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Long-time contractivity estimates for kinetic Kolmogorov-Fokker-Planck equations

Nicolò Forcillo, Alessio Porretta

TL;DR

This work addresses the problem of long-time convergence for hypoelliptic kinetic Kolmogorov-Fokker-Planck equations by introducing a self-contained PDE approach that derives exponential contraction via dual oscillation estimates on the adjoint problem. The authors first prove Wasserstein contraction through a doubling-variables coupling argument and then upgrade to weighted total-variation decay using short-time $L^{\infty}$-to-$W^{1,\infty}$ smoothing (hypocoercivity). The key contributions include (i) a rigorous oscillation-decay framework for the adjoint problem leading to $W_1$-type contraction, (ii) a Bernstein-type short-time smoothing result giving $L^{\infty}$-Lipschitz regularization, and (iii) explicit Lyapunov-function-based conditions yielding exponential decay in the weighted TV norm, with concrete examples such as the Kolmogorov equation. The results provide a robust, duality-based method that extends to nonlinear, inhomogeneous first-order terms and highlights the role of hypoellipticity in driving long-time stabilization without requiring explicit steady states.

Abstract

We prove long-time contractivity estimates and exponential rates of convergence to equilibrium for solutions of hypoelliptic diffusion equations, which include the well-known Kolmogorov equation and similar kinetic Fokker-Planck equations in $\R^d$. Compared to the existing literature, our proof exploits a different approach, elementary and self-contained, based on oscillation estimates for the adjoint problem. We first prove contractivity in Wasserstein distances through doubling variables (coupling) methods. Next, we upgrade the estimate to weighted $L^1$-(or total variation) norms, thanks to short-time hypocoercivity gradient estimates.

Long-time contractivity estimates for kinetic Kolmogorov-Fokker-Planck equations

TL;DR

This work addresses the problem of long-time convergence for hypoelliptic kinetic Kolmogorov-Fokker-Planck equations by introducing a self-contained PDE approach that derives exponential contraction via dual oscillation estimates on the adjoint problem. The authors first prove Wasserstein contraction through a doubling-variables coupling argument and then upgrade to weighted total-variation decay using short-time -to- smoothing (hypocoercivity). The key contributions include (i) a rigorous oscillation-decay framework for the adjoint problem leading to -type contraction, (ii) a Bernstein-type short-time smoothing result giving -Lipschitz regularization, and (iii) explicit Lyapunov-function-based conditions yielding exponential decay in the weighted TV norm, with concrete examples such as the Kolmogorov equation. The results provide a robust, duality-based method that extends to nonlinear, inhomogeneous first-order terms and highlights the role of hypoellipticity in driving long-time stabilization without requiring explicit steady states.

Abstract

We prove long-time contractivity estimates and exponential rates of convergence to equilibrium for solutions of hypoelliptic diffusion equations, which include the well-known Kolmogorov equation and similar kinetic Fokker-Planck equations in . Compared to the existing literature, our proof exploits a different approach, elementary and self-contained, based on oscillation estimates for the adjoint problem. We first prove contractivity in Wasserstein distances through doubling variables (coupling) methods. Next, we upgrade the estimate to weighted -(or total variation) norms, thanks to short-time hypocoercivity gradient estimates.

Paper Structure

This paper contains 11 sections, 16 theorems, 175 equations.

Key Result

Theorem 1.1

Assume that $H,B$ satisfy (Blip) and (H1)-(H2), and there exists a Lyapunov function $\varphi$ (cf. Definition def-Lyap) fulfilling conditions (liplocvfi), (vfi2), and (vfi3). Then, there exist $\omega, K>0$ such that, for every initial data $m_{01}, m_{02}\in {\mathcal{P}}_1({\mathbb R}^{2d})$ for where $\|\cdot\|_{TV_\varphi}$ is the norm of the total variation weighted by $\varphi$.

Theorems & Definitions (35)

  • Theorem 1.1
  • Remark 2.1
  • Definition 2.2
  • Theorem 2.3
  • Remark 2.4
  • Corollary 2.5
  • Definition 3.1
  • Theorem 3.2
  • proof
  • Remark 3.3
  • ...and 25 more