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We use the conformal bootstrap program to derive necessary conditions for emergent symmetry enhancement from discrete symmetry (e.g. $\mathbb{Z}_n$) to continuous symmetry (e.g. $U(1)$) under the renormalization group flow. In three…

Strongly Correlated Electrons · Physics 2016-09-28 Yu Nakayama , Tomoki Ohtsuki

A constructive numerical approximation of the two-dimensional unsteady stochastic Navier-Stokes equations of an incompressible fluid is proposed via a pseudo-compressibility technique involving a parameter $\epsilon$. Space and time are…

Numerical Analysis · Mathematics 2022-05-02 Jad Doghman

We show, how the classical Berry-Esseen theorem for normal approximation may be used to derive rates of convergence for random sums of centerd, real-valued random variables with respect to a certain class of probability metrics, including…

Probability · Mathematics 2012-12-24 Christian Döbler

This paper develops the large deviations theory for the point process associated with the Euclidean volume of $k$-nearest neighbor balls centered around the points of a homogeneous Poisson or a binomial point processes in the unit cube. Two…

Probability · Mathematics 2022-10-25 Christian Hirsch , Taegyu Kang , Takashi Owada

Laplace's method approximates a target density with a Gaussian distribution at its mode. It is computationally efficient and asymptotically exact for Bayesian inference due to the Bernstein-von Mises theorem, but for complex targets and…

Machine Learning · Computer Science 2026-03-12 Hanlin Yu , Marcelo Hartmann , Bernardo Williams , Mark Girolami , Arto Klami

This article introduces and studies the tight approximation property, a property of algebraic varieties defined over the function field of a complex or real curve that refines the weak approximation property (and the known cohomological…

Algebraic Geometry · Mathematics 2024-06-18 Olivier Benoist , Olivier Wittenberg

We consider a sequence of approximate solutions to the compressible Euler system admitting uniform energy bounds and/or satisfying the relevant field equations modulo an error vanishing in the asymptotic limit. We show that such a sequence…

Analysis of PDEs · Mathematics 2020-01-03 Eduard Feireisl , Martina Hofmanová

Although much progress has been made in the theory and application of bootstrap approximations for max statistics in high dimensions, the literature has largely been restricted to cases involving light-tailed data. To address this issue, we…

Methodology · Statistics 2025-12-24 Mingshuo Liu , Miles E. Lopes

Using lattice approximations of Euclidean space, we develop a way to approximate stable processes that are represented by stochastic integrals over Euclidean space. Via a stable version of the Lindeberg-Feller Theorem we show that the…

Probability · Mathematics 2013-02-19 Clément Dombry , Paul Jung

We consider the problem of computing the Euler characteristic of an abstract simplicial complex given by its vertices and facets. We show that this problem is #P-complete and present two new practical algorithms for computing Euler…

Computational Geometry · Computer Science 2011-12-21 Bjarke Hammersholt Roune , Eduardo Sáenz de Cabezón

We consider distributional approximation by generalized Dickman distributions, which appear in number theory, perpetuities, logarithmic combinatorial structures and many other areas. We prove bounds in the Kolmogorov distance for the…

Probability · Mathematics 2022-11-21 Chinmoy Bhattacharjee , Matthias Schulte

The metric tensor of a Riemannian manifold can be approximated using Regge finite elements and such approximations can be used to compute approximations to the Gauss curvature and the Levi-Civita connection of the manifold. It is shown that…

Numerical Analysis · Mathematics 2024-02-14 Jay Gopalakrishnan , Michael Neunteufel , Joachim Schöberl , Max Wardetzky

Particle island models (Verg\'e et al., 2013) provide a means of parallelization of sequential Monte Carlo methods, and in this paper we present novel convergence results for algorithms of this sort. In particular we establish a central…

Computation · Statistics 2017-02-27 Pierre Del Moral , Eric Moulines , Jimmy Olsson , Christelle Vergé

The Bonferroni adjustment, or the union bound, is commonly used to study rate optimality properties of statistical methods in high-dimensional problems. However, in practice, the Bonferroni adjustment is overly conservative. The extreme…

Methodology · Statistics 2020-01-13 Hang Deng , Cun-Hui Zhang

We describe how to approximate the Riemann curvature tensor as well as sectional curvatures on possibly infinite-dimensional shape spaces that can be thought of as Riemannian manifolds. To this end, we extend the variational time…

Numerical Analysis · Mathematics 2019-12-17 Alexander Effland , Behrend Heeren , Martin Rumpf , Benedikt Wirth

For a class of stochastic models with Gaussian and rough mean-reverting volatility that embeds the genuine rough Stein-Stein model, we study the weak approximation rate when using a Euler type scheme with integrated kernels. Our first…

Probability · Mathematics 2026-02-23 Aurélien Alfonsi , Ahmed Kebaier

Due to extreme difficulties in numerical simulations of Euler-Maxwell equations, which are caused by the highly complicated structures of the equations, this paper concerns the simplification of Euler-Maxwell system through the…

Analysis of PDEs · Mathematics 2023-12-13 Rui Jin , Yachun Li , Liang Zhao

We construct new testing procedures for spherical and elliptical symmetry based on the characterization that a random vector $X$ with finite mean has a spherical distribution if and only if $\Ex[u^\top X | v^\top X] = 0$ holds for any two…

Statistics Theory · Mathematics 2020-04-29 Isaia Albisetti , Fadoua Balabdaoui , Hajo Holzmann

We consider the problem of the approximation of the solution of a one-dimensional SDE with non-globally Lipschitz drift and diffusion coefficients behaving as $x^\alpha$, with $\alpha>1$. We propose an (semi-explicit) exponential-Euler…

Probability · Mathematics 2022-11-30 Mireille Bossy , Jean Francois Jabir , Kerlyns Martinez

We consider upper bounds for the approximation error E|g(X)-g(\hat X)|^p, where X and \hat X are random variables such that \hat X is an approximation of X in the L_p-norm, and the function g belongs to certain function classes, which…

Probability · Mathematics 2007-12-24 Rainer Avikainen
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