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Related papers: Upper Entropy Axioms and Lower Entropy Axioms

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This article provides a completion to theories of information based on entropy, resolving a longstanding question in its axiomatization as proposed by Shannon and pursued by Jaynes. We show that Shannon's entropy function has a…

Information Theory · Computer Science 2015-04-14 Frank Lad , Giuseppe Sanfilippo , Gianna Agrò

Thermodynamic entropy is determined by a heat measurement through the Clausius equality. The entropy then formalizes a fundamental limitation of operations by the second law of thermodynamics. The entropy is also expressed as the Shannon…

Statistical Mechanics · Physics 2015-06-17 Shin-ichi Sasa

When at equilibrium, large-scale systems obey conventional thermodynamics because they belong to microscopic configurations (or states) that are typical. Crucially, the typical states usually represent only a small fraction of the total…

Statistical Mechanics · Physics 2025-01-14 Bernat Corominas-Murtra , Rudolf Hanel , Petr Jizba

In this paper we introduce an easy to compute upper bound on the Tsallis entropy of a density matrix describing a system coupled to a noise source. This suggests that the Tsallis entropy is most natural in the context of quantum information…

Quantum Physics · Physics 2017-02-28 Boaz Tamir

Entropies are fundamental measures of uncertainty with central importance in information theory and statistics and applications across all the quantitative sciences. Under a natural set of operational axioms, the most general form of…

Information Theory · Computer Science 2026-02-02 Roberto Rubboli , Erkka Haapasalo , Marco Tomamichel

For certain groups, parabolic subgroups appear as stabilizers of flags of sets or vector spaces. Quotients by these parabolic subgroups represent orbits of flags, and their cardinalities asymptotically reveal entropies (as rates of…

Information Theory · Computer Science 2025-12-03 Ryan Leal , Jingtong Sun , Juan Pablo Vigneaux

Systems driven away from thermal equilibrium constantly deliver entropy to their environment. Determining this entropy production requires detailed information about the system's internal states and dynamics. However, in most practical…

Statistical Mechanics · Physics 2017-10-03 Gili Bisker , Matteo Polettini , Todd R. Gingrich , Jordan M. Horowitz

The weak law of large numbers implies that, under mild assumptions on the source, the Renyi entropy per produced symbol converges (in probability) towards the Shannon entropy rate. This paper quantifies the speed of this convergence for…

Information Theory · Computer Science 2017-05-01 Maciej Skorski

The notion of group entropy is proposed. It enables to unify and generalize many different definitions of entropy known in the literature, as those of Boltzmann-Gibbs, Tsallis, Abe and Kaniadakis. Other new entropic functionals are…

Statistical Mechanics · Physics 2015-05-28 Piergiulio Tempesta

The structure entropy is one of the most important parameters to describe the structure property of the complex networks. Most of the existing struc- ture entropies are based on the degree or the betweenness centrality. In order to describe…

Social and Information Networks · Computer Science 2014-11-25 Qi Zhang , Xi Lu , Meizhu Li , Yong Deng , Sankaran Mahadevan

In this paper, we investigate new procedures for statistical testing based on Tsallis entropy, a parametric generalization of Shannon entropy. Focusing on multivariate generalized Gaussian and $q$-Gaussian distributions, we develop…

Methodology · Statistics 2025-06-18 Mehmet Sıddık Çadırcı

Tsallis has suggested a nonextensive generalization of the Boltzmann-Gibbs entropy, the maximization of which gives a generalized canonical distribution under special constraints. In this brief report we show that the generalized canonical…

Statistical Mechanics · Physics 2021-04-28 Brian R. La Cour , William C. Schieve

Generalized entropies and relative entropies are the subject of active research. Similar to the standard relative entropy, the relative $q$-entropy is generally unbounded for $q>1$. Upper bounds on the quantum relative $q$-entropy in terms…

Mathematical Physics · Physics 2011-06-28 Alexey E. Rastegin

Since its origin in the thermodynamics of the 19th century, the concept of entropy has also permeated other fields of physics and mathematics, such as Classical and Quantum Statistical Mechanics, Information Theory, Probability Theory,…

Machine Learning · Statistics 2025-03-06 Salomé A. Sepúveda Fontaine , José M. Amigó

We study maximum-entropy inference for finite-dimensional quantum states under linear moment constraints. Given expectation values of finitely many observables, the feasible set of states is convex but typically non-unique. The…

Quantum Physics · Physics 2025-10-27 James Tian

Based on the form invariance of the structures given by Khinchin's axiomatic foundations of information theory and the pseudoadditivity of the Tsallis entropy indexed by q, the concept of conditional entropy is generalized to the case of…

Quantum Physics · Physics 2009-11-06 Sumiyoshi Abe , A. K. Rajagopal

The equilibrium distributions of probabilities providing maximality of Renyi and Tsallis entropies are rederived. New S-forms of them are found which are normalised with corresponding entropies in contrast to the usual Z-forms normalised…

Statistical Mechanics · Physics 2007-05-23 A. G. Bashkirov

We study entropies caused by the unstable part of partially hyperbolic systems. We define unstable metric entropy and unstable topological entropy, and establish a variational principle for partially hyperbolic diffeomorphsims, which states…

Dynamical Systems · Mathematics 2017-10-10 Huyi Hu , Yongxia Hua , Weisheng Wu

Separability conditions for a bipartite quantum system of finite-dimensional subsystems are formulated in terms of R\'{e}nyi and Tsallis entropies. Entropic uncertainty relations often lead to entanglement criteria. We propose new approach…

Quantum Physics · Physics 2017-11-01 Alexey E. Rastegin

Bayes' theorem incorporates distinct types of information through the likelihood and prior. Direct observations of state variables enter the likelihood and modify posterior probabilities through consistent updating. Information in terms of…

Methodology · Statistics 2024-07-19 Duncan K. Foley , Ellis Scharfenaker