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In this paper, we establish a large deviation principle for the conservative stochastic partial differential equations, whose solutions are related to stochastic differential equations with interaction. The weak convergence method and the…

Probability · Mathematics 2023-07-13 Ping Chen , Tusheng Zhang

We explore a systematic approach to studying the dynamics of evolving networks at a coarse-grained, system level. We emphasize the importance of finding good observables (network properties) in terms of which coarse grained models can be…

In the former article "Formal mathematical systems including a structural induction principle" we have presented a unified theory for formal mathematical systems including recursive systems closely related to formal grammars, including the…

Logic · Mathematics 2022-01-21 Matthias Kunik

A fundamental question in nonequilibrium statistical physics is whether effective equilibrium behavior can emerge at coarse-grained scales in strongly driven systems. Here, we investigate this question in the context of human mobility by…

Physics and Society · Physics 2026-03-24 Lei Dong

Biological systems exhibit processes on a wide range of time and length scales. This work demonstrates that models, wherein the interaction between system constituents is captured by algebraic operations, inherently allow for successive…

Molecular Networks · Quantitative Biology 2019-08-16 Dimitri Loutchko

We consider a fractional generalization of gradient systems. We use differential forms and exterior derivatives of fractional orders. Examples of fractional gradient systems are considered. We describe the stationary states of these…

Chaotic Dynamics · Physics 2015-06-26 Vasily E. Tarasov

We develop a formalism to discuss the properties of GENERIC systems in terms of corresponding Hamiltonians that appear in the characterization of large-deviation limits. We demonstrate how the GENERIC structure naturally arises from a…

Analysis of PDEs · Mathematics 2020-03-31 Richard C. Kraaij , Alexandre Lazarescu , Christian Maes , Mark A. Peletier

Coarse-graining is central to reducing dimensionality in molecular dynamics, and is typically characterized by a mapping which projects the full state of the system to a smaller class of variables. While extensive literature has been…

Probability · Mathematics 2020-01-08 Frédéric Legoll , Tony Lelièvre , Upanshu Sharma

We consider generalized gradients in the general context of $G$-structures. They are natural first order differential operators acting on sections of vector bundles associated to irreducible $G$-representations. We study their geometric…

Differential Geometry · Mathematics 2009-08-18 Mihaela Pilca

We introduce a stochastic particle system that corresponds to the Fokker-Planck equation with decay in the many-particles limit, and study its large deviations. We show that the large-deviation rate functional corresponds to an…

Analysis of PDEs · Mathematics 2013-03-08 Mark Peletier , Michiel Renger , Marco Veneroni

A classic approach in dynamical systems is to use particular geometric structures to deduce statistical properties, for example the existence of invariant measures with stochastic-like behaviour such as large deviations or decay of…

Dynamical Systems · Mathematics 2012-09-14 José F. Alves , Jorge Milhazes Freitas , Stefano Luzzatto , Sandro Vaienti

The common idea behind complexity reduction in physical systems is separation of information into "physically meaningful" and "safely ignorable". Here we consider a generic notion of such separation -- implemented by coarse-graining the…

Quantum Physics · Physics 2018-06-04 Oleg Kabernik

For driven open systems in contact with multiple heat reservoirs, we find the marginal distributions of work or heat do not satisfy any fluctuation theorem, but only the joint distribution of work and heat satisfies a family of fluctuation…

Statistical Mechanics · Physics 2023-03-08 Jin-Fu Chen , H. T. Quan

Understanding the structure and dynamics of liquids is pivotal for the study of larger spatiotemporal processes, especially in glass-forming materials at low temperatures. Density scaling, observed in many molecular systems through…

Soft Condensed Matter · Physics 2024-10-29 Jaehyeok Jin , David R. Reichman , Jeppe C. Dyre , Ulf R. Pedersen

Mixing grains with different properties is a remarkably challenging process, relevant to many industrial applications. Rotating drums have been used extensively as model systems to study granular media flow and mixing and segregation.…

Soft Condensed Matter · Physics 2018-09-05 Claudia Piacenza , Marco Marconati , Colin Hare , Andrea C. Santomaso , Marco Ramaioli

A fuzzy observable is regarded as a smearing of a sharp observable, and the structure of covariant fuzzy observables is studied. It is shown that the covariant coarse-grainings of sharp observables are exactly the covariant fuzzy…

Quantum Physics · Physics 2009-11-10 T. Heinonen , P. Lahti , K. Ylinen

Data-based discovery of effective, coarse-grained (CG) models of high-dimensional dynamical systems presents a unique challenge in computational physics and particularly in the context of multiscale problems. The present paper offers a…

Computational Physics · Physics 2020-08-26 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis

A general mean field theory is presented for the construction of equilibrium coarse grained models. Inverse methods that reconstruct microscopic models from low resolution experimental data can be derived as particular implementations of…

Statistical Mechanics · Physics 2010-07-13 Luca Larini , Vinod Krishna

We poorly understand the macroscopic properties of complex fluids and of amorphous bodies in general. This is mainly due to the interplay between phenomena at different levels and length-scales. In particular, it is not necessarily true…

Soft Condensed Matter · Physics 2010-04-14 Alessio Zaccone

In this study the general formula for differential and integral operations of fractional calculus via fractal operators by the method of cumulative diminution and cumulative growth is obtained. The under lying mechanism in the success of…

Statistical Mechanics · Physics 2016-08-31 Fevzi Buyukkilic , Zahide Ok Bayrakdar , Dogan Demirhan