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We derive various exact results for Markovian systems that spontaneously relax to a non-equilibrium steady-state by using joint probability distributions symmetries of different entropy production decompositions. The analytical approach is…

Statistical Mechanics · Physics 2012-02-10 Reinaldo García-García , Vivien Lecomte , A. B. Kolton , D. Domínguez

This contribution presents a derivation of the steady-state distribution of velocities and distances of driven particles on a onedimensional periodic ring. We will compare two different situations: (i) symmetrical interaction forces…

Data Analysis, Statistics and Probability · Physics 2009-11-13 Martin Treiber , Dirk Helbing

For branching processes, the generating functions for limit distributions of so-called ratios of probabilities of rare events satisfy the Schr\"oder-type integral-functional equations. Excepting limited special cases, the corresponding…

Probability · Mathematics 2024-10-01 Anton A. Kutsenko

We study normal approximations for a class of discrete-time occupancy processes, namely, Markov chains with transition kernels of product Bernoulli form. This class encompasses numerous models which appear in the complex networks…

Probability · Mathematics 2018-11-13 Liam Hodgkinson , Ross McVinish , Philip K. Pollett

We introduce the problem of simultaneously learning all powers of a Poisson Binomial Distribution (PBD). A PBD of order $n$ is the distribution of a sum of $n$ mutually independent Bernoulli random variables $X_i$, where $\mathbb{E}[X_i] =…

Data Structures and Algorithms · Computer Science 2017-07-19 Dimitris Fotakis , Vasilis Kontonis , Piotr Krysta , Paul Spirakis

In this article, we obtain, for the total variance distance, the error bounds between Poisson and convolution of power series distributions via Stein's method. This provides a unified approach to many known discrete distributions. Several…

Probability · Mathematics 2020-06-26 A. N. Kumar , P. Vellaisamy , F. Viens

This paper investigates what can be inferred about an arbitrary continuous probability distribution from a finite sample of $N$ observations drawn from it. The central finding is that the $N$ sorted sample points partition the real line…

Machine Learning · Statistics 2025-07-30 Urban Eriksson

A Hamiltonian-based model of many harmonically interacting massive particles that are subject to linear friction and coupled to heat baths at different temperatures is used to study the dynamic approach to equilibrium and non-equilibrium…

Statistical Mechanics · Physics 2020-09-17 Roland R. Netz

We investigate the informational aspect of (1+1)-dimensional directed percolation, a canonical model of a nonequilibrium continuous transition to a phase dominated by a single special state called the "absorbing" state. Using a tensor…

Statistical Mechanics · Physics 2019-09-09 Kenji Harada , Naoki Kawashima

Maximum entropy models are increasingly being used to describe the collective activity of neural populations with measured mean neural activities and pairwise correlations, but the full space of probability distributions consistent with…

Biological Physics · Physics 2017-08-22 Badr F. Albanna , Christopher Hillar , Jascha Sohl-Dickstein , Michael R. DeWeese

We investigate equilibrium properties of small world networks, in which both connectivity and spin variables are dynamic, using replicated transfer matrices within the replica symmetric approximation. Population dynamics techniques allow us…

Disordered Systems and Neural Networks · Physics 2009-11-11 J. P. L. Hatchett , N. S. Skantzos , T. Nikoletopoulos

The Poisson-binomial distribution is useful in many applied problems in engineering, actuarial science, and data mining. The Poisson-binomial distribution models the distribution of the sum of independent but not identically distributed…

Computation · Statistics 2017-02-07 Man Zhang , Yili Hong , Narayanaswamy Balakrishnan

Entropy is a central concept in physics, but can be challenging to calculate even for systems that are easily simulated. This is exacerbated out of equilibrium, where generally little is known about the distribution characterizing simulated…

Statistical Mechanics · Physics 2024-05-09 Samuel D. Gelman , Guy Cohen

This Comment corrects the error which appeared in the calculation of the degree distribution of random apollonian networks. As a result, the expression of $P(k)$, which gives the probability that a randomly selected node has exactly $k$…

Statistical Mechanics · Physics 2007-05-23 Zhi-Xi Wu , Xin-Jian Xu , Ying-Hai Wang

Networks play a central role in modern data analysis, enabling us to reason about systems by studying the relationships between their parts. Most often in network analysis, the edges are given. However, in many systems it is difficult or…

Machine Learning · Statistics 2014-02-06 Scott W. Linderman , Ryan P. Adams

A unified view on macroscopic thermodynamics and quantum transport is presented. Thermodynamic processes with an exchange of energy between two systems necessarily involve the flow of other balanceable quantities. These flows are first…

Mesoscale and Nanoscale Physics · Physics 2012-10-02 C. Strunk

We investigate the profound relation between the equations of biological evolution and quantum mechanics by writing a biologically inspired equation for the stochastic dynamics of an ensemble of particles. Interesting behavior is observed…

Statistical Mechanics · Physics 2015-05-20 Ginestra Bianconi , Christoph Rahmede

Two families of stochastic interacting particle systems, the interacting Brownian motions and Bessel processes, are defined as extensions of Dyson's Brownian motion models and the eigenvalue processes of the Wishart and Laguerre processes…

Mathematical Physics · Physics 2014-06-09 Sergio Andraus

General relations are found between the measure of the uniformity of distributions on the phase space and the first moments and correlations of extensive variables for systems close to thermal equilibrium. The role played by the parameter…

Statistical Mechanics · Physics 2009-11-07 Arkadiusz Majka , Wojciech Wislicki

Probabilistic cellular automata (PCA) are used to model a variety of discrete spatially extended systems undergoing parallel-updating. We propose an embedding of a number of classical nonequilibrium concepts in the PCA-world. We start from…

Statistical Mechanics · Physics 2017-01-17 Christian Maes