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In this paper we consider global $\theta$-curvatures of finite Markov chains with associated means $\theta$ in the spirit of the entropic curvature (based on the logarithmic mean) by Erbar-Maas and Mielke. As in the case of Bakry-\'Emery…

Differential Geometry · Mathematics 2025-04-01 Supanat Kamtue , Shiping Liu , Florentin Münch , Norbert Peyerimhoff

The unit Euclidean distance degree and the generic Euclidean distance degree are two well-studied invariants of projective varieties. These quantities measure the algebraic complexity of nearest-point problems on a variety, and in many…

Algebraic Geometry · Mathematics 2026-05-14 Laurenţiu G. Maxim , Jose Israel Rodriguez , Botong Wang

We investigate the transport properties of a kinetic theory model that is tuned to describe the thermodynamic properties of QCD at zero chemical potential using a new formulation of the relaxation time approximation. In contrast to previous…

Nuclear Theory · Physics 2022-08-24 Gabriel S. Rocha , Maurício N. Ferreira , Gabriel S. Denicol , Jorge Noronha

Transport properties of particles and waves in spatially periodic structures that are driven by external time-dependent forces manifestly depend on the space-time symmetries of the corresponding equations of motion. A systematic analysis of…

Mesoscale and Nanoscale Physics · Physics 2014-12-23 Sergey Denisov , Sergej Flach , Peter Hanggi

In this letter we present a theorem on the dynamics of the generalized Hubbard models. This theorem shows that the symmetry of the single particle Hamiltonian can protect a kind of dynamical symmetry driven by the interactions. Here the…

Quantum Gases · Physics 2017-12-06 Jinlong Yu , Ning Sun , Hui Zhai

Optimal transport between classical probability distributions has been proven useful in areas such as machine learning and random combinatorial optimization. Quantum optimal transport, and the quantum Wasserstein distance as the minimal…

We study the problem of representing all distances between $n$ points in $\mathbb R^d$, with arbitrarily small distortion, using as few bits as possible. We give asymptotically tight bounds for this problem, for Euclidean metrics, for…

Computational Geometry · Computer Science 2021-10-08 Piotr Indyk , Tal Wagner

We consider a Markov chain on $\mathbb{R}^d$ with invariant measure $\mu$. We are interested in the rate of convergence of the empirical measures towards the invariant measure with respect to various dual distances, including in particular…

Probability · Mathematics 2022-10-13 Adrian Riekert

A general principle of modern statistical physics is that divergences of either thermodynamic or transport properties are only possible if the correlation length diverges. We show by explicit calculation that the thermopower in the quantum…

Strongly Correlated Electrons · Physics 2014-08-27 Kridsanaphong Limtragool , Philip W. Phillips

Let $G=(V,E)$ be a finite, combinatorial graph. We define a notion of curvature on the vertices $V$ via the inverse of the resistance distance matrix. We prove that this notion of curvature has a number of desirable properties. Graphs with…

Combinatorics · Mathematics 2023-02-22 Karel Devriendt , Andrea Ottolini , Stefan Steinerberger

In this paper, we provide sufficient conditions for the existence of the invariant distribution and for subgeometric rates of convergence in Wasserstein distance for general state-space Markov chains which are (possibly) not irreducible.…

Probability · Mathematics 2015-07-15 Alain Durmus , Gersende Fort , Eric Moulines

We consider a condition on the Ricci curvature involving vector fields, which is broader than the Bakry-\'Emery Ricci condition. Under this condition volume comparison, Laplacian comparison, isoperimetric inequality and gradient bounds are…

Differential Geometry · Mathematics 2016-06-01 Qi S Zhang , Meng Zhu

In this paper, we derive exponential ergodicity in relative entropy for general kinetic SDEs under a partially dissipative condition. It covers non-equilibrium situations where the forces are not of gradient type and the invariant measure…

Probability · Mathematics 2025-07-10 Xing Huang , Eva Kopfer , Pierre Monmarché , Panpan Ren

We develop a new class of distances for objects including lines, hyperplanes, and trajectories, based on the distance to a set of landmarks. These distances easily and interpretably map objects to a Euclidean space, are simple to compute,…

Computational Geometry · Computer Science 2019-06-13 Jeff M. Phillips , Pingfan Tang

The aim of this paper is to investigate the contraction properties of $p$-Wasserstein distances with respect to convolution in Euclidean spaces both qualitatively and quantitatively. We connect this question to the question of uniform…

Analysis of PDEs · Mathematics 2025-12-05 Max Fathi , Michael Goldman , Daniel Tsodyks

Distances between probability distributions that take into account the geometry of their sample space,like the Wasserstein or the Maximum Mean Discrepancy (MMD) distances have received a lot of attention in machine learning as they can, for…

Machine Learning · Computer Science 2020-04-29 Gaëtan Hadjeres , Frank Nielsen

We provide quantitative estimates in total variation distance for positive semi-groups, which can be non-conservative and non-homogeneous. The techniques relies on a family of conservative semigroups that describes a typical particle and…

Analysis of PDEs · Mathematics 2020-07-22 Vincent Bansaye , Bertrand Cloez , Pierre Gabriel

We introduce a fractional Klein-Kramers equation which describes sub-ballistic superdiffusion in phase space in the presence of a space-dependent external force field. This equation defines the differential L{\'e}vy walk model whose…

Statistical Mechanics · Physics 2015-06-24 Ralf Metzler , Igor M. Sokolov

We establish subgeometric bounds on convergence rate of general Markov processes in the Wasserstein metric. In the discrete time setting we prove that the Lyapunov drift condition and the existence of a "good" $d$-small set imply…

Probability · Mathematics 2014-03-20 Oleg Butkovsky

Relativistic transport phenomena are important from both theoretical and practical point of view. Accordingly, hydrodynamics of relativistic gas has been extensively studied theoretically. Here, we introduce a three-dimensional canonical…

Statistical Mechanics · Physics 2015-06-15 Malihe Ghodrat , Afshin Montakhab