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The formalism of statistical mechanics can be generalized by starting from more general measures of information than the Shannon entropy and maximizing those subject to suitable constraints. We discuss some of the most important examples of…

Statistical Mechanics · Physics 2015-05-13 Christian Beck

While most useful information theoretic inequalities can be deduced from the basic properties of entropy or mutual information, Shannon's entropy power inequality (EPI) seems to be an exception: available information theoretic proofs of the…

Information Theory · Computer Science 2016-11-17 Olivier Rioul

We propose a new way to measure inequalities such as the glass ceiling effect in attributed networks. Existing measures typically rely solely on node degree distribution or degree assortativity, but our approach goes beyond these measures…

Social and Information Networks · Computer Science 2023-03-20 Rui Luo , Buddhika Nettasinghe , Vikram Krishnamurthy

We present a problem relating measurements and information theory in spin foam models. In the three dimensional case of quantum gravity we can compute probabilities of spin network graphs and study the behaviour of the Shannon entropy…

General Relativity and Quantum Cosmology · Physics 2015-06-05 J. Manuel Garcia-Islas

The entropy of a graph is an information-theoretic quantity which expresses the complexity of a graph \cite{DM1,M}. After Shannon introduced the definition of entropy to information and communication, many generalizations of the entropy…

Combinatorics · Mathematics 2014-11-26 Xueliang Li , Zhongmei Qin , Meiqin Wei , Ivan Gutman , Matthias Dehmer

In information theory, the well-known log-sum inequality is a fundamental tool which indicates the non-negativity for the relative entropy. In this article, we establish a set of inequalities which are similar to the log-sum inequality…

Functional Analysis · Mathematics 2022-11-08 Supriyo Dutta , Shigeru Furuichi

We develop a general formalism for representing and understanding structure in complex systems. In our view, structure is the totality of relationships among a system's components, and these relationships can be quantified using information…

Statistical Mechanics · Physics 2014-09-17 Benjamin Allen , Blake C. Stacey , Yaneer Bar-Yam

In information theory, one major goal is to find useful functions that summarize the amount of information contained in the interaction of several random variables. Specifically, one can ask how the classical Shannon entropy, mutual…

Information Theory · Computer Science 2025-02-14 Leon Lang , Pierre Baudot , Rick Quax , Patrick Forré

Ruzsa's equivalence theorem provided a framework for converting certain families of inequalities in additive combinatorics to entropic inequalities (which sometimes did not possess stand-alone entropic proofs). In this work, we first…

Information Theory · Computer Science 2025-02-06 Chin Wa Lau , Chandra Nair

Complex systems that are characterized by strong correlations and fat-tailed distribution functions have been argued to be incompatible within the framework of Boltzmann-Gibbs entropy. As an alternative, so-called generalized entropies were…

Statistical Mechanics · Physics 2022-08-15 Rudolf Hanel , Stefan Thurner

The information-theoretic representation of quantum systems, which complements the familiar energy description of the density-functional and wave-function-based theories, is here discussed. According to it, the internal disorder of the…

Quantum Physics · Physics 2013-05-27 J. S. Dehesa , D. Manzano , P. S. Sánchez-Moreno , R. J. Yáñez

In this paper, we present a theoretical discussion on AI deep learning neural network uncertainty investigation based on the classical Rademacher complexity and Shannon entropy. First it is shown that the classical Rademacher complexity and…

Machine Learning · Computer Science 2020-11-24 Mingyong Zhou

Ranks of subspaces of vector spaces satisfy all linear inequalities satisfied by entropies (including the standard Shannon inequalities) and an additional inequality due to Ingleton. It is known that the Shannon and Ingleton inequalities…

Information Theory · Computer Science 2010-07-21 Randall Dougherty , Chris Freiling , Kenneth Zeger

A new concept named nonsymmetric entropy which generalizes the concepts of Boltzman's entropy and shannon's entropy, was introduced. Maximal nonsymmetric entropy principle was proven. Some important distribution laws were derived naturally…

Information Theory · Computer Science 2007-07-13 Chengshi Liu

We investigate certain optimization problems for Shannon information measures, namely, minimization of joint and conditional entropies $H(X,Y)$, $H(X|Y)$, $H(Y|X)$, and maximization of mutual information $I(X;Y)$, over convex regions. When…

Information Theory · Computer Science 2013-12-31 Mladen Kovačević , Ivan Stanojević , Vojin Šenk

It is pointed out that the case for Shannon entropy and von Neumann entropy, as measures of uncertainty in quantum mechanics, is not as bleak as suggested in quant-ph/0006087. The main argument of the latter is based on one particular…

Quantum Physics · Physics 2007-05-23 Michael J. W. Hall

Classical and quantum physics impose different constraints on the joint probability distributions of observed variables in a causal structure. These differences mean that certain correlations can be certified as non-classical, which has…

Quantum Physics · Physics 2020-07-22 V. Vilasini , Roger Colbeck

Recently, Suyari has proposed a generalization of Shannon-Khinchin axioms, which determines a class of entropies containing the well-known Tsalis and Havrda-Charvat entropies [H. Suyari, IEEE Trans. Inf. Theory, vol. 50, pp. 1783-1787, Aug.…

Mathematical Physics · Physics 2012-12-03 Velimir M. Ilic , Miomir S. Stankovic , Edin H. Mulalic

This article introduces the physics of information in the context of molecular biology and genomics. Entropy and information, the two central concepts of Shannon's theory of information and communication, are often confused with each other…

Biomolecules · Quantitative Biology 2007-05-23 Christoph Adami

This article consists of a very short introduction to classical and quantum information theory. Basic properties of the classical Shannon entropy and the quantum von Neumann entropy are described, along with related concepts such as…

High Energy Physics - Theory · Physics 2020-04-20 Edward Witten
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