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Calculating the Shannon entropy for symbolic sequences has been widely considered in many fields. For descriptive statistical problems such as estimating the N-gram entropy of English language text, a common approach is to use as much data…

Information Theory · Computer Science 2018-05-24 Andrew D. Back , Daniel Angus , Janet Wiles

We conduct an axiomatic study of the problem of estimating the strength of a known causal relationship between a pair of variables. We propose that an estimate of causal strength should be based on the conditional distribution of the effect…

Information Theory · Computer Science 2016-06-03 Weihao Gao , Sreeram Kannan , Sewoong Oh , Pramod Viswanath

The Shannon based conditional entropy that underlies five-dimensional Einstein-Hilbert gravity coupled to a dilaton field is investigated in the context of dynamical holographic AdS/QCD models. Considering the UV and IR dominance limits of…

High Energy Physics - Theory · Physics 2016-09-22 Alex E. Bernardini , Roldao da Rocha

We consider estimating the Shannon entropy of a discrete distribution $P$ from $n$ i.i.d. samples. Recently, Jiao, Venkat, Han, and Weissman, and Wu and Yang constructed approximation theoretic estimators that achieve the minimax $L_2$…

Information Theory · Computer Science 2019-01-03 Yanjun Han , Jiantao Jiao , Tsachy Weissman

We conclude a sequence of work by giving near-optimal sketching and streaming algorithms for estimating Shannon entropy in the most general streaming model, with arbitrary insertions and deletions. This improves on prior results that obtain…

Data Structures and Algorithms · Computer Science 2008-12-18 Nicholas J. A. Harvey , Jelani Nelson , Krzysztof Onak

Recently, Extropy was introduced by Lad, Sanfilippo and Agr\`o as a complement dual of Shannon Entropy. In this paper, we propose dynamic versions of Extropy for doubly truncated random variables as measures of uncertainty called Interval…

Probability · Mathematics 2021-12-03 Francesco Buono , Osman Kamari , Maria Longobardi

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

In the article the $mm$-entropy (an entropy of a metric measure space) introduced by C. Shannon is evaluated for an $\alpha$-stable L\'evy process. For $\alpha<1$ the double-sided estimates of the same order are obtained for process…

Probability · Mathematics 2026-05-28 Viktor Khamzin , Mikhail Lifshits

The Shannon entropy is used as a basis for applying different lemmas and conjectures concerning the set of gaps between prime numbers G_p , thus estimating several measures of it. The same procedures are applied to artificially created…

General Mathematics · Mathematics 2016-06-28 Arturo Ortiz Tapia , Hans Henrik Støleum

We address the generalized uncertainty principle in scenarios of successive measurements. Uncertainties are characterized by means of generalized entropies of both the R\'{e}nyi and Tsallis types. Here, specific features of measurements of…

Quantum Physics · Physics 2018-05-30 Alexey E. Rastegin

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

In the present work we investigate phase correlations by recourse to the Shannon entropy. Using theoretical arguments we show that the entropy provides an accurate measure of phase correlations in any dynamical system, in particular when…

Chaotic Dynamics · Physics 2019-10-24 P. M. Cincotta , C. M. Giordano

We analyze dynamical properties of the Shannon information entropy of a continuous probability distribution, which is driven by a standard diffusion process. This entropy choice is confronted with another option, employing the conditional…

Statistical Mechanics · Physics 2016-08-31 Piotr Garbaczewski

We calculate Shannon information entropy of trapped interacting bosons in both the position and momentum spaces, $S_r$ and $S_k$ respectively. The total entropy maintains the fuctional form $S=a + b \ln N$ for repulsive bosons. At the…

Quantum Gases · Physics 2013-01-25 Sudip Kumar Haldar , Barnali Chakrabarti

It was recently shown that estimating the Shannon entropy $H({\rm p})$ of a discrete $k$-symbol distribution ${\rm p}$ requires $\Theta(k/\log k)$ samples, a number that grows near-linearly in the support size. In many applications $H({\rm…

Information Theory · Computer Science 2016-03-11 Jayadev Acharya , Alon Orlitsky , Ananda Theertha Suresh , Himanshu Tyagi

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

We comment on a formulation of quantum statistical mechanics, which incorporates the statistical inference of Shannon. Our basic idea is to distinguish the dynamical entropy of von Neumann, $H = -k Tr \hat{\rho}\ln\hat{\rho}$, in terms of…

Condensed Matter · Physics 2015-06-24 Kazuo Fujikawa

We investigate the behavior of the Gibbs-Shannon entropy of the stationary nonequilibrium measure describing a one-dimensional lattice gas, of L sites, with symmetric exclusion dynamics and in contact with particle reservoirs at different…

Statistical Mechanics · Physics 2015-05-13 B. Derrida , J. L. Lebowitz , E. R. Speer

This paper considers the estimation of Shannon entropy for discrete distributions with countably infinite support. While minimax rates for finite-support distributions are established, infinite-support distributions present distinct…

Statistics Theory · Mathematics 2025-12-03 Octavio César Mesner

Inferring models, predicting the future, and estimating the entropy rate of discrete-time, discrete-event processes is well-worn ground. However, a much broader class of discrete-event processes operates in continuous-time. Here, we provide…

Statistical Mechanics · Physics 2020-05-11 S. E. Marzen , J. P. Crutchfield