Overcrowding asymptotics for the Sine_beta process

We give overcrowding estimates for the Sine_beta process, the bulk point process limit of the Gaussian beta-ensemble. We show that the probability of having at least n points in a fixed interval is given by $e^{-frac{beta}{2} n^2 log(n)+O(n^2)}$ as $nto infty$. We also identify the next order term in the exponent if the size of the interval goes to zero.

Fluctuation exponents for directed polymers in the intermediate disorder regime

We compute the fluctuation exponents for a solvable model of one-dimensional directed polymers in random environment in the intermediate regime. This regime corresponds to taking the inverse temperature to zero with the size of the system. The exponents satisfy the KPZ scaling relation and coincide with physical predictions. In the critical case, we recover the fluctuation exponents of the Cole-Hopf solution of the KPZ equation in equilibrium and close to equilibrium.

Large deviations for the Sine_beta and Sch_tau processes

We study two one-parameter families of point processes connected to random matrices: the Sine_beta and Sch_tau processes. The first one is the bulk point process limit for the Gaussian beta-ensemble. For beta=1, 2 and 4 it gives the limit of the GOE, GUE and GSE models of random matrix theory. In particular, for beta=2 it is a determinantal point process conjectured to have similar behavior to the critical zeros of the Riemann zeta-function. The second process can be obtained as the bulk scaling limit of the spectrum of certain discrete one-dimensional random Schrodinger operators. Both processes have asymptotically constant average density, in our normalization one expects close to lambda/(2pi) points in a large interval of length lambda. Our main results are large deviation principles for the average densities of the processes, essentially we compute the asymptotic probability of seeing an unusual average density in a large interval. Our approach is based on the representation of the counting functions of these processes using stochastic differential equations. We also prove path level large deviation principles for the arising diffusions. Our techniques work for the full range of parameter values. The results are novel even in the classical beta=1, 2 and 4 cases for the Sine_beta process. They are consistent with the existing rigorous results on large gap probabilities and confirm the physical predictions made using log-gas arguments.

Diffusivity of lattice gases

We consider one component lattice gases with a local dynamics and a stationary product Bernoulli measure. We give upper and lower bounds on the diffusivity at an equilibrium point depending on the dimension and the local behavior of the macroscopic flux function. We show that if the model is expected to be diffusive, it is indeed diffusive, and, if it is expected to be superdiffusive, it is indeed superdiffusive.