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From the output produced by a memoryless deletion channel from a uniformly random input of known length $n$, one obtains a posterior distribution on the channel input. The difference between the Shannon entropy of this distribution and that…

Information Theory · Computer Science 2018-08-01 Arash Atashpendar , David Mestel , A. W. Roscoe , Peter Y. A. Ryan

We study the Shannon entropy of the cluster size distribution in classical as well as explosive percolation, in order to estimate the uncertainty in the sizes of randomly chosen clusters. At the critical point the cluster size distribution…

Disordered Systems and Neural Networks · Physics 2015-08-18 T. M. Vieira , G. M. Viswanathan , L. R. da Silva

It is shown that the residual entropy (entropy minus that of the ideal gas at the same temperature and density) is mostly synonymous with the independent variable of density scaling, identifying a direct link between these two approaches.…

Chemical Physics · Physics 2024-06-19 Ian Bell , Robin Fingerhut , Jadran Vrabec , Lorenzo Costigliola

The spin 1/2 entropy of electrons trapped in a quantum dot has previously been measured with great accuracy, but the protocol used for that measurement is valid only within a restrictive set of conditions. Here, we demonstrate a novel…

The exact range of the joined values of several R\'{e}nyi entropies is determined. The method is based on topology with special emphasis on the orientation of the objects studied. Like in the case when only two orders of R\'{e}nyi entropies…

Information Theory · Computer Science 2009-04-17 Peter Harremoës

The paper examines relationships between the Shannon entropy and the $\ell_{\alpha}$-norm for $n$-ary probability vectors, $n \ge 2$. More precisely, we investigate the tight bounds of the $\ell_{\alpha}$-norm with a fixed Shannon entropy,…

Information Theory · Computer Science 2016-01-29 Yuta Sakai , Ken-ichi Iwata

Mixture distributions are a workhorse model for multimodal data in information theory, signal processing, and machine learning. Yet even when each component density is simple, the differential entropy of the mixture is notoriously hard to…

Information Theory · Computer Science 2026-02-18 Namyoon Lee

The Shannon entropy is a fundamental measure for quantifying diversity and model complexity in fields such as information theory, ecology, and genetics. However, many existing studies assume that the number of species is known, an…

Methodology · Statistics 2026-02-23 Takato Hashino , Koji Tsukuda

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

The theorem of Shannon-McMillan-Breiman states that for every generating partition on an ergodic system, the exponential decay rate of the measure of cylinder sets equals the metric entropy almost everywhere (provided the entropy is…

Dynamical Systems · Mathematics 2009-03-10 Nicolai T A Haydn

We study the small-regularisation limit of the entropic optimal transport problem on the line with distance cost. While convergence of entropic minimizers is well understood in the discrete setting and in the case where the cost is…

Optimization and Control · Mathematics 2025-12-08 Armand Ley

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

High-order accurate, $\textit{entropy stable}$ numerical methods for hyperbolic conservation laws have attracted much interest over the last decade, but only a few rigorous convergence results are available, particularly in multiple space…

Numerical Analysis · Mathematics 2019-06-13 Neelabja Chatterjee , Ulrik Skre Fjordholm

We study the fluctuation entropy for two-dimensional matter systems with an internal symmetry coupled to Jackiw--Teitelboim(JT) gravity joined to a Minkowski region. The fluctuation entropy is the Shannon entropy associated to probabilities…

High Energy Physics - Theory · Physics 2023-06-28 Alexey Milekhin , Amirhossein Tajdini

The entanglement in a quantum system that possess an internal symmetry, characterized by the Sz-magnetization or U(1)-charge, is distributed among different sectors. The aim of this letter is to gain a deeper understanding of the…

Statistical Mechanics · Physics 2018-07-25 J. C. Xavier , F. C. Alcaraz , G. Sierra

We quantify a social organization's potentiality, that is its ability to attain different configurations. The organization is represented as a network in which nodes correspond to individuals and (multi-)edges to their multiple…

Physics and Society · Physics 2019-09-18 Christian Zingg , Giona Casiraghi , Giacomo Vaccario , Frank Schweitzer

Entropic measures of complexity are able to quantify the information encoded in complex network structures. Several entropic measures have been proposed in this respect. Here we study the relation between the Shannon entropy and the Von…

Disordered Systems and Neural Networks · Physics 2011-09-30 Kartik Anand , Ginestra Bianconi , Simone Severini

We study the Shannon entropy of the probability distribution resulting from the ground-state wave function of a one-dimensional quantum model. This entropy is related to the entanglement entropy of a Rokhsar-Kivelson-type wave function…

Strongly Correlated Electrons · Physics 2009-11-25 Jean-Marie Stéphan , Shunsuke Furukawa , Grégoire Misguich , Vincent Pasquier

We consider entanglement in the ground state of the XY spin model on infinite chain. We use von Neumann entropy of a sub-system as a measure of entanglement. The entropy of a large block of neighboring spins approaches a constant as the…

Quantum Physics · Physics 2007-05-23 A. R. Its , B. -Q. Jin , V. E. Korepin

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
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