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Paradoxically, while the assumptions of second-order stationarity and isotropy appear outdated in light of modern spatial data, they remain remarkably robust in practice, as nonstationary methods often provide marginal improvements in…

Methodology · Statistics 2025-11-07 Federico Blasi , Reinhard Furrer

We generalize McDiarmid's inequality for functions with bounded differences on a high probability set, using an extension argument. Those functions concentrate around their conditional expectations. We further extend the results to…

Machine Learning · Computer Science 2024-05-03 Richard Combes

This paper contains a study of multivariate second order stochastic mappings indexed by an abstract set $\Lambda$ in close connection to their operator covariance functions. The characterizations of the normal Hilbert module or of Hilbert…

Functional Analysis · Mathematics 2015-01-27 Pastorel Gaspar , Lorena Popa

We study the nodal properties of many-body eigenstates of stationary Schr\"odinger equation that affect the accuracy of real-space quantum Monte Carlo calculations. In particular, we introduce weighted nodal domain averages that provide a…

Computational Physics · Physics 2022-03-14 Lubos Mitas , Abdulgani Annaberdiyev

In this paper our aim is to present some monotonicity and convexity properties for the one dimensional regularization of the Coulomb potential, which has applications in the study of atoms in magnetic fields and which is in fact a…

Classical Analysis and ODEs · Mathematics 2013-08-19 Árpád Baricz , Tibor K. Pogány

This paper is devoted to optimal functional inequalities for fractional Laplace operators on the sphere. Based on spectral properties, subcritical inequalities are established. Their consequences for fractional heat flows are considered.…

Analysis of PDEs · Mathematics 2016-10-07 Jean Dolbeault , An Zhang

This paper is a follow up to an article by two of the authors dedicated to the study of Poincar\'e and logarithmic Sobolev inequalities for measures of the form $d\mu = e^{-U} d\nu$ where $e^{-U}$ is seen as a perturbation of $d\nu$.…

Probability · Mathematics 2026-03-10 Patrick Cattiaux , Paula Cordero-Encinar , Arnaud Guillin

In this note we investigate the multi-parameter Potential Theory on the weighted $d$-tree (Cartesian product of several copies of uniform dyadic tree), which is connected to the discrete models of weighted Dirichlet spaces on the polydisc.…

Complex Variables · Mathematics 2018-11-06 Nicola Arcozzi , Pavel Mozolyako , Karl-Mikael Perfekt

We introduce extremal affine surface areas in a functional setting. We show their main properties. Among them are linear invariance, isoperimetric inequalities and monotonicity properties. We establish a new duality formula, which shows…

Metric Geometry · Mathematics 2024-02-27 Stephanie Egler , Elisabeth M. Werner

It has been observed that an interesting class of non-Gaussian stationary processes is obtained when in the harmonics of a signal with random amplitudes and phases, frequencies can also vary randomly. In the resulting models, the…

Probability · Mathematics 2019-11-19 Anastassia Baxevani , Krzysztof Podgórski

This paper presents asymptotic covariance formulae and central limit theorems for geometric functionals, including volume, surface area, and all Minkowski functionals and translation invariant Minkowski tensors as prominent examples, of…

Probability · Mathematics 2016-02-03 Daniel Hug , Michael A. Klatt , Günter Last , Matthias Schulte

Multivariate max-stable processes are important for both theoretical investigations and various statistical applications motivated by the fact that these are limiting processes, for instance of stationary multivariate regularly varying time…

Probability · Mathematics 2021-02-16 Enkelejd Hashorva , Alfred Kume

We prove generalizations of the Poincare and logarithmic Sobolev inequalities corresponding to the case of fractional derivatives in measure spaces with only a minimal amount of geometric structure. The class of such spaces includes (but is…

Classical Analysis and ODEs · Mathematics 2012-05-28 Philip T. Gressman

We consider systems of stochastic differential equations with multiple scales and small noise and assume that the coefficients of the equations are ergodic and stationary random fields. Our goal is to construct provably-efficient importance…

Probability · Mathematics 2015-09-29 Konstantinos Spiliopoulos

Based on the homogeneity ($F[n_{\lambda m}]=\lambda^{p(m)}F[n]$) and invariance ($F[n_{\lambda m_0}]=F[n]$) properties of a functional of the electron density under uniform scaling of the coordinates in the density $n_{\lambda…

Mathematical Physics · Physics 2014-10-16 Lázaro Calderín

This work explores new deep connections between John-Nirenberg type inequalities and Muckenhoupt weight invariance for a large class of $BMO$-type spaces. The results are formulated in a very general framework in which $BMO$ spaces are…

Functional Analysis · Mathematics 2017-07-06 Jarod Hart , Rodolfo H. Torres

In this work we deal with the stochastic homogenization of the initial boundary value problems of monotone type. The models of monotone type under consideration describe the deformation behaviour of inelastic materials with a microstructure…

Analysis of PDEs · Mathematics 2017-01-16 Martin Heida , Sergiy Nesenenko

Recently, based on the method of collective variables the statistical field theory for multicomponent inhomogeneous systems was formulated [O. Patsahan, I. Mryglod, J.-M. Caillol, Journal of Physical Studies, 2007, 11, 133]. In this letter…

Statistical Mechanics · Physics 2012-07-13 O. Patsahan , I. Mryglod

We consider various inequalities for polynomials, with an emphasis on the most fundamental inequalities of approximation theory. In the sequel a key role is played by the generalized Minkowski functional \alpha(K,x), already being used by…

Classical Analysis and ODEs · Mathematics 2007-05-23 Szilard Gy. Revesz

We derive novel concentration inequalities that bound the statistical error for a large class of stochastic optimization problems, focusing on the case of unbounded objective functions. Our derivations utilize the following key tools: 1) A…

Machine Learning · Statistics 2026-01-01 Jeremiah Birrell