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Applying Stein's method, an inductive technique and size bias coupling yields a Berry-Esseen theorem for normal approximation without the usual restriction that the coupling be bounded. The theorem is applied to counting the number of…

Probability · Mathematics 2013-02-26 Larry Goldstein

In a series of recent works, Boyd, Diaconis, and their co-authors have introduced a semidefinite programming approach for computing the fastest mixing Markov chain on a graph of allowed transitions, given a target stationary distribution.…

Probability · Mathematics 2011-09-07 S. Roch

We prove that the classical Efron--Stein inequality holds for independent exchangeable pairs \((X_i,Y_i)\). The same inequality fails for independent identically distributed pairs; a simple trigonometric counterexample shows that the…

Probability · Mathematics 2026-05-08 Jnaneshwar Baslingker , Bálint Virág

A detailed analysis of anomalous U(1)'s and their effective couplings is performed both in field theory and string theory. It is motivated by the possible relevance of such couplings in particle physics, as well as a potential signal…

High Energy Physics - Theory · Physics 2009-11-11 P. Anastasopoulos , M. Bianchi , E. Dudas , E. Kiritsis

We use Stein's method to bound the Wasserstein distance of order $2$ between a measure $\nu$ and the Gaussian measure using a stochastic process $(X_t)_{t \geq 0}$ such that $X_t$ is drawn from $\nu$ for any $t > 0$. If the stochastic…

Probability · Mathematics 2020-05-12 Thomas Bonis

When maximum likelihood estimation is infeasible, one often turns to score matching, contrastive divergence, or minimum probability flow to obtain tractable parameter estimates. We provide a unifying perspective of these techniques as…

Statistics Theory · Mathematics 2022-10-07 Alessandro Barp , Francois-Xavier Briol , Andrew B. Duncan , Mark Girolami , Lester Mackey

A number of coupling strategies are presented for stochastically modeled biochemical processes with time-dependent parameters. In particular, the stacked coupling is introduced and is shown via a number of examples to provide an…

Numerical Analysis · Mathematics 2018-04-04 David F. Anderson , Chaojie Yuan

We show that any application of the technique of unbiased simulation becomes perfect simulation when coalescence of the two coupled Markov chains can be practically assured in advance. This happens when a fixed number of iterations is high…

Computation · Statistics 2023-08-15 George M. Leigh , Wen-Hsi Yang , Montana E. Wickens , Amanda R. Northrop

We study the coupling of axions to gauge bosons in heterotic string theory. The axion-gauge boson couplings in the low energy 4d theory are derived by matching mixed anomalies between higher-form global symmetries and the zero-form gauge…

High Energy Physics - Phenomenology · Physics 2024-10-08 Prateek Agrawal , Michael Nee , Mario Reig

This work presents several expected generalization error bounds based on the Wasserstein distance. More specifically, it introduces full-dataset, single-letter, and random-subset bounds, and their analogues in the randomized subsample…

Machine Learning · Statistics 2022-03-29 Borja Rodríguez-Gálvez , Germán Bassi , Ragnar Thobaben , Mikael Skoglund

We analyze the coupling of qubits mediated by a tunable and fast element beyond the adiabatic approximation. The nonadiabatic corrections are important and even dominant in parts of the relevant parameter range. As an example, we consider…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Carsten Hutter , Alexander Shnirman , Yuriy Makhlin , Gerd Schön

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

We present a straightforward formulation of Stein's method for the semicircular distribution, specifically designed for the analysis of non-commutative random variables. Our approach employs a non-commutative version of Stein's heuristic,…

Probability · Mathematics 2024-12-03 Mario Díaz , Arturo Jaramillo

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

Variance-Gamma distributions are widely used in financial modelling and contain as special cases the normal, Gamma and Laplace distributions. In this paper we extend Stein's method to this class of distributions. In particular, we obtain a…

Probability · Mathematics 2014-04-01 Robert E. Gaunt

Electron beams enable highly localized near-field excitation of waveguided optical modes, yet their coupling is typically limited by short interaction times along straight-line trajectories with fixed impact parameters. Here, we…

Mesoscale and Nanoscale Physics · Physics 2026-05-28 L. Prelat , S. Abdullah , C. I. Velasco , F. J. García de Abajo

We consider a geometrically frustrated spin-1/2 Ising-Heisenberg diamond chain, which is an exactly solvable model when assuming part of the exchange interactions as Heisenberg ones and another part as Ising ones. A small $XY$ part is…

Strongly Correlated Electrons · Physics 2015-12-16 Oleg Derzhko , Olesia Krupnitska , Bohdan Lisnyi , Jozef Strecka

This work introduces a new, explicit bound on the Hellinger distance between a continuous random variable and a Gaussian with matching mean and variance. As example applications, we derive a quantitative Hellinger central limit theorem and…

Probability · Mathematics 2025-09-23 Morgane Austern , Lester Mackey

We provide a new general theorem for multivariate normal approximation on convex sets. The theorem is formulated in terms of a multivariate extension of Stein couplings. We apply the results to a homogeneity test in dense random graphs and…

Probability · Mathematics 2016-08-14 Xiao Fang , Adrian Röllin

Benjamini, Burdzy and Chen (2007) introduced the notion of a shy coupling: a coupling of a Markov process such that, for suitable starting points, there is a positive chance of the two component processes of the coupling staying a positive…

Probability · Mathematics 2015-03-13 Wilfrid S. Kendall