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A large deviations principle is established for the joint law of the empirical measure and the flow measure of a renewal Markov process on a finite graph. We do not assume any bound on the arrival times, allowing heavy tailed distributions.…

Probability · Mathematics 2014-02-18 Mauro Mariani , Lorenzo Zambotti

The electoral college of voting system for the US presidential election is analogous to a coarse graining procedure commonly used to study phase transitions in physical systems. In a recent paper, opinion dynamics models manifesting a phase…

Physics and Society · Physics 2020-12-22 Kathakali Biswas , Soumyajyoti Biswas , Parongama Sen

The emergence of macroscopic variables can be effected through {\it coarse graining}. Despite practical and fundamental benefits conveyed by this partitioning of state space, the apparently subjective nature of the selection of coarse…

Statistical Mechanics · Physics 2016-08-31 L. S. Schulman , B. Gaveau

We propose to employ the hierarchical coarse-grained structure in the artificial neural networks explicitly to improve the interpretability without degrading performance. The idea has been applied in two situations. One is a neural network…

Machine Learning · Computer Science 2024-06-19 Xi-Ci Yang , Z. Y. Xie , Xiao-Tao Yang

A variation principle for mass transport in solids is derived that recasts transport coefficients as minima of local thermodynamic average quantities. The result is independent of diffusion mechanism, and applies to amorphous and…

Statistical Mechanics · Physics 2018-12-05 Dallas R. Trinkle

This paper develops some mathematical models arising in behavioral sciences, particularly in psychology, which are formalized via general preferences with variable ordering structures. Our considerations are based on the recent variational…

Optimization and Control · Mathematics 2013-11-26 T. Q. Bao , B. S. Mordukhovich , A. Soubeyran

Using the large-deviation formalism, we study the statistics of current fluctuations in a diffusive nonequilibrium quantum spin chain. The boundary-driven XX chain with dephasing consists of a coherent bulk hopping and a local dissipative…

Statistical Mechanics · Physics 2014-04-25 Marko Znidaric

We apply macroscopic fluctuation theory to study the diffusion of a tracer in a one-dimensional interacting particle system with excluded mutual passage, known as single-file diffusion. In the case of Brownian point particles with hard-core…

Statistical Mechanics · Physics 2014-11-18 P. L. Krapivsky , Kirone Mallick , Tridib Sadhu

Granular segregation is ubiquitous in industrial, geological or daily-life context, but there is still no unifying theoretical approach. In this review, we examine two examples of granular segregation -- shallow rapid flows and rotating…

Soft Condensed Matter · Physics 2015-03-13 Matthias Schröter , Karen E. Daniels

Self-organized pattern formation is vital for many biological processes. Reaction-diffusion models have advanced our understanding of how biological systems develop spatial structures, starting from homogeneity. However, biological…

Variational approximation methods have proven to be useful for scaling Bayesian computations to large data sets and highly parametrized models. Applying variational methods involves solving an optimization problem, and recent research in…

Methodology · Statistics 2017-01-13 Victor M. -H. Ong , David J. Nott , Michael S. Smith

We systematically derive an exact coarse-grained description for interacting particles with thermodynamically consistent stochastic dynamics, applicable across different observation scales, the mesoscopic and the macroscopic. We implement…

Statistical Mechanics · Physics 2026-03-05 Atul Tanaji Mohite , Heiko Rieger

There may be structural principles pertaining to the general behavior of systems that lead to similarities in a variety of different contexts. Classic examples include the descriptive power of fractals, the importance of surface area to…

Earth and Planetary Astrophysics · Physics 2013-12-19 Bruce S. Lieberman , Adrian L. Melott

In many far-from-equilibrium biological systems, energy injected by irreversible processes at microscopic scales propagates to larger scales to fulfill important biological functions. But given dissipative dynamics at the microscale, how…

Statistical Mechanics · Physics 2025-06-03 Qiwei Yu , Matthew P. Leighton , Christopher W. Lynn

In systems of diffusing particles, we investigate large deviations of a time-averaged measure of clustering around one particle. We focus on biased ensembles of trajectories, which realise large-deviation events. The bias acts on a single…

Statistical Mechanics · Physics 2021-06-02 Jakub Dolezal , Robert L. Jack

We propose a mechanism to explain what occurs when a mixture of grains of different sizes and different shapes (i.e. different repose angles) is poured into a quasi-two-dimensional cell. Specifically, we develop a model that displays…

Statistical Mechanics · Physics 2009-10-31 Hernan A. Makse , Pierre Cizeau , H. Eugene Stanley

We review a few representative examples of granular experiments or models where phase separation, accompanied by domain coarsening, is a relevant phenomenon. We first elucidate the intrinsic non-equilibrium, or athermal, nature of granular…

Statistical Mechanics · Physics 2015-04-29 Andrea Baldassarri , Andrea Puglisi , Alessandro Sarracino

The systematic development of Coarse-Grained (CG) models via the Mori-Zwanzig projector operator formalism requires the explicit description of several terms, including a deterministic drift term, a dissipative memory term and a random…

Statistical Mechanics · Physics 2021-09-29 N. Di Pasquale , T. Hudson , M. Icardi , L. Rovigatti , M. Spinaci

Practical methods for quantitative analysis of radial and angular coordinates of leafy organs of vascular plants are presented and applied to published phyllotactic patterns of various real systems from young leaves on a shoot tip to…

Biological Physics · Physics 2012-12-17 Takuya Okabe

The combination of high-dimensionality and disparity of time scales encountered in many problems in computational physics has motivated the development of coarse-grained (CG) models. In this paper, we advocate the paradigm of data-driven…

Computational Physics · Physics 2018-03-05 L. Felsberger , P. S. Koutsourelakis
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