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We apply a common measure of randomness, the entropy, in the context of iterated functions on a finite set with n elements. For a permutation, it turns out that this entropy is asymptotically (for a growing number of iterations) close to…

Number Theory · Mathematics 2017-12-20 Joachim von zur Gathen

We deploy Shannon's information entropy to the distribution of branching fractions in a particle decay. This serves to quantify how important a given new reported decay channel is, from the point of view of the information that it adds to…

The uncertainty relation based on the Shannon entropies of the probability densities in position and momentum spaces is improved for quantum systems in arbitrary $D$-dimensional spherically symmetric potentials. To find it, we have used the…

Mathematical Physics · Physics 2013-05-22 Łukasz Rudnicki , Pablo Sánchez-Moreno , Jesús S. Dehesa

Entropy rate is a real valued functional on the space of discrete random sources which lacks a closed formula even for subclasses of sources which have intuitive parameterizations. A good way to overcome this problem is to examine its…

Information Theory · Computer Science 2015-01-14 Alexander Schönhuth

We present a new class of estimators of Shannon entropy for severely undersampled discrete distributions. It is based on a generalization of an estimator proposed by T. Schuermann, which itself is a generalization of an estimator proposed…

Information Theory · Computer Science 2021-11-30 Peter Grassberger

The entropic region is formed by the collection of the Shannon entropies of all subvectors of finitely many jointly distributed discrete random variables. For four or more variables, the structure of the entropic region is mostly unknown.…

Information Theory · Computer Science 2026-03-04 E. P. Csirmaz , L. Csirmaz

An "entropy increasing to the maximum" result analogous to the entropic central limit theorem (Barron 1986; Artstein et al. 2004) is obtained in the discrete setting. This involves the thinning operation and a Poisson limit. Monotonic…

Information Theory · Computer Science 2009-11-18 Yaming Yu

In this paper, some general properties of Shannon information measures are investigated over sets of probability distributions with restricted marginals. Certain optimization problems associated with these functionals are shown to be…

Information Theory · Computer Science 2020-08-13 Mladen Kovačević , Ivan Stanojević , Vojin Šenk

We explore the relation between entanglement entropy of quantum many body systems and the distribution of corresponding, properly selected, observables. Such a relation is necessary to actually measure the entanglement entropy. We show that…

Statistical Mechanics · Physics 2009-11-11 Israel Klich , Gil Refael , Alessandro Silva

The Shannon entropy of a random variable has much behaviour analogous to a signed measure. Previous work has explored this connection by defining a signed measure on abstract sets, which are taken to represent the information that different…

Information Theory · Computer Science 2025-05-28 Keenan J. A. Down , Pedro A. M. Mediano

We introduce a method for quantifying the inherent unpredictability of a continuous-valued time series via an extension of the differential Shannon entropy rate. Our extension, the specific entropy rate, quantifies the amount of predictive…

Machine Learning · Computer Science 2016-06-09 David Darmon

Based on the q-exponential distribution which has been observed in more and more physical systems, the varentropy method is used to derive the uncertainty measure of such an abnormal distribution function. The uncertainty measure obtained…

Mathematical Physics · Physics 2010-09-07 Congjie Ou , Aziz El Kaabouchi , Qiuping A. Wang , Jincan Chen

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

A method of estimating the joint probability mass function of a pair of discrete random variables is described. This estimator is used to construct the conditional Shannon-R\'eyni-Tsallis entropies estimates. From there almost sure rates of…

Statistics Theory · Mathematics 2020-02-18 Ba Amadou Diadie , Lo Gane Samb

The statistics of work done on a quantum system can be quantified by the two-point measurement scheme. We show how the Shannon entropy of the work distribution admits a general upper bound depending on the initial diagonal entropy, and a…

Quantum Physics · Physics 2023-05-04 Anthony Kiely , Eoin O'Connor , Thomás Fogarty , Gabriel T. Landi , Steve Campbell

This study investigates entropy's potential for analyzing scientific research patterns across disciplines. Originating from thermodynamics, entropy now measures uncertainty and diversity in information systems. We examine Shannon Entropy,…

Physics and Society · Physics 2025-03-27 Yujie Shi , Alex Jie Yang , Sanhong Deng

For studies in reliability, biometry, and survival analysis, the length-biased distribution is often well-suited for certain natural sampling plans. In this paper, we study the strong uniform consistency of two nonparametric estimators for…

Methodology · Statistics 2025-09-22 Vaishnavi Pavithradas , Rajesh G

Bounds on the entropy of patterns of sequences generated by independently identically distributed (i.i.d.) sources are derived. A pattern is a sequence of indices that contains all consecutive integer indices in increasing order of first…

Information Theory · Computer Science 2007-07-13 Gil I. Shamir

Stochastic thermodynamics extends classical thermodynamics to small systems in contact with one or more heat baths. It can account for the effects of thermal fluctuations and describe systems far from thermodynamic equilibrium. A basic…

Statistical Mechanics · Physics 2018-01-04 Momčilo Gavrilov , Raphaël Chétrite , John Bechhoefer

Entropy can signify different things: For instance, heat transfer in thermodynamics or a measure of information in data analysis. Many entropies have been introduced and it can be difficult to ascertain their different importance and…

Mathematical Physics · Physics 2025-07-10 Henrik Jeldtoft Jensen , Piergiulio Tempesta
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