中文
相关论文

相关论文: Extreme value statistics of work done in stretchin…

200 篇论文

Multivariate extreme value statistical analysis is concerned with observations on several variables which are thought to possess some degree of tail-dependence. In areas such as the modeling of financial and insurance risks, or as the…

应用统计 · 统计学 2014-12-31 Alexis Bienvenüe , Christian Y. Robert

Sampling a target probability distribution with an unknown normalization constant is a fundamental challenge in computational science and engineering. Recent work shows that algorithms derived by considering gradient flows in the space of…

机器学习 · 统计学 2024-03-12 Yifan Chen , Daniel Zhengyu Huang , Jiaoyang Huang , Sebastian Reich , Andrew M Stuart

The stretching of brushes of long polymers grafted to a planar surface is investigated byMonte Carlo simulations in the limit of very high grafting densities, as achieved in recent experiments. The monomer density profiles are shown to…

软凝聚态物质 · 物理学 2009-11-13 Ivan Coluzza , Jean-Pierre Hansen

In this paper we develop a statistical theory and an implementation of deep learning models. We show that an elegant variable splitting scheme for the alternating direction method of multipliers optimises a deep learning objective. We allow…

机器学习 · 统计学 2015-09-22 Nicholas G. Polson , Brandon T. Willard , Massoud Heidari

In this paper we characterize the limiting behavior of sums of extreme values of long range dependent sequences defined as functionals of linear processes with finite variance. The extremal sums behave completely different by compared to…

概率论 · 数学 2007-06-13 Rafal Kulik

We compute analytically the probability distribution function ${\cal P}(\epsilon)$ of the dissipation field $\epsilon =(\nabla \theta)^{2}$ of a passive scalar $\theta$ advected by a $d$-dimensional random flow, in the limit of large Peclet…

chao-dyn · 物理学 2015-06-24 A. Gamba , I. V. Kolokolov

We derive a systematic, multiple time-scale perturbation expansion for the work distribution in isothermal quasi-static Langevin processes. To first order we find a Gaussian distribution reproducing the result of Speck and Seifert [Phys.…

统计力学 · 物理学 2015-06-15 Johannes Hoppenau , Andreas Engel

We study numerically the distributions of the length $L$ of the longest increasing subsequence (LIS) for the two cases of random permutations and of one-dimensional random walks. Using sophisticated large-deviation algorithms, we are able…

无序系统与神经网络 · 物理学 2019-04-05 Jörn Börjes , Hendrik Schawe , Alexander K. Hartmann

We develop a general mathematical framework to analyze scaling regimes and derive explicit analytic solutions for gradient flow (GF) in large learning problems. Our key innovation is a formal power series expansion of the loss evolution,…

机器学习 · 计算机科学 2026-02-05 Dmitry Yarotsky , Eugene Golikov , Yaroslav Gusev

Large-deviations theory deals with tails of probability distributions and the rare events of random processes, for example spreading packets of particles. Mathematically, it concerns the exponential fall-of of the density of thin-tailed…

统计力学 · 物理学 2017-07-04 Erez Aghion , David A. Kessler , Eli Barkai

The transitional and well-developed regimes of turbulent shear flows exhibit a variety of remarkable scaling laws that are only now beginning to be systematically studied and understood. In the first part of this article, we summarize…

流体动力学 · 物理学 2017-01-04 Nigel Goldenfeld , Hong-Yan Shih

The stretching of a polymer chain by a large scale chaotic flow is considered. The steady state which emerges as a balance of the turbulent stretching and anharmonic resistance of the chain is quantitatively described, i.e. the dependency…

chao-dyn · 物理学 2009-10-31 Michael Chertkov

We report on an investigation of the vertical transport of tracer particles released within a shallow, continuously-forced flow by means of numerical simulations. The investigation is motivated by the shallow flows encountered in many…

We formulate large deviations principle (LDP) for diffusion pair $(X^\epsilon,\xi^\epsilon)=(X_t^\epsilon,\xi_t^\epsilon)$, where first component has a small diffusion parameter while the second is ergodic Markovian process with fast time.…

概率论 · 数学 2007-05-23 R. Liptser

We give bounds on the distribution and fragmentation functions that appear at leading order in deep inelastic 1-particle inclusive leptoproduction or in Drell-Yan processes. These bounds simply follow from positivity of the defining matrix…

高能物理 - 唯象学 · 物理学 2011-07-19 A. Bacchetta , M. Boglione , A. Henneman , P. J. Mulders

We propose a transformation capable of altering the tail properties of a distribution, motivated by extreme value theory, which can be used as a layer in a normalizing flow to approximate multivariate heavy tailed distributions. We apply…

机器学习 · 统计学 2023-11-02 Tennessee Hickling , Dennis Prangle

We present event distributions for the polymer translocation obtained by extensive Langevin dynamics simulations. Such distributions have not been reported previously and they provide new understanding of the stochastic characteristics of…

软凝聚态物质 · 物理学 2012-04-13 R. P. Linna , K. Kaski

Motivation: Although there is a rich literature on methods for assessing the impact of functional predictors, the focus has been on approaches for dimension reduction that can fail dramatically in certain applications. Examples of standard…

统计方法学 · 统计学 2018-07-13 Willem van den Boom , Callie Mao , Rebecca A. Schroeder , David B. Dunson

We consider the single-particle velocity distribution of a one-dimensional fluid of inelastic particles. Both the freely evolving (cooling) system and the non-equilibrium stationary state obtained in the presence of random forcing are…

统计力学 · 物理学 2009-11-07 A. Barrat , T. Biben , Z. Racz , E. Trizac , F. van Wijland

Forced detachment of a single polymer chain, strongly-adsorbed on a solid substrate, is investigated by two complementary methods: a coarse-grained analytical dynamical model, based on the Onsager stochastic equation, and Molecular Dynamics…

软凝聚态物质 · 物理学 2014-03-27 J. Paturej , J. L. A. Dubbeldam , V. G. Rostiashvili , A. Milchev , T. A. Vilgis