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Researchers have proposed formal definitions of quantitative information flow based on information theoretic notions such as the Shannon entropy, the min entropy, the guessing entropy, and channel capacity. This paper investigates the…

Cryptography and Security · Computer Science 2010-04-02 Hirotoshi Yasuoka , Tachio Terauchi

The data for many classification problems, such as pattern and speech recognition, follow mixture distributions. To quantify the optimum performance for classification tasks, the Shannon mutual information is a natural information-theoretic…

Signal Processing · Electrical Eng. & Systems 2022-06-22 Yijun Ding , Amit Ashok

Complementarity relations between various characterizations of a probability distribution are at the core of information theory. In particular, lower and upper bounds for the entropic function are of great importance. In applied topics, we…

Quantum Physics · Physics 2022-09-07 Alexey E. Rastegin

For random percolation at p_c, the probability distribution P(n) of the number of spanning clusters (n) has been studied in large scale simulations. The results are compatible with $P(n) \sim \exp(-an^2)$ for all dimensions. We also study…

Statistical Mechanics · Physics 2009-10-30 Parongama Sen

In this paper, we investigate the asymptotic stability of finite-dimensional stochastic integrable Hamiltonian systems via information entropy. Specifically, we establish the asymptotic vanishing of Shannon entropy difference (with…

Dynamical Systems · Mathematics 2025-10-28 Chen Wang , Yong Li

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

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

The basic notion of percolation in physics assumes the emergence of a giant connected (percolation) cluster in a large disordered system when the density of connections exceeds some critical value. Until recently, the percolation phase…

Disordered Systems and Neural Networks · Physics 2015-05-19 R. A. da Costa , S. N. Dorogovtsev , A. V. Goltsev , J. F. F. Mendes

Information entropic measures such as Fisher information, Shannon entropy, Onicescu energy and Onicescu Shannon entropy of a symmetric double-well potential are calculated in both position and momentum space. Eigenvalues and eigenvectors of…

Quantum Physics · Physics 2019-04-26 Neetik Mukherjee , Arunesh Roy , Amlan K. Roy

The problems of causality, modeling, and control for chaotic, high-dimensional dynamical systems are formulated in the language of information theory. The central quantity of interest is the Shannon entropy, which measures the amount of…

Dynamical Systems · Mathematics 2022-06-01 Adrián Lozano-Durán , Gonzalo Arranz

We show that statistical criticality, i.e. the occurrence of power law frequency distributions, arises in samples that are maximally informative about the underlying generating process. In order to reach this conclusion, we first identify…

Data Analysis, Statistics and Probability · Physics 2019-07-09 Ryan John Cubero , Junghyo Jo , Matteo Marsili , Yasser Roudi , Juyong Song

Global physical properties of random media change qualitatively at a percolation threshold, where isolated clusters merge to form one infinite connected component. The precise knowledge of percolation thresholds is thus of paramount…

Statistical Mechanics · Physics 2008-01-13 Richard A. Neher , Klaus Mecke , Herbert Wagner

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

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

In a recent Letter, Friedman and Landsberg discussed the underlying mechanism of explosive phase transitions on complex networks [Phys. Rev. Lett. 103, 255701 (2009)]. This Brief Report presents a modest, though more insightful extension of…

Statistical Mechanics · Physics 2011-03-18 H. Hooyberghs , B. Van Schaeybroeck

Shannon's entropy is one of the building blocks of information theory and an essential aspect of Machine Learning methods (e.g., Random Forests). Yet, it is only finitely defined for distributions with fast decaying tails on a countable…

Statistics Theory · Mathematics 2022-05-25 Jialin Zhang , Jingyi Shi

The chain rule for the Shannon and von Neumann entropy, which relates the total entropy of a system to the entropies of its parts, is of central importance to information theory. Here we consider the chain rule for the more general smooth…

Quantum Physics · Physics 2013-10-25 Alexander Vitanov , Frederic Dupuis , Marco Tomamichel , Renato Renner

It is known that the entropy of a block of spins of size $L$ embedded in an infinite pure critical spin chain diverges as the logarithm of $L$ with a prefactor fixed by the central charge of the corresponding conformal field theory. For a…

Strongly Correlated Electrons · Physics 2009-11-11 Raoul Santachiara

Entropy is a fundamental property of both classical and quantum systems, spanning myriad theoretical and practical applications in physics and computer science. We study the problem of obtaining estimates to within a multiplicative factor…

Quantum Physics · Physics 2021-11-23 Tom Gur , Min-Hsiu Hsieh , Sathyawageeswar Subramanian

After Shannon, entropy becomes a fundamental quantity to describe not only uncertainity or chaos of a system but also information carried by the system. Shannon's important discovery is to give a mathematical expression of the mutual…

Quantum Physics · Physics 2007-05-23 Masanori Ohya
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