MARK KAC SEMINAR

April 2024 Season 2023-2024 Main speaker: N. Kistler

April 5 2024

Location: JKH 2-3, room 111
11:00–11:45
Giulia Sebastiani (Frankfurt) homepage

Part 5: On the GREM Approximation of TAP Free Energies.

The free energy of TAP-solutions for the SK-model of mean field spin glasses can be expressed as a nonlinear functional of local terms: we exploit this feature in order to contrive abstract GREM-like models which we then solve by a classical large deviations treatment. This allows to identify the origin of the physically unsettling quadratic (in the inverse of temperature) correction to the Parisi free energy for the SK-model, and formalizes thetrue cavity dynamics which acts on TAP-space, i.e. on the space of TAP-solutions. Joint works with Nicola Kistler, and Marius A. Schmidt.

12:00–12:45
A. Schertzer (Frankfurt) homepage

Part 6: From log-correlated models to (un)directed polymers in the mean field limit

As seen in the previous lectures, Derrida's Random Energy Models have played a key role in the understanding of certain issues in spin glasses. The mathematical analysis of these models - in particular the multi-scale refinement of the second moment method as devised by Kistler, is also particularly efficient to analyse the so-called log-correlated class; the latter consists of Gaussian fields with - as the name suggests, logarithmically decaying correlations. I will introduce/recall some models falling into this class, and the main steps in their analysis through the paradigmatic Branching Brownian motion / Branching Random Walk. Finally, I will conclude with recent results on models which are not even Gaussian, but for which the multiscale treatment still goes through swiftly: the directed and undirected first passage percolation in the limit of large dimensions, a.k.a. the (un)directed polymers in random environment. Joint works with Nicola Kistler, and Marius A. Schmidt.

14:15–16:00
Vittoria Silvestri (Rome) homepage

Fluctuations and mixing of Internal DLA on cylinders

Internal DLA models the growth of a random discrete set by subsequent aggregation of particles. At each step, a new particle starts inside the current aggregate, and it performs a simple random walk until reaching an unoccupied site, where it settles. The large scale properties of IDLA clusters are by now well understood. In these two talks I will instead focus on Internal DLA on cylinder graphs, seen as a Markov chain on the space of particle configurations. I will present several techniques for bounding the maximal fluctuations of IDLA clusters, which allow one to show that the stationary distribution concentrates on a small subset of the infinite state space. I will then discuss the mixing time of the chain, and its dependence on the choice of the cylinder's base graph.