Activity
A regularity method for lower bounds on the Lyapunov exponent for stochastic differential equations
Date:2021-09-15

Abstract.  In this talk we discuss our recently introduced methods for obtaining strictly positive lower bounds on the top Lyapunov exponent of high-dimensional, stochastic differential equations such as the weakly-damped Lorenz-96 (L96) model or Galerkin truncations of the 2d Navier-Stokes equations (joint with Alex Blumenthal and Sam Punshon-Smith). This hallmark of chaos has long been observed in these models, however, no mathematical proof had previously been made for any type of deterministic or stochastic forcing. The method we proposed combines (A) a new identity connecting the Lyapunov exponents to a Fisher information of the stationary measure of the Markov process tracking tangent directions (the so-called "projective process"); and (B) an L1-based hypoelliptic regularity estimate to show that this (degenerate) Fisher information is an upper bound on some fractional regularity. For L96 and GNSE, we then further reduce the lower bound of the top Lyapunov exponent to proving that the projective process satisfies Hörmander's condition. I will also discuss the recent work of Sam Punshon-Smith and I on verifying this condition for the 2d Galerkin-Navier-Stokes equations in a rectangular, periodic box of any aspect ratio using some special structure of matrix Lie algebras and ideas from computational algebraic geometry.

 

 

 

 

 

Bio.  Jacob Bedrossian is a Professor at the University of Maryland, College Park. He got Peter Lax Award, IMA Prize, SIAG/APDE prize, and Alfred P. Sloan Research Fellow in Mathematics for his breakthrough in mixing, turbulence, and the stability of coherent structures in 2D and 3D fluid mechanics at high Reynolds number and Landau damping-related kinetic effects arising in plasmas. He is also an invited speaker at ICM 2022.

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