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There is a long history of establishing central limit theorems for Markov chains. Quantitative bounds for chains with a spectral gap were proved by Mann and refined later. Recently, rates of convergence for the total variation distance were…

Probability · Mathematics 2023-08-24 Rafael Chiclana , Yuval Peres

We study the mean curvature flow of complete space-like submanifolds in pseudo-Euclidean space with bounded Gauss image, as well as that of complete submanifolds in Euclidean space with convex Gauss image. By using the confinable property…

Differential Geometry · Mathematics 2007-05-23 Y. L. Xin

L\'evy-type walks with correlated jumps, induced by the topology of the medium, are studied on a class of one-dimensional deterministic graphs built from generalized Cantor and Smith-Volterra-Cantor sets. The particle performs a standard…

Statistical Mechanics · Physics 2015-05-14 R. Burioni , L. Caniparoli , S. Lepri , A. Vezzani

We propose a general approach for quantitative convergence analysis of non-reversible Markov processes, based on the concept of second-order lifts and a variational approach to hypocoercivity. To this end, we introduce the flow Poincar{\'e}…

Analysis of PDEs · Mathematics 2025-07-22 Andreas Eberle , Arnaud Guillin , Leo Hahn , Francis Lörler , Manon Michel

We define the Uniform Random Walk (URW) on a connected, locally finite graph as the weak limit of the uniform walk of length $n$ starting at a fixed vertex. When the limit exists, it is necessarily Markovian and is independent of the…

Probability · Mathematics 2025-12-11 Miklos Abert , Adam Arras , Jaelin Kim

We propose a novel multiple-scale spatial marching method for flows with slow streamwise variation. The key idea is to couple the boundary region equations, which govern large-scale flow evolution, with local exact coherent structures that…

Fluid Dynamics · Physics 2026-01-14 Runjie Song , Kengo Deguchi

In this paper, we consider an inverse space-dependent source problem for a time-fractional diffusion equation. To deal with the ill-posedness of the problem, we transform the problem into an optimal control problem with total variational…

Optimization and Control · Mathematics 2025-01-15 Bin Fan

We introduce the setting of extended metric-topological measure spaces as a general "Wiener-like" framework for optimal transport problems and nonsmooth metric analysis in infinite dimension. After a brief review of optimal transport tools…

Functional Analysis · Mathematics 2015-06-22 Luigi Ambrosio , Matthias Erbar , Giuseppe Savaré

We present an analysis of total-variation (TV) on non-Euclidean parameterized surfaces, a natural representation of the shapes used in 3D graphics. Our work explains recent experimental findings in shape spectral TV [Fumero et al., 2020]…

Computational Geometry · Computer Science 2024-02-05 Jonathan Brokman , Martin Burger , Guy Gilboa

We propose a novel discrete concept for the total generalized variation (TGV), which has originally been derived to reduce the staircasing effect in classical total variation (TV) regularization, in image denoising problems. We describe…

Numerical Analysis · Mathematics 2022-09-27 Lukas Baumgärtner , Ronny Bergmann , Roland Herzog , Stephan Schmidt , José Vidal-Núñez

We review various features of the statistics of random paths on graphs. The relationship between path statistics and Quantum Mechanics (QM) leads to two canonical ways of defining random walk on a graph, which have different statistics and…

Statistical Mechanics · Physics 2010-08-04 Z. Burda , J. Duda , J. M. Luck , B. Waclaw

We study asymptotic limits of reversible random walks on tessellations via a variational approach, which relies on a specific generalized-gradient-flow formulation of the corresponding forward Kolmogorov equation. We establish sufficient…

Analysis of PDEs · Mathematics 2022-02-15 Anastasiia Hraivoronska , Oliver Tse

We study the inverse problem of determining a finite weighted graph $(X,E)$ from the source-to-solution map on a vertex subset $B\subset X$ for heat equations on graphs, where the time variable can be either discrete or continuous. We prove…

Spectral Theory · Mathematics 2023-01-05 Emilia Blåsten , Hiroshi Isozaki , Matti Lassas , Jinpeng Lu

The total-variation cutoff phenomenon has been conjectured to hold for simple random walk on all transitive expanders. However, very little is actually known regarding this conjecture, and cutoff on sparse graphs in general. In this paper…

Probability · Mathematics 2022-08-17 Michael Chapman , Ori Parzanchevski

There is an extensive literature concerning self-avoiding walk on infinite graphs, but the subject is relatively undeveloped on finite graphs. The purpose of this paper is to elucidate the phase transition for self-avoiding walk on the…

Probability · Mathematics 2019-09-19 Gordon Slade

The kinetics of a variety of transport-controlled processes can be reduced to the problem of determining the mean time needed to arrive at a given location for the first time, the so called mean first passage time (MFPT) problem. The…

Statistical Mechanics · Physics 2015-06-11 Aljaz Godec , Ralf Metzler

A random walk is a basic stochastic process on graphs and a key primitive in the design of distributed algorithms. One of the most important features of random walks is that, under mild conditions, they converge to a stationary distribution…

Probability · Mathematics 2020-06-19 Leran Cai , Thomas Sauerwald , Luca Zanetti

We investigated a cost-constrained static ergodic control problem of the variance of measure-valued affine processes and its application in streamflow management. The controlled system is a jump-driven mixed moving average process that…

Optimization and Control · Mathematics 2025-11-24 Hidekazu Yoshioka , Tomohiro Tanaka , Yumi Yoshioka , Ayumi Hashiguchi

Continuous time random Walk model has been versatile analytical formalism for studying and modeling diffusion processes in heterogeneous structures, such as disordered or porous media. We are studying the continuous limits of Heterogeneous…

Statistical Mechanics · Physics 2020-06-23 Liubov Tupikina

Sampling a probability distribution with an unknown normalization constant is a fundamental problem in computational science and engineering. This task may be cast as an optimization problem over all probability measures, and an initial…

Machine Learning · Statistics 2024-09-12 Yifan Chen , Daniel Zhengyu Huang , Jiaoyang Huang , Sebastian Reich , Andrew M. Stuart