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Related papers: Power Laws are Logarithmic Boltzmann Laws

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It is well known that random multiplicative processes generate power-law probability distributions. We study how the spatio-temporal correlation of the multipliers influences the power-law exponent. We investigate two sources of the time…

Adaptation and Self-Organizing Systems · Physics 2016-03-16 Satoru Morita

Processes involving bursts of activity separated by quiescent periods occur across diverse systems and scales. In human dynamics, these phenomena have been described by power-law inter-event time distributions, $P(t)\sim t^{-\alpha}$, with…

Other Condensed Matter · Physics 2026-04-17 Morten Møller , Philipp Rahe , Sadegh Ghaderzadeh , Elena Besley , Philip Moriarty

We look into the fluctuations caused by disturbances in power systems. In the linearized system of the power systems, the disturbance is modeled by a Brownian motion process, and the fluctuations are described by the covariance matrix of…

Systems and Control · Electrical Eng. & Systems 2023-03-20 Xian Wu , Kaihua Xi , Aijie Cheng , Hai Xiang Lin , Jan H van Schuppen , Chenghui Zhang

We uncover a universal scaling law governing the dispersion of collective attention and identify its underlying stochastic criticality. By analysing large-scale ensembles of Wikipedia page views, we find that the variance of logarithmic…

Physics and Society · Physics 2026-01-21 Keisuke Okamura

We propose a new formulation of the fluctuating lattice Boltzmann equation that is consistent with both equilibrium statististical mechanics and fluctuating hydrodynamics. The formalism is based on a generalized lattice-gas model, with each…

Soft Condensed Matter · Physics 2009-11-13 Burkhard Duenweg , Ulf D. Schiller , Anthony J. C. Ladd

Linear systems with many degrees of freedom containing multiplicative and additive noise are considered. The steady state probability distribution for equations of this kind is examined. With multiplicative white noise it is shown that…

chao-dyn · Physics 2009-10-22 J. M. Deutsch

Subdiffusive behavior of one-dimensional stochastic systems can be described by time-subordinated Langevin equations. The corresponding probability density satisfies the time-fractional Fokker-Planck equations. In the homogeneous systems…

Statistical Mechanics · Physics 2015-07-01 Rytis Kazakevicius , Julius Ruseckas

We analyze the structure of stochastic dynamics near either a stable or unstable fixed point, where force can be approximated by linearization. We find that a cost function that determines a Boltzmann-like stationary distribution can always…

Statistical Mechanics · Physics 2009-11-11 Chulan Kwon , Ping Ao , David J. Thouless

We introduce preferential behavior into the study on statistical mechanics of money circulation. The computer simulation results show that the preferential behavior can lead to power laws on distributions over both holding time and amount…

Physics and Society · Physics 2009-11-11 Ning Ding , Yougui Wang

Macroscopic fluctuation theory has shown that a wide class of non-equilibrium stochastic dynamical systems obey a large deviation principle, but except for a few one-dimensional examples these large deviation principles are in general not…

Statistical Mechanics · Physics 2014-10-02 Gino Del Ferraro , Erik Aurell

In this paper, we propose an optimization-based mechanism to explain power law distributions, where the function that the optimization process is seeking to optimize is derived mathematically, then the behavior and interpretation of this…

Physics and Society · Physics 2018-12-27 A. M. Khalili

It is well-known that the semi-circle law, which is the limiting distribution in the Wigner theorem, is the minimizer of the logarithmic energy penalized by the second moment. A very similar fact holds for the Girko and Marchenko--Pastur…

Probability · Mathematics 2024-07-22 Djalil Chafaï , Benjamin Dadoun , Pierre Youssef

Time evolution of the cities and of the languages is considered in terms of multiplicative noise and fragmentation processes; where power law (Pareto-Zipf law) and slightly asymmetric log-normal (Gauss) distribution result for the size…

Physics and Society · Physics 2009-11-13 C. Tuncay

Boltzmann machines are physics informed generative models with wide applications in machine learning. They can learn the probability distribution from an input dataset and generate new samples accordingly. Applying them back to physics, the…

Computational Physics · Physics 2017-11-20 Lei Wang

Using the information current, we develop a Lorentz-covariant framework for modeling equilibrium fluctuations in relativistic kinetic theory in the grand-canonical ensemble. The resulting stochastic theory is proven to be causal and…

Nuclear Theory · Physics 2024-07-24 Gabriel Soares Rocha , Lorenzo Gavassino , Nicki Mullins

Complex systems consist of many interacting elements which participate in some dynamical process. The activity of various elements is often different and the fluctuation in the activity of an element grows monotonically with the average…

Physics and Society · Physics 2008-04-24 Zoltan Eisler , Imre Bartos , Janos Kertesz

We construct a model of wealth distribution, based on an interactive multiplicative stochastic process on static complex networks. Through numerical simulations we show that a decrease in the number of links discourages equality in wealth…

Statistical Mechanics · Physics 2007-05-23 Wataru Souma , Yoshi Fujiwara , Hideaki Aoyama

Recurrence networks are a novel tool of nonlinear time series analysis allowing the characterisation of higher-order geometric properties of complex dynamical systems based on recurrences in phase space, which are a fundamental concept in…

Chaotic Dynamics · Physics 2016-04-07 Y. Zou , J. Heitzig , R. V. Donner , J. F. Donges , J. D. Farmer , R. Meucci , S. Euzzor , N. Marwan , J. Kurths

A new class of stochastic variables, governed by a specifice set of rules, is introduced. These rules force them to loose some properties usually assumed for this kind of variables. We demonstrate that stochastic processes driven by these…

Quantum Physics · Physics 2007-05-23 J. M. A. Figueiredo

Boltzmann machines are undirected graphical models with two-state stochastic variables, in which the logarithms of the clique potentials are quadratic functions of the node states. They have been widely studied in the neural computing…

Machine Learning · Computer Science 2013-02-01 Neil D. Lawrence , Christopher M. Bishop , Michael I. Jordan
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