English

Convergence in Wasserstein Distance for Empirical Measures of Non-Symmetric Subordinated Diffusion Processes

Probability 2023-02-28 v2

Abstract

By using the spectrum of the underlying symmetric diffusion operator, the convergence in LpL^p-Wasserstein distance Wp(p1)\mathbb W_p (p\ge 1) is characterized for the empirical measure μt\mu_t of non-symmetric subordinated diffusion processes in an abstract framework. The main results are applied to the subordinations of several typical models, which include the (reflecting) diffusion processes on compact manifolds, the conditional diffusion processes, the Wright-Fisher diffusion process, and hypoelliptic diffusion processes on {\bf SU}(2). In particular, for the (reflecting) diffusion processes on a compact Riemannian manifold with invariant probability measure μ\mu: (1) the sharp limit of tW2(μt,μ)2t\mathbb W_2(\mu_t,\mu)^2 is derived in Lq(P)L^q(\mathbb P) for concrete q1,q\ge 1, which provides a precise characterization on the physical observation that a divergence-free perturbation accelerates the convergence in W2\mathbb W_2; (2) the sharp convergence rates are presented for (E[W2p(μt,μ)q])1q(p,q1)(\mathbb E[\mathbb W_{2p}(\mu_t,\mu)^{q}])^{\frac 1 q} (p,q\ge 1), where a critical phenomenon appears with the critical rate t1logtt^{-1}\log t as tt\to\infty.

Keywords

Cite

@article{arxiv.2301.08420,
  title  = {Convergence in Wasserstein Distance for Empirical Measures of Non-Symmetric Subordinated Diffusion Processes},
  author = {Feng-Yu Wang},
  journal= {arXiv preprint arXiv:2301.08420},
  year   = {2023}
}

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57 pages