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Entropy is one of the key thermodynamic variables reflecting changes in the state of matter. Unlike other thermodynamic variables, it is well-defined also for nonequilibrium steady states through its relation to information. Applying this…

Statistical Mechanics · Physics 2026-04-15 Haim Diamant , Gil Ariel

IIt is demonstrated that the entropy of statistical mechanics and of information theory, $S({\bf p}) = -\sum p_i \log p_i $ may be viewed as a measure of correlation. Given a probability distribution on two discrete variables, $p_{ij}$, we…

Mathematical Physics · Physics 2007-05-23 John H. Van Drie

The new estimates of the conditional Shannon entropy are introduced in the framework of the model describing a discrete response variable depending on a vector of d factors having a density w.r.t. the Lebesgue measure in R^d. Namely, the…

Statistics Theory · Mathematics 2018-04-25 Alexander Bulinski , Alexey Kozhevin

The profile of a sample is the multiset of its symbol frequencies. We show that for samples of discrete distributions, profile entropy is a fundamental measure unifying the concepts of estimation, inference, and compression. Specifically,…

Machine Learning · Statistics 2020-02-27 Yi Hao , Alon Orlitsky

In this paper, I expand Shannon's definition of entropy into a new form of entropy that allows integration of information from different random events. Shannon's notion of entropy is a special case of my more general definition of entropy.…

Machine Learning · Computer Science 2008-11-04 Stefan Jaeger

We characterize different cell states, related to cancer and ageing phenotypes, by a measure of entropy of network ensembles, integrating gene expression values and protein interaction networks. The entropy measure estimates the parameter…

Molecular Networks · Quantitative Biology 2013-05-24 G. Menichetti , G. Bianconi , E. Giampieri , G. Castellani , D. Remondini

We establish a quantitative bound on the entropy jump associated to the sum of independent, identically distributed (IID) radially symmetric random vectors having dimension greater than one. Following the usual approach, we first consider…

Information Theory · Computer Science 2016-11-04 Thomas A. Courtade

We define an entropy based on a chosen governing probability distribution. If a certain kind of measurements follow such a distribution it also gives us a suitable scale to study it with. This scale will appear as a link function that is…

Data Analysis, Statistics and Probability · Physics 2007-10-24 Peter Sunehag

Relative entropy, as a divergence metric between two distributions, can be used for offline change-point detection and extends classical methods that mainly rely on moment-based discrepancies. To build a statistical test suitable for this…

Methodology · Statistics 2025-12-19 Matthieu Garcin , Louis Perot

Observational entropy -- a quantity that unifies Boltzmann's entropy, Gibbs' entropy, von Neumann's macroscopic entropy, and the diagonal entropy -- has recently been argued to play a key role in a modern formulation of statistical…

Quantum Physics · Physics 2026-03-24 Teruaki Nagasawa , Kohtaro Kato , Eyuri Wakakuwa , Francesco Buscemi

Determining the strength of non-linear statistical dependencies between two variables is a crucial matter in many research fields. The established measure for quantifying such relations is the mutual information. However, estimating mutual…

Data Analysis, Statistics and Probability · Physics 2019-07-24 Damián G. Hernández , Inés Samengo

We study the problem of choosing the copula when the marginal distributions of a random vector are not all continuous. Inspired by four motivating examples including simulation from copulas, stress scenarios, co-risk measures, and…

Risk Management · Quantitative Finance 2025-02-05 Liyuan Lin , Ruodu Wang , Ruixun Zhang , Chaoyi Zhao

We analyze entropic uncertainty relations for two orthogonal measurements on a $N$-dimensional Hilbert space, performed in two generic bases. It is assumed that the unitary matrix $U$ relating both bases is distributed according to the Haar…

Quantum Physics · Physics 2016-08-10 Radosław Adamczak , Rafał Latała , Zbigniew Puchała , Karol Życzkowski

For a closed-loop control system with a digital channel between the sensor and the controller, the notion of invariance entropy quantifies the smallest average rate of information above which a given compact subset of the state space can be…

Optimization and Control · Mathematics 2021-11-19 Mahendra Singh Tomar , Christoph Kawan , Majid Zamani

Quantum coherence is the most distinguished signature of quantum mechanics, also recognized to be an essential resource for many promising quantum technologies, playing a central role in phenomena related to quantum information science,…

Quantum Physics · Physics 2019-02-27 Bertúlio de Lima Bernardo

We analyze the concept of virtuosity as a collective attribute in music and its relationship with the entropy based on an experiment that compares two sets of digital signals played by composer-performer electric guitarists. Based on an…

Sound · Computer Science 2024-04-26 Igor Lugo , Martha G. Alatriste-Contreras

We present an index of dependence that allows one to measure the joint or mutual dependence of a $d$-dimensional random vector with $d>2$. The index is based on a $d$-dimensional Kendall process. We further propose a standardized version of…

Statistics Theory · Mathematics 2020-12-24 Georgios Afendras , Marianthi Markatou , Albert Vexler

On the basis of the balance equations for energy-momentum, spin, particle and entropy density, an approach is considered which represents a comparatively general framework for special- and general-relativistic continuum thermodynamics. In…

General Relativity and Quantum Cosmology · Physics 2009-11-13 W. Muschik , H. -H. v. Borzeszkowski

Entropy and information provide natural measures of correlation among elements in a network. We construct here the information theoretic analog of connected correlation functions: irreducible $N$--point correlation is measured by a decrease…

Biological Physics · Physics 2016-09-08 Elad Schneidman , Susanne Still , Michael J. Berry , William Bialek

We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of information theoretic quantities from data uncovers…

Quantitative Methods · Quantitative Biology 2007-07-13 Ilya Nemenman