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Related papers: MaxEnt and dynamical information

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The principle of maximum entropy is a broadly applicable technique for computing a distribution with the least amount of information possible constrained to match empirical data, for instance, feature expectations. We seek to generalize…

Information Theory · Computer Science 2022-05-30 Kenneth Bogert

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

A path information is defined in connection with the probability distribution of paths of nonequilibrium hamiltonian systems moving in phase space from an initial cell to different final cells. On the basis of the assumption that these…

Statistical Mechanics · Physics 2007-05-23 Q. A. Wang

The science of cities is a relatively new and interdisciplinary topic. It borrows techniques from agent-based modeling, stochastic processes, and partial differential equations. However, how the cities rise and fall, how they evolve, and…

Physics and Society · Physics 2023-04-28 Simone Daniotti , Bernardo Monechi , Enrico Ubaldi

In mixed strategy 2\times2 population games, the realization of maximum entropy (Maxent) is of the theoretical expectation. We evaluate this theoretical prediction in the experimental economics game data. The data includes 12 treatments and…

Applications · Statistics 2012-06-18 Bin Xu , Zhijian Wang

The investigation of the question "which treatment has a causal effect on a target variable?" is of particular relevance in a large number of scientific disciplines. This challenging task becomes even more difficult if not all treatment…

Methodology · Statistics 2022-02-28 Sergio Hernan Garrido Mejia , Elke Kirschbaum , Dominik Janzing

The principle of maximum entropy (Maxent) is often used to obtain prior probability distributions as a method to obtain a Gibbs measure under some restriction giving the probability that a system will be in a certain state compared to the…

Information Theory · Computer Science 2019-06-26 Hector Zenil , Narsis A. Kiani , Jesper Tegnér

An amended MaxEnt formulation for systems displaced from the conventional MaxEnt equilibrium is proposed. This formulation involves the minimization of the Kullback-Leibler divergence to a reference $Q$ (or maximization of Shannon…

Mathematical Physics · Physics 2009-11-11 Jean-François Bercher

We consider a system composed of a fixed number of particles with total energy smaller or equal to some prescribed value. The particles are non-interacting, indistinguishable and distributed over fixed number of energy levels. The energy…

Probability · Mathematics 2021-03-23 Tomasz M. Łapiński

Recent work in data mining and related areas has highlighted the importance of the statistical assessment of data mining results. Crucial to this endeavour is the choice of a non-trivial null model for the data, to which the found patterns…

Artificial Intelligence · Computer Science 2009-06-30 Tijl De Bie

In view of the recent quest for well-behaved nonlinear extensions of the traditional Schroedinger-von Neumann unitary dynamics that could provide fundamental explanations of recent experimental evidence of loss of quantum coherence at the…

Quantum Physics · Physics 2010-11-13 Gian-Paolo Beretta

The phenomenon of entropy concentration provides strong support for the maximum entropy method, MaxEnt, for inferring a probability vector from information in the form of constraints. Here we extend this phenomenon, in a discrete setting,…

Information Theory · Computer Science 2021-01-11 Kostas N. Oikonomou

Entropy, its production, and its change in a dynamical system can be understood from either a fully stochastic dynamic description or from a deterministic dynamics exhibiting chaotic behavior. By taking the former approach based on the…

Mathematical Physics · Physics 2025-08-26 Hong Qian , Zhongwei Shen

We extend present Shannon's static statistical information theory to dynamic processes and establish a dynamic statistical information theory. We derive the nonlinear evolution equations of dynamic information density and dynamic…

Statistical Mechanics · Physics 2007-05-23 Xing Xiu-San

In dynamical systems composed of interacting parts, conditional exponents, conditional exponent entropies and cylindrical entropies are shown to be well defined ergodic invariants which characterize the dynamical selforganization and…

adap-org · Physics 2009-10-30 R. Vilela Mendes

It is well understood that various alternatives are available within EM theory for the definitions of energy density, momentum transfer, EM stress-energy tensor, and so forth. Although the various options are all compatible with the basic…

General Physics · Physics 2010-09-28 H. E. Puthoff

We give conditions to prove the existence of an Extremal Index for general stationary stochastic processes by detecting the presence of one or more underlying periodic phenomena. This theory, besides giving general useful tools to identify…

Probability · Mathematics 2014-01-20 Ana Cristina Moreira Freitas , Jorge Milhazes Freitas , Mike Todd

We show that an equilibriumlike additivity property can remarkably lead to power-law distributions observed frequently in a wide class of out-of-equilibrium systems. The additivity property can determine the full scaling form of the…

Statistical Mechanics · Physics 2015-12-17 Arghya Das , Sayani Chatterjee , Punyabrata Pradhan , P. K. Mohanty

The entropy maximum approach (Maxent) was developed as a minimization of the subjective uncertainty measured by the Boltzmann--Gibbs--Shannon entropy. Many new entropies have been invented in the second half of the 20th century. Now there…

Data Analysis, Statistics and Probability · Physics 2013-11-07 A. N. Gorban

Ill-posed inverse problems of the form y = X p where y is J-dimensional vector of a data, p is m-dimensional probability vector which cannot be measured directly and matrix X of observable variables is a known J,m matrix, J < m, are…

Mathematical Physics · Physics 2012-08-27 M. Grendar, , M. Grendar