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A finite dimensional abstract approximation and convergence theory is developed for estimation of the distribution of random parameters in infinite dimensional discrete time linear systems with dynamics described by regularly dissipative…

Optimization and Control · Mathematics 2019-03-15 Melike Sirlanci , Susan E. Luczak , I. Gary Rosen

We outline an efficient method for the reconstruction of a probability density function from the knowledge of its infinite sequence of ordinary moments. The approximate density is obtained resorting to maximum entropy technique, under the…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Pierluigi Novi Inverardi , Alberto Petri , Giorgio Pontuale , Aldo Tagliani

We introduce a version of Stein's method of comparison of operators specifically tailored to the problem of bounding the Wasserstein-1 distance between continuous and discrete distributions on the real line. Our approach rests on a new…

Probability · Mathematics 2023-11-03 Gilles Germain , Yvik Swan

We consider a random walk $S_k$ with i.i.d. steps on a compact group equipped with a bi-invariant metric. We prove quantitative ergodic theorems for the sum $\sum_{k=1}^N f(S_k)$ with H\"older continuous test functions $f$, including the…

Probability · Mathematics 2022-09-27 Bence Borda

In this paper, we propose a general means of estimating the rate at which convergences in law occur. Our approach, which is an extension of the classical Stein-Tikhomirov method, rests on a new pair of linear operators acting on…

Probability · Mathematics 2017-06-29 Benjamin Arras , Guillaume Mijoule , Guillaume Poly , Yvik Swan

We use Stein's method to obtain bounds on the rate of convergence for a class of statistics in geometric probability obtained as a sum of contributions from Poisson points which are exponentially stabilizing, i.e. locally determined in a…

Probability · Mathematics 2007-05-23 Mathew D. Penrose , J. E. Yukich

A general class of solutions of Einstein's equation for a slowly rotating fluid source, with supporting internal pressure, is matched using Lichnerowicz junction conditions, to the Kerr metric up to and including first order terms in…

General Relativity and Quantum Cosmology · Physics 2015-06-25 R. J. Wiltshire

Seiberg-Witten theory leads to a delicate interplay between Riemannian geometry and smooth topology in dimension four. In particular, the scalar curvature of any metric must satisfy certain non-trivial estimates if the manifold in question…

Differential Geometry · Mathematics 2016-09-07 Claude LeBrun

The study of generic properties of quantum states has led to an abundance of insightful results. A meaningful set of states that can be efficiently prepared in experiments are ground states of gapped local Hamiltonians, which are well…

Quantum Physics · Physics 2022-05-03 Jonas Haferkamp , Christian Bertoni , Ingo Roth , Jens Eisert

Observational entropy -- a quantity that unifies Boltzmann's entropy, Gibbs' entropy, von Neumann's macroscopic entropy, and the diagonal entropy -- has recently been argued to play a key role in a modern formulation of statistical…

Quantum Physics · Physics 2026-03-24 Teruaki Nagasawa , Kohtaro Kato , Eyuri Wakakuwa , Francesco Buscemi

We propose an entropic Fourier method for the numerical discretization of the Boltzmann collision operator. The method, which is obtained by modifying a Fourier Galerkin method to match the form of the discrete velocity method, can be…

Numerical Analysis · Mathematics 2018-07-05 Zhenning Cai , Yuwei Fan , Lexing Ying

In this paper we investigate the entropy of gravitational Chern-Simons terms for the horizon with non-vanishing extrinsic curvatures, or the holographic entanglement entropy for arbitrary entangling surface. In 3D we find no anomaly of…

High Energy Physics - Theory · Physics 2016-05-04 Wu-Zhong Guo , Rong-Xin Miao

Entropy-like functionals on operator algebras have been studied since the pioneering work of von Neumann, Umegaki, Lindblad, and Lieb. The most well-known are the von Neumann entropy $trace (\rho\log \rho)$ and a generalization of the…

Optimization and Control · Mathematics 2008-07-19 Tryphon T. Georgiou

In this paper we show that the existence of a primarily discrete space-time may be a fruitful assumption from which we may develop a new approach of statistical thermodynamics in pre-relativistic conditions. The discreetness of space-time…

Quantum Physics · Physics 2010-05-17 J. P. Badiali

Informational dependence between statistical or quantum subsystems can be described with Fisher matrix or Fubini-Study metric obtained from variations of the sample/configuration space coordinates. Using these non-covariant objects as…

High Energy Physics - Theory · Physics 2019-01-30 Vitaly Vanchurin

The purpose of the present paper is to establish moment estimates of Rosenthal type for a rather general class of random variables satisfying certain bounds on the cumulants. We consider sequences of random variables which satisfy a central…

Probability · Mathematics 2019-01-16 Peter Eichelsbacher , Lukas Knichel

Stein's method is a method of probability approximation which hinges on the solution of a functional equation. For normal approximation the functional equation is a first order differential equation. Malliavin calculus is an…

Probability · Mathematics 2015-05-11 Louis H. Y. Chen

We obtain explicit error bounds for the $d$-dimensional normal approximation on hyperrectangles for a random vector that has a Stein kernel, or admits an exchangeable pair coupling, or is a non-linear statistic of independent random…

Probability · Mathematics 2020-09-08 Xiao Fang , Yuta Koike

We study the contraction in Wasserstein distance of the coordinate ascent variational inference algorithm. This is shown to hold under a transport-information inequality at the fixed points and a functional smoothness condition. The results…

Machine Learning · Statistics 2026-05-29 Rocco Caprio , Adrien Corenflos , Sam Power

The Matrix-based Renyi's entropy enables us to directly measure information quantities from given data without the costly probability density estimation of underlying distributions, thus has been widely adopted in numerous statistical…

Machine Learning · Statistics 2022-05-17 Yuxin Dong , Tieliang Gong , Shujian Yu , Chen Li