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The statistical analysis of data stemming from dynamical systems, including, but not limited to, time series, routinely relies on the estimation of information theoretical quantities, most notably Shannon entropy. To this purpose, possibly…

Information Theory · Computer Science 2021-09-01 Leonardo Ricci , Alessio Perinelli , Michele Castelluzzo

Stretched exponential relaxation of a quantity n versus time t according to n = n_0 exp[-(lambda* t)^beta] is ubiquitous in many research fields, where lambda* is a characteristic relaxation rate and the stretching exponent beta is in the…

Statistical Mechanics · Physics 2010-11-12 D. C. Johnston

Stretched-exponential relaxation is a widely observed phenomenon found in ordered ferromagnets as well as glassy systems. One modeling approach connects this behavior to a droplet dynamics described by an effective Langevin equation for the…

Statistical Mechanics · Physics 2024-02-21 Lucianno Defaveri , Eli Barkai , David A. Kessler

Relaxation in glasses is often approximated by a stretched-exponential form: $f(t) = A \exp [-(t/\tau)^{\beta}]$. Here, we show that the relaxation in a model of sheared non-Brownian suspensions developed by Cort\'e et al. [Nature Phys. 4,…

Soft Condensed Matter · Physics 2017-02-02 Joseph D. Paulsen , Sidney R. Nagel

Shannon Entropy is the preeminent tool for measuring the level of uncertainty (and conversely, information content) in a random variable. In the field of communications, entropy can be used to express the information content of given…

Information Theory · Computer Science 2024-11-06 Bill Kay , Audun Myers , Thad Boydston , Emily Ellwein , Cameron Mackenzie , Iliana Alvarez , Erik Lentz

Statistical properties of coupled dynamic-stochastic systems are studied within a combination of the maximum information principle and the superstatistical approach. The conditions at which the Shannon entropy functional leads to a…

Statistical Mechanics · Physics 2009-11-11 E. V. Vakarin , J. P. Badiali

Shannon information entropy is a natural measure of probability (de)localization and thus (un)predictability in various procedures of data analysis for model systems. We pay particular attention to links between the Shannon entropy and the…

Statistical Mechanics · Physics 2007-05-23 Piotr Garbaczewski

In the first chapter of Shannon's "A Mathematical Theory of Communication," it is shown that the maximum entropy rate of an input process of a constrained system is limited by the combinatorial capacity of the system. Shannon considers…

Information Theory · Computer Science 2009-11-20 Georg Böcherer , Valdemar Cardoso da Rocha Junior , Cecilio Pimentel

The electrical activity of external anal sphincter can be registered with surface electromyography. This signals are known to be highly complex and nonlinear. This work aims in characterisation of the information carried in the signals by…

Medical Physics · Physics 2018-12-31 Paulina Trybek , Michal Nowakowski , Jerzy Salowka , Lukasz Machura

The diversity of a community that cannot be fully counted must be inferred. The two preeminent inference methods are the MaxEnt method, which uses information in the form of constraints and Bayes' rule which uses information in the form of…

Methodology · Statistics 2008-08-25 Adom Giffin

In the analysis of any type of system, granting maximum information extraction from its data is non-trivial. Confidence in successful information extraction typically builds on prior knowledge of the studied system or on the user's…

Data Analysis, Statistics and Probability · Physics 2026-01-01 Matteo Becchi , Giovanni Maria Pavan

The entropic uncertainty measures of the multidimensional hydrogenic states quantify the multiple facets of the spatial delocalization of the electronic probability density of the system. The Shannon entropy is the most adequate uncertainty…

Quantum Physics · Physics 2019-11-19 Irene V. Toranzo , David Puertas-Centeno , Nahual Sobrino , Jesús S. Dehesa

This paper derives bounds for two omnipresent information theoretic measures, the Shannon entropy and its complementary dual, the extropy. Based on a large size data set from a logconcave model, the said bounds are obtained for the entropy…

Statistics Theory · Mathematics 2025-07-21 Konstantinos Zografos

We develop a coarse-grained stochastic theory for axonal growth on micropatterned substrates using the Shannon--Jaynes maximum entropy principle. Starting from a Langevin description of growth cone motion, we infer the effective…

Biological Physics · Physics 2026-04-29 Julian Sutaria , Cristian Staii

The maximum entropy principle (MEP) is a method for obtaining the most likely distribution functions of observables from statistical systems, by maximizing entropy under constraints. The MEP has found hundreds of applications in ergodic and…

Classical Physics · Physics 2016-10-03 Rudolf Hanel , Stefan Thurner , Murray Gell-Mann

The metaphor of a potential epigenetic differentiation landscape broadly suggests that during differentiation a stem cell follows the steepest descending gradient toward a stable equilibrium state which represents the final cell type. It…

Cell Behavior · Quantitative Biology 2020-09-22 K. Wiesner , J. Teles , M. Hartnor , C. Peterson

Distributed systems, such as biological and artificial neural networks, process information via complex interactions engaging multiple subsystems, resulting in high-order patterns with distinct properties across scales. Investigating how…

Information Theory · Computer Science 2025-04-23 Aaron J. Gutknecht , Fernando E. Rosas , David A. Ehrlich , Abdullah Makkeh , Pedro A. M. Mediano , Michael Wibral

We attempt to give a bird's eye view of the physical mechanisms leading to anomalous relaxation, and the relation of this phenomenon with anomalous diffusion and transport. Whereas in some cases these two notions are indeed deeply related,…

Disordered Systems and Neural Networks · Physics 2007-05-23 Jean-Philippe Bouchaud

An information theory description of finite systems explicitly evolving in time is presented. We impose a MaxEnt variational principle on the Shannon entropy at a given time while the constraints are set at a former time. The resulting…

Nuclear Theory · Physics 2008-11-26 F. Gulminelli , Ph. Chomaz , O. Juillet , M. J. Ison , C. O. Dorso

This short report details the mathematical properties of the stretched exponential function and some of its applications in materials science. G(tau) distributions for different values of the stretching parameter beta are provided.

Disordered Systems and Neural Networks · Physics 2018-08-03 Daniel C. Elton
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