seminar I

A solution to Weaver's \(KS_2\)
11:15am|S-101

We will outline the proof that gives a positive solution of to Weaver's conjecture \(KS_2\). That is, we will show that any isotropic collection of vectors whose outer products sum to twice the identity can be partitioned into two parts such that...

Nov
26
2013

Non-equilibrium Dynamics and Random Matrices

Diffusion for the (Markov) Anderson model
2:00pm|S-101

I will discuss the proof by Yang Kang and myself of diffusion for the Markov Anderson model, in which the potential is allowed to fluctuate in time as a Markov process. However, I want to highlight the method of the proof more than the result itself...