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Einsiedler, Mozes, Shah and Shapira [Compos. Math. 152 (2016), 667-692] prove an equidistribution theorem for rational points on expanding horospheres in the space of d-dimensional Euclidean lattices, with d>2. Their proof exploits measure…

Number Theory · Mathematics 2016-09-05 Min Lee , Jens Marklof

The stochastic processes underlying the growth and stability of biological and psychological systems reveal themselves when far from equilibrium. Far from equilibrium, nonergodicity reigns. Nonergodicity implies that the average outcome for…

Methodology · Statistics 2022-02-03 Madhur Mangalam , Damian G. Kelty-Stephen

The global stratification and circulation of the ocean and their sensitivities to changes in forcing depend crucially on the representation of the mesoscale eddy field. Here, a geometrically informed and energetically constrained…

Atmospheric and Oceanic Physics · Physics 2018-11-14 Julian Mak , James R. Maddison , David P. Marshall , David R. Munday

Here we show that a particular one-parameter generalization of the exponential function is suitable to unify most of the popular one-species discrete population dynamics models into a simple formula. A physical interpretation is given to…

Biological Physics · Physics 2009-10-20 Alexandre Souto Martinez , Rodrigo Silva Gonzalez , Aquino Lauri Espindola

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete…

Numerical Analysis · Mathematics 2020-01-27 Peter Richtárik , Martin Takáč

In this paper, we study the characterization of geodesics for a class of distances between probability measures introduced by Dolbeault, Nazaret and Savar e. We first prove the existence of a potential function and then give necessary and…

Optimization and Control · Mathematics 2012-04-12 Pierre Cardaliaguet , Guillaume Carlier , Bruno Nazaret

The standard theory of stochastic approximation (SA) is extended to the case when the constraint set is a Riemannian manifold. Specifically, the standard ODE method for analyzing SA schemes is extended to iterations constrained to stay on a…

Optimization and Control · Mathematics 2017-11-30 Suhail M. Shah

We exhibit a family of dynamical systems arising from rational points on elliptic curves in an attempt to mimic the familiar toral automorphisms. At the non-archimedean primes, a continuous map is constructed on the local elliptic curve…

Dynamical Systems · Mathematics 2007-05-23 P. D'Ambros , G. Everest , R. Miles , T. Ward

We consider matrix-valued processes described as solutions to stochastic differential equations of very general form. We study the family of the empirical measure-valued processes constructed from the corresponding eigenvalues. We show that…

Probability · Mathematics 2019-01-10 Jacek Małecki , José Luis Pérez

Let f be a non-invertible holomorphic endomorphism of the complex projective space P^k, f^n its iterate of order n and \mu the equilibrium measure of f. We estimate the speed of convergence in the following known result. If a is a Zariski…

Dynamical Systems · Mathematics 2009-01-21 Tien-Cuong Dinh , Nessim Sibony

We construct the complete set of orders of growth and we define on it the generalized entropy of a dynamical systems. With this object we provide a framework where we can study the separation of orbits of a map beyond the scope of…

Dynamical Systems · Mathematics 2023-06-22 Javier Correa , Enrique R. Pujals

In this paper we obtain logarithmic Hardy and Rellich inequalities on general Lie groups. In the case of graded groups, we also show their refinements using the homogeneous Sobolev norms. In fact, we derive a family of weighted logarithmic…

Analysis of PDEs · Mathematics 2021-07-13 Marianna Chatzakou , Aidyn Kassymov , Michael Ruzhansky

Many systems in physics, engineering, and biology exhibit multiscale stochastic dynamics, where low-dimensional slow variables evolve under the influence of high-dimensional fast processes. In practice, observations are often limited to a…

Machine Learning · Statistics 2026-05-12 Anan Saha , Arnab Ganguly

We present a new approach to far-from-equilibrium statistical mechanics, based on the concept of generalized entropy, which is a microscopically-defined generalization of Onsager-Machlup functional. In the case when a set of slow…

Statistical Mechanics · Physics 2007-05-23 Alexei V. Tkachenko

We formulate a notion of stability for maps between polarised varieties which generalises Kontsevich's definition when the domain is a curve and Tian-Donaldson's definition of K-stability when the target is a point. We give some examples,…

Algebraic Geometry · Mathematics 2018-06-01 Ruadhaí Dervan , Julius Ross

Discrete multiplicative turbulent cascades are described using a formalism involving infinitely divisible random measures. This permits to consider the continuous limit of a cascade developed on a continuum of scales, and to provide the…

Statistical Mechanics · Physics 2015-06-24 F. Schmitt , D. Marsan

Consider a pair of cumulative distribution functions $F$ and $G$, where $F$ is unknown and $G$ is a known reference distribution. Given a sample from $F$, we propose tests to detect the convexity or the concavity of $G^{-1}\circ F$ versus…

Statistics Theory · Mathematics 2025-06-25 Tommaso Lando , Mohammed Es-Salih Benjrada

We propose a new family of fairness definitions for classification problems that combine some of the best properties of both statistical and individual notions of fairness. We posit not only a distribution over individuals, but also a…

Machine Learning · Computer Science 2019-12-18 Michael Kearns , Aaron Roth , Saeed Sharifi-Malvajerdi

This paper is concerned with the study of a circular random distribution called geodesic Normal distribution recently proposed for general manifolds. This distribution, parameterized by two real numbers associated to some specific location…

Statistics Theory · Mathematics 2012-02-27 Jean-François Coeurjolly , Nicolas Le Bihan

Stochastic approximation is a framework unifying many random iterative algorithms occurring in a diverse range of applications. The stability of the process is often difficult to verify in practical applications and the process may even be…

Probability · Mathematics 2014-03-10 Christophe Andrieu , Matti Vihola