Uniform-in-Time and Uniform-in-Temperature Particle Approximations of Coulomb MMD Flows
Junho Lee, Promit Ghosal
Abstract
We study particle approximations of maximum mean discrepancy (MMD) flows with the Coulomb kernel on the torus Td, d2, driven by thermal noise of strength τ0. For smooth, strictly positive initial and target densities and i.i.d. initial positions, we prove that the expected Wasserstein-1 distance between the empirical measure and the mean-field solution is at most of order N-1/d for d3 and ( N)/N for d=2, uniformly in time and in the temperature τ0, including the deterministic case τ=0. At each fixed τ>0, we also prove propagation of chaos in total variation for any k-fold marginal distributions of particles, uniformly in time, with a bound of order k/τ times the empirical convergence rate. Our proof uses the modulated free-energy method of Bresch, Jabin, and Wang to reduce the particle convergence estimate to a relaxation estimate that controls the time integral of the mean-field velocity gradient uniformly in τ0. Near zero temperature, where the smoothing effect of the noise degenerates, we obtain this estimate by recentering the dynamics at thermal equilibrium and using the damping generated by the Coulomb interaction.
Create a lesson
Related papers
Closed-form evaluation of the cumulative distribution function and absolute moments of the variance-gamma distribution
Robert E. Gaunt, Heather L. Sutcliffe
Dudley-type bound for stationary Bernoulli processes
W. Bednorz, R. Martynek, R. Meller
Poincaré inequalities, logarithmic growth and doubling
Joaquim Martin
Axioms and internal rigidity of spectral duality structures
Juan Antonio Vega Coso
D-Pullback Measure Attractors of McKean-Vlasov Stochastic Lattice Wave Equations
Huixia Wen, Ji Shu, Gang He
Large deviation principles for 2D stochastic g-Navier--Stokes equations on unbounded channel-like domains
Gang He, Ji Shu, Huixia Wen et al.