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For Markov processes evolving on multiple time-scales a combination of large component scalings and averaging of rapid fluctuations can lead to useful limits for model approximation. A general approach to proving a law of large numbers to a…

Probability · Mathematics 2020-12-29 Lea Popovic

Large and moderate deviation principles are proved for Engel continued fractions, a new type of continued fraction expansion with non-decreasing partial quotients in number theory.

Probability · Mathematics 2016-08-29 Lulu Fang , Lei Shang

In this paper we discuss the connections between a Vlasov-Fokker-Planck equation and an underlying microscopic particle system, and we interpret those connections in the context of the GENERIC framework (\"Ottinger 2005). This…

Analysis of PDEs · Mathematics 2015-06-12 Manh Hong Duong , Mark A. Peletier , Johannes Zimmer

Based on a nonsmooth coherence condition, we construct and prove the convergence of a forward-backward splitting method that alternates between steps on a fine and a coarse grid. Our focus is a total variation regularised inverse imaging…

Optimization and Control · Mathematics 2025-05-21 Felipe Guerra , Tuomo Valkonen

We present a simple model to account for the rheological behavior observed in recent experiments on micellar gels. The model combines attachment-detachment kinetics with stretching due to shear, and shows well-defined jammed and flowing…

Statistical Mechanics · Physics 2013-02-19 Saroj Kumar Nandi , Bulbul Chakraborty , A. K. Sood , Sriram Ramaswamy

We examine two basic assumptions of kinetic theory-- binary collisions and molecular chaos-- using numerical simulations of sheared granular materials. We investigate a wide range of densities and restitution coefficients and demonstrate…

Soft Condensed Matter · Physics 2015-06-25 Gregg Lois , Anael Lemaitre , Jean M. Carlson

Advances in statistical learning theory have resulted in a multitude of different designs of learning machines. But which ones are implemented by brains and other biological information processors? We analyze how various abstract Bayesian…

Neurons and Cognition · Quantitative Biology 2007-05-23 Ilya Nemenman

Motivated by the wide range of applicability of the fluctuation and dissipation phenomena in non-equilibrium systems, we provide a universal study scheme for the dissipation of the energy and the corresponding Brownian motion analysis of…

High Energy Physics - Theory · Physics 2018-09-26 Dimitrios Giataganas , Da-Shin Lee , Chen-Pin Yeh

We study small noise large deviation asymptotics for stochastic differential equations with a multiplicative noise given as a fractional Brownian motion $B^H$ with Hurst parameter $H>\frac12$. The solutions of the stochastic differential…

Probability · Mathematics 2020-06-18 Amarjit Budhiraja , Xiaoming Song

The link between Tauberian theorems and large deviations is surveyed, with particular reference to regular variation.

Probability · Mathematics 2008-01-03 N. H. Bingham

For a fractional Brownian motion $B^H$ with Hurst parameter $H\in]{1/4},{1/2}[\cup]{1/2},1[$, multiple indefinite integrals on a simplex are constructed and the regularity of their sample paths are studied. Then, it is proved that the…

Probability · Mathematics 2007-05-23 Marta Sanz-Solé , Iván Torrecilla-Tarantino

Using the Naimark dilation theory we investigate the question under what conditions an observable which is a coarse graining of another observable is a function of it. To this end, conditions for the separability and for the Boolean…

Quantum Physics · Physics 2009-11-10 A. Dvurecenskij , P. Lahti , S. Pulmannova , K. Ylinen

This work explores the manner in which classical phase space distribution functions converge to the microcanonical distribution. We first prove a theorem about the lack of convergence, then define a generalization of the coarse-graining…

Statistical Mechanics · Physics 2024-08-26 Casey O. Barkan

Coarse-graining or model reduction is a term describing a range of approaches used to extend the time-scale of molecular simulations by reducing the number of degrees of freedom. In the context of molecular simulation, standard…

Dynamical Systems · Mathematics 2023-11-14 Thomas Hudson , Xingjie Helen Li

We consider some possible approaches to the fractional-order generalization of definition of variation (functional) derivative. Some problems of formulation of a fractional-order variational derivative are discussed. To give a consistent…

Classical Analysis and ODEs · Mathematics 2015-02-27 Vasily E. Tarasov

Given a fine-scale physical theory characterized by an evolutionary system of equations and a set of quantities, defined from the variables of the fine theory, that serve as a coarse representation of the fine scale phenomena, a systematic…

Statistical Mechanics · Physics 2007-05-23 Amit Acharya

In this short note we consider semi-Markov processes satisfying the condition of direction-time independence (Markov renewal processes). We derive large deviation principles and fluctuation theorems for the empirical current and the…

Statistical Mechanics · Physics 2017-09-19 A. Faggionato

The existing fractional grey prediction models mainly use discrete fractional-order difference and accumulation, but in the actual modeling, continuous fractional-order calculus has been proved to have many excellent properties, such as…

General Mathematics · Mathematics 2020-10-28 Wanli Xie , Caixia Liu , Weidong Li , Wenze Wu , Chong Liu

After reviewing the Lagrangian-Hamiltonian unified formalism (i.e, the Skinner-Rusk formalism) for higher-order (non-autonomous) dynamical systems, we state a unified geometrical version of the Variational Principles which allows us to…

Mathematical Physics · Physics 2014-01-16 Pedro D. Prieto-Martínez , Narciso Román-Roy

We prove a large deviation principle for stochastic differential equations driven by semimartingales, with additive controls. Conditions are given in terms of characteristics of driven semimartingales, so that if the noise-control pairs…

Probability · Mathematics 2024-08-13 Qiao Huang , Wei Wei , Jinqiao Duan