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Whether turbulence intermittencies shall be described by a log-Poisson, a log-stable pdf or other distributions is still debated nowadays. In this paper, a bridge between polymer physics, self-avoiding walk and random vortex stretching is…

Fluid Dynamics · Physics 2015-05-14 Nicolas Rimbert

In the present paper we consider the varying coefficient model which represents a useful tool for exploring dynamic patterns in many applications. Existing methods typically provide asymptotic evaluation of precision of estimation…

Statistics Theory · Mathematics 2013-02-07 Olga Klopp , Marianna Pensky

The paper studies a higher-order diffusion model of Maxwell-Stefan kind. The model is based upon higher-order moment equations of kinetic theory of mixtures, which include viscous dissipation in the model. Governing equations are analyzed…

Analysis of PDEs · Mathematics 2023-05-16 Bérénice Grec , Srboljub Simic

A variational method is used to derive a self-consistent macro-particle model for relativistic electromagnetic kinetic plasma simulations. Extending earlier work [E. G. Evstatiev and B. A. Shadwick, J. Comput. Phys., vol. 245, pp. 376-398,…

Computational Physics · Physics 2014-04-22 A. B. Stamm , B. A. Shadwick , E. G. Evstatiev

Modelling multivariate tail dependence is one of the key challenges in extreme-value theory. Multivariate extremes are usually characterized using parametric models, some of which have simpler submodels at the boundary of their parameter…

Methodology · Statistics 2018-12-17 Anna Kiriliouk

Trapping macromolecules is impoartant for the study of their conformations, interactions, dynamics and kinetic processes. Here, we develop a variational approach which self-consistently introduces a mean force that controls the…

Soft Condensed Matter · Physics 2024-04-23 Luofu Liu , Chao Duan , Rui Wang

In this paper a multi-scale version of the Sherrington and Kirkpatrick model is introduced and studied. The pressure per particle in the thermodynamical limit is proved to obey a variational principle of Parisi type. The result is achieved…

Mathematical Physics · Physics 2019-02-20 Pierluigi Contucci , Emanuele Mingione

We review some recent coarse-graining and multi-scale methods, but also put forward some new ideas for addressing such issues. We find that, if one is guided by nonequilibrium statistical mechanics and thermodynamics, it is possible to…

Soft Condensed Matter · Physics 2009-11-06 Patrick Ilg , Vlasis Mavrantzas , Hans Christian Öttinger

Mixture models are widely used in Bayesian statistics and machine learning, in particular in computational biology, natural language processing and many other fields. Variational inference, a technique for approximating intractable…

Statistics Theory · Mathematics 2020-08-03 Badr-Eddine Chérief-Abdellatif , Pierre Alquier

The existence and the regularity results obtained in [37] for the variational model introduced in [36] to study the optimal shape of crystalline materials in the setting of stress-driven rearrangement instabilities (SDRI) are extended from…

Analysis of PDEs · Mathematics 2026-01-29 Shokhrukh Kholmatov , Paolo Piovano

The well-known Hill's averaging theorems for stresses and strains as well as the so-called Hill-Mandel principle of macrohomogeneity are essential ingredients for the coupling and the consistency between the micro and macro scales in…

Materials Science · Physics 2016-06-29 Chenchen Liu , Celia Reina

Predicting extreme events is important in many applications in risk analysis. The extreme-value theory suggests modelling extremes by max-stable distributions. The Bayesian approach provides a natural framework for statistical prediction.…

Statistics Theory · Mathematics 2020-09-22 Simone A. Padoan , Stefano Rizzelli

Using the superstatistics method, we propose an extension of the random matrix theory to cover systems with mixed regular-chaotic dynamics. Unlike most of the other works in this direction, the ensembles of the proposed approach are basis…

Statistical Mechanics · Physics 2007-05-23 A. Y. Abul-Magd

Max-stable processes have proved to be useful for the statistical modelling of spatial extremes. Several representations of max-stable random fields have been proposed in the literature. For statistical inference it is often assumed that…

Methodology · Statistics 2011-07-25 Richard A. Davis , Claudia Klüppelberg , Christina Steinkohl

A simple analytical model of intergranular normal stresses is proposed for a general elastic polycrystalline material with arbitrary shaped and randomly oriented grains under uniform loading. The model provides algebraic expressions for the…

Materials Science · Physics 2023-04-21 Samir El Shawish , Timon Mede

Multivariate extreme-value analysis is concerned with the extremes in a multivariate random sample, that is, points of which at least some components have exceptionally large values. Mathematical theory suggests the use of max-stable models…

Probability · Mathematics 2012-04-03 Johan Segers

The stability of convection rolls in a fluid heated from below is limited by secondary instabilities, including the skew-varicose and crossroll instabilities. We observe a stability boundary defined by the same instabilities in stripe…

In the fiber melt spinning of semi-crystalline polymers, the degree of crystallization can be non-homogeneous over the cross-section of the fiber, affecting the properties of the end product. For simulation-based process design, the…

Fluid Dynamics · Physics 2024-07-12 Manuel Ettmüller , Walter Arne , Nicole Marheineke , Raimund Wegener

We address combinatorial problems that can be formulated as minimization of a partially separable function of discrete variables (energy minimization in graphical models, weighted constraint satisfaction, pseudo-Boolean optimization, 0-1…

Computer Vision and Pattern Recognition · Computer Science 2015-05-05 Alexander Shekhovtsov

In this paper, we begin our discussion with some of the well-known methods available in the literature for the estimation of the parameters of a univariate/multivariate stable distribution. Based on the available methods, a new hybrid…

Computation · Statistics 2019-02-27 Aastha M. Sathe , Neelesh. S. Upadhye