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We derive the limiting distributions of exceedances point processes of randomly scaled weakly dependent stationary Gaussian sequences under some mild asymptotic conditions. In the literature analogous results are available only for…

Probability · Mathematics 2013-10-22 Enkelejd Hashorva , Zuoxiang Peng , Zhichao Weng

A discrete gradient model for interfaces is studied. The interaction potential is a non-convex perturbation of the quadratic gradient potential. Based on a representation for the finite volume Gibbs measure obtained via a renormalization…

Mathematical Physics · Physics 2016-03-16 Susanne Hilger

We prove a central limit theorem for strictly stationary random fields under a sharp projective condition. The assumption was introduced in the setting of random variables by Maxwell and Woodroofe. Our approach is based on new results for…

Probability · Mathematics 2017-08-29 Magda Peligrad , Na Zhang

We consider the discrete Gaussian Free Field (DGFF) in scaled-up (square-lattice) versions of suitably regular continuum domains $D\subset\mathbb C$ and describe the scaling limit, including local structure, of the level sets at heights…

Probability · Mathematics 2020-01-06 Marek Biskup , Oren Louidor

Finite size fluctuations are a crucial ingredient in kinetic theory of long-range interacting collisionless systems. In this Letter, we introduce a phenomenological theory which predicts an anomalous scaling close to marginal stability for…

Statistical Mechanics · Physics 2026-03-19 Yoshiyuki Y. Yamaguchi , Julien Barré

Let $X(t), t\in \mathcal{T}$ be a centered Gaussian random field with variance function $\sigma^2(\cdot)$ that attains its maximum at the unique point $t_0\in \mathcal{T}$, and let $M(\mathcal{T}):=\sup_{t\in \mathcal{T}} X(t)$. For…

Probability · Mathematics 2016-05-31 Krzyztof Dębicki , Enkelejd Hashorva , Peng Liu

We consider a continuous-time random walk which is the generalization, by means of the introduction of waiting periods on sites, of the one-dimensional nonhomogeneous random walk with a position-dependent drift known in the mathematical…

Statistical Mechanics · Physics 2021-10-25 Gaia Pozzoli , Mattia Radice , Manuele Onofri , Roberto Artuso

Current statistics literature on statistical inference of random fields typically assumes that the fields are stationary or focuses on models of non-stationary Gaussian fields with parametric/semiparametric covariance families, which may…

Statistics Theory · Mathematics 2024-09-04 Yunyi Zhang , Zhou Zhou

In principle, observables as for example the sphaleron rate or the tunneling rate in a first-order phase transition are gauge-independent. However, in practice a gauge dependence is introduced in explicit perturbative calculations due to…

High Energy Physics - Phenomenology · Physics 2012-08-09 Mathias Garny , Thomas Konstandin

I discuss the so-called stochastic individual based model of adaptive dynamics and in particular how different scaling limits can be obtained by taking limits of large populations, small mutation rate, and small effect of single mutations…

Populations and Evolution · Quantitative Biology 2021-07-06 Anton Bovier

Recently, self-dualities based on saddle-point expansions have been proposed as a means to obtain qualitative non-perturbative information in scalar field theories. In this work, we test this proposition quantitatively by studying the phase…

High Energy Physics - Theory · Physics 2026-05-12 Paul Romatschke , Ulrike Romatschke

We consider the problem of model selection in Gaussian Markov fields in the sample deficient scenario. In many practically important cases, the underlying networks are embedded into Euclidean spaces. Using the natural geometric structure,…

Machine Learning · Statistics 2018-10-31 Ilya Soloveychik , Vahid Tarokh

A momentum dependent projection of the Wegner-Hougton equation is derived for a scalar theory coupled to an external field. This formalism is useful to discuss the phase diagram of the theory. In particular we study some properties of the…

High Energy Physics - Theory · Physics 2009-10-30 A. Bonanno , D. Zappala'

We study a class of discrete-time random walks in $\mathbb{R}^d$ whose conditional drift decays polynomially in time and grows polynomially with the distance from the origin to the current position. This class is related to several models…

Probability · Mathematics 2026-05-19 Ngo P. N. Ngoc , Tuan-Minh Nguyen

We have defined pinning fields as those random fields that keep some of the magnetic moments unreversed in the region of negative external applied field during the demagnetizing process. An analysis of the statistical properties of such…

Disordered Systems and Neural Networks · Physics 2009-11-11 Xavier Illa , Eduard Vives

We construct a natural discrete random field on $\mathbb{Z}^{d}$, $d\geq 5$ that converges weakly to the bi-Laplacian Gaussian field in the scaling limit. The construction is based on assigning i.i.d. Bernoulli random variables on each…

Probability · Mathematics 2013-12-03 Xin Sun , Wei Wu

The extreme value dependence of regularly varying stationary time series can be described by the spectral tail process. Drees, Segers and Warchol [Extremes 18(3): 369--402, 2015] proposed estimators of the marginal distributions of this…

Statistics Theory · Mathematics 2019-07-23 Holger Drees , Miran Knezevic

Compact stars above a critical stellar mass develop large scalar fields in some scalar-tensor theories. This scenario, called spontaneous scalarization, has been an intense topic of study since it passes weak-field gravity tests naturally…

General Relativity and Quantum Cosmology · Physics 2025-08-07 Kıvanç İ. Ünlütürk , Semih Tuna , Oğuzhan K. Yamak , Fethi M. Ramazanoğlu

We show that the critical scaling behavior of random-field systems with short-range interactions and disorder correlations cannot be described in general by only two independent exponents, contrary to previous claims. This conclusion is…

Disordered Systems and Neural Networks · Physics 2015-06-15 Gilles Tarjus , Ivan Balog , Matthieu Tissier

In the statistical inference for long range dependent time series the shape of the limit distribution typically depends on unknown parameters. Therefore, we propose to use subsampling. We show the validity of subsampling for general…

Statistics Theory · Mathematics 2016-10-20 Annika Betken , Martin Wendler