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The paper examines relationships between the conditional Shannon entropy and the expectation of $\ell_{\alpha}$-norm for joint probability distributions. More precisely, we investigate the tight bounds of the expectation of…

Information Theory · Computer Science 2020-08-24 Yuta Sakai , Ken-ichi Iwata

Many axiomatic definitions of entropy, such as the R\'enyi entropy, of a random variable are closely related to the $\ell_{\alpha}$-norm of its probability distribution. This study considers probability distributions on finite sets, and…

Information Theory · Computer Science 2016-05-06 Yuta Sakai , Ken-ichi Iwata

We calculate and analyze various entropy measures and their properties for selected probability distributions. The entropies considered include Shannon, R\'enyi, generalized R\'enyi, Tsallis, Sharma-Mittal, and modified Shannon entropy,…

Information Theory · Computer Science 2024-11-26 Iryna Bodnarchuk , Yuliya Mishura , Kostiantyn Ralchenko

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 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

Algorithmic entropy and Shannon entropy are two conceptually different information measures, as the former is based on size of programs and the later in probability distributions. However, it is known that, for any recursive probability…

Information Theory · Computer Science 2010-06-03 Andreia Teixeira , Andre Souto , Armando Matos , Luis Antunes

In the present paper we prove a family of tight upper and lower bounds for the Shannon entropy and von Neumann entropy based on the p-norms. This allows us to have an entropy estimate, a criterion for the finiteness of it and a bound on the…

Information Theory · Computer Science 2024-08-22 Juan Pablo Lopez

This study examines sharp bounds on Arimoto's conditional R\'enyi entropy of order $\beta$ with a fixed another one of distinct order $\alpha \neq \beta$. Arimoto inspired the relation between the R\'enyi entropy and the $\ell_{r}$-norm of…

Information Theory · Computer Science 2020-08-24 Yuta Sakai , Ken-ichi Iwata

Relations between Shannon entropy and Renyi entropies of integer order are discussed. For any N-point discrete probability distribution for which the Renyi entropies of order two and three are known, we provide an lower and an upper bound…

Quantum Physics · Physics 2007-05-23 Karol Zyczkowski

In this paper, we study entropic uncertainty relations on a finite-dimensional Hilbert space and provide several tighter bounds for multi-measurements, with some of them also valid for R\'{e}nyi and Tsallis entropies besides the Shannon…

Quantum Physics · Physics 2016-05-02 Yunlong Xiao , Naihuan Jing , Shao-Ming Fei , Tao Li , Xianqing Li-Jost , Teng Ma , Zhi-Xi Wang

The problem of Shannon entropy estimation in countable infinite alphabets is addressed from the study and use of convergence results of the entropy functional, which is known to be discontinuous with respect to the total variation distance…

Information Theory · Computer Science 2018-04-03 Jorge F. Silva

In this article, we discuss the problem of establishing relations between information measures assessed for network structures. Two types of entropy based measures namely, the Shannon entropy and its generalization, the R\'{e}nyi entropy…

Information Theory · Computer Science 2013-01-24 Lavanya Sivakumar , Matthias Dehmer

This paper provides tight bounds on the R\'enyi entropy of a function of a discrete random variable with a finite number of possible values, where the considered function is not one-to-one. To that end, a tight lower bound on the R\'enyi…

Information Theory · Computer Science 2018-12-11 Igal Sason

Entropic uncertainty relations $H(A)+H(B)\geqslant \gamma$ give a nonzero lower bound $\gamma$ to the sum of the Shannon entropies $H$ of the outcome probabilities of incompatible observables $A$ and $B$. They are better than the…

Quantum Physics · Physics 2026-05-05 Alberto Riccardi , Lorenzo Maccone

In this work, we investigate the reliability of information-theoretic measures based on the electron-density and shape-function, specifically Shannon and R\'enyi entropies, as descriptors of electronic correlation. By establishing a…

Quantum Physics · Physics 2026-05-21 Diogo J. L. Rodrigues , Evelio Francisco , Ángel Martín Pendás

Entropic uncertainty relations place nontrivial lower bounds to the sum of Shannon information entropies for noncommuting observables. Here we obtain a novel lower bound on the entropy sum for general pairs of observables in…

Quantum Physics · Physics 2009-11-13 Julio I. de Vicente , Jorge Sánchez-Ruiz

Convergence properties of Shannon Entropy are studied. In the differential setting, it is shown that weak convergence of probability measures, or convergence in distribution, is not enough for convergence of the associated differential…

Information Theory · Computer Science 2016-11-18 Francisco J. Piera , Patricio Parada

In this work we use the extremization method of various information-theoretic measures (Fisher information, Shannon entropy, Tsallis entropy) for $d$-dimensional quantum systems, which complementary describe the spreading of the quantum…

Quantum Physics · Physics 2016-10-07 I. V. Toranzo , S. López-Rosa , R. O. Esquivel , J. S. Dehesa

We show that a proper expression of the uncertainty relation for a pair of canonically-conjugate continuous variables relies on entropy power, a standard notion in Shannon information theory for real-valued signals. The resulting…

Quantum Physics · Physics 2018-01-16 Anaelle Hertz , Michael G. Jabbour , Nicolas J. Cerf

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
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