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Under natural conditions, we proved the exponential ergodicity in Wasserstein distance of two-type continuous-state branching processes in L\'evy random environments with immigration. Furthermore, we expressed accurately the parameters of…

Probability · Mathematics 2022-02-14 Shukai Chen , Rongjuan Fang , Xiangqi Zheng

In this paper we consider compact, Riemannian manifolds $M_1, M_2$ each equipped with a one-parameter family of metrics $g_1(t), g_2(t)$ satisfying the Ricci flow equation. Motivated by a characterization of the super Ricci flow developed…

Differential Geometry · Mathematics 2018-07-24 Sajjad Lakzian , Michael Munn

This work investigates several aspects related to quantitative stability in optimal transport, as well as uniqueness of the dual transport problem. Our main contributions are as follows. Chapter 1: Observations regarding the quantitative…

Functional Analysis · Mathematics 2025-10-22 William Ford

The diffusive transport distance, a novel pseudo-metric between probability measures on the real line, is introduced. It generalizes Martingale optimal transport, and forms a hierarchy with the Hellinger and the Wasserstein metrics. We…

Analysis of PDEs · Mathematics 2025-01-27 Daniel Matthes , Eva-Maria Rott , André Schlichting

We study the problem of minimizing the Wasserstein distance between a probability distribution and an algebraic variety. We consider the setting of finite state spaces and describe the solution depending on the choice of the ground metric…

Optimization and Control · Mathematics 2020-01-15 T. Ö. Çelik , A. Jamneshan , G. Montúfar , B. Sturmfels , L. Venturello

In recent years, two prominent paradigms have shaped distributionally robust optimization (DRO), modeling distributional ambiguity through $\phi$-divergences and Wasserstein distances, respectively. While the former focuses on ambiguity in…

Optimization and Control · Mathematics 2025-12-22 Jose Blanchet , Daniel Kuhn , Jiajin Li , Bahar Taskesen

We develop a compactness theory for super Ricci flows, which lays the foundations for the partial regularity theory in [Bam20b]. Our results imply that any sequence of super Ricci flows of the same dimension that is pointed in an…

Differential Geometry · Mathematics 2023-08-16 Richard H Bamler

We develop two novel couplings between general pure-jump L\'evy processes in $\R^d$ and apply them to obtain upper bounds on the rate of convergence in an appropriate Wasserstein distance on the path space for a wide class of L\'evy…

Probability · Mathematics 2025-06-19 Jorge González Cázares , David Kramer-Bang , Aleksandar Mijatović

The Wasserstein distances $W_p$ ($p\geq 1$), defined in terms of solution to the Monge-Kantorovich problem, are known to be a useful tool to investigate transport equations. In particular, the Benamou-Brenier formula characterizes the…

Analysis of PDEs · Mathematics 2014-11-19 Benedetto Piccoli , Francesco Rossi

We propose a new approach to measuring the agreement between two oscillatory time series, such as seismic waveforms, and demonstrate that it can be employed effectively in inverse problems. Our approach is based on Optimal Transport theory…

Geophysics · Physics 2022-07-01 Malcolm Sambridge , Andrew Jackson , Andrew P. Valentine

We consider four extended Ricci flow systems---that is, Ricci flow coupled with other geometric flows---and prove dynamical stability of certain classes of stationary solutions of these flows. The systems include Ricci flow coupled with…

Differential Geometry · Mathematics 2015-06-22 Michael Bradford Williams

We investigate stability properties of weak supermartingale optimal transport (WSOT) problems on $\mathbb{R}$. For probability measures $\mu,\nu\in\mathcal{P}_r$ satisfying $\mu \leq_{cd} \nu$ (equivalently, $\Pi_S(\mu,\nu)\neq\emptyset$),…

Probability · Mathematics 2026-03-31 Shuoqing Deng , Gaoyue Guo , Dominykas Norgilas

We investigate the stability of the Wasserstein distance, a metric structure on the space of probability measures arising from the theory of optimal transport, under metric ultralimits. We first show that if $(X_{i},d_{i})_{i\in\mathbb{N}}$…

Metric Geometry · Mathematics 2023-03-09 Andrew Warren

The function that maps a family of probability measures to the solution of the dual entropic optimal transport problem is known as the Schr\"odinger map. We prove that when the cost function is $\mathcal{C}^{k+1}$ with $k\in \mathbb{N}^*$…

Optimization and Control · Mathematics 2024-03-04 Guillaume Carlier , Lénaïc Chizat , Maxime Laborde

In this paper we discuss the Wasserstein distance between the n-point motions of Harris flows whose covariance functions have compact support. We prove that it can be estimated by the diameters of their support provided the latter are…

Probability · Mathematics 2017-04-04 A. A. Dorogovtsev , V. V. Fomichov

We revisit the question of characterizing the convergence rate of plug-in estimators of optimal transport costs. It is well known that an empirical measure comprising independent samples from an absolutely continuous distribution on…

Probability · Mathematics 2024-02-06 Tudor Manole , Jonathan Niles-Weed

We show that the distance function under the Ricci flow is uniformly continuous in the time direction, assuming only the scalar curvature is bounded.

Differential Geometry · Mathematics 2017-09-05 Gang Tian , Qi S. Zhang

We discuss the classical problem of measuring the regularity of distribution of sets of $N$ points in $\mathbb{T}^d$. A recent line of investigation is to study the cost ($=$ mass $\times$ distance) necessary to move Dirac measures placed…

Classical Analysis and ODEs · Mathematics 2020-09-29 Louis Brown , Stefan Steinerberger

Ricci flow on two dimensional surfaces is far simpler than in the higher dimensional cases. This presents an opportunity to obtain much more detailed and comprehensive results. We review the basic facts about this flow, including the…

Differential Geometry · Mathematics 2011-03-25 James Isenberg , Rafe Mazzeo , Natasa Sesum

Wasserstein distance (WD) and the associated optimal transport plan have been proven useful in many applications where probability measures are at stake. In this paper, we propose a new proxy of the squared WD, coined min-SWGG, that is…

Machine Learning · Statistics 2023-10-31 Guillaume Mahey , Laetitia Chapel , Gilles Gasso , Clément Bonet , Nicolas Courty