Seminar | August 31 | 3:10-4 p.m. | 340 Evans Hall
Milind Hegde, Department of Mathematics, Columbia University
The Kardar-Parisi-Zhang (KPZ) equation is a canonical non-linear stochastic PDE believed to describe the evolution of a large number of planar stochastic growth models which make up the KPZ universality class. A particularly important observable is the one-point distribution of its analogue of the fundamental solution, which has featured in much of its recent study. However, in spite of significant recent progress relying on explicit formulas, a sharp understanding of its upper tail behaviour has remained out of reach. In this talk we will discuss a geometric approach, related to the tangent method introduced by Colomo-Sportiello and rigorously implemented by Aggarwal for the six-vertex model. The approach utilizes a Gibbs resampling property of the KPZ equation and yields a sharp understanding for a large class of initial data.
Joint work with Shirshendu Ganguly.
CA, alanmh@berkeley.edu, 000000000000
Alan Hammond, alanmh@berkeley.edu, 000-000-0000