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Related papers: Information Theory based on Non-additive Informati…

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The form invariance of pseudoadditivity is shown to determine the structure of nonextensive entropies. Nonextensive entropy is defined as the appropriate expectation value of nonextensive information content, similar to the definition of…

Statistical Mechanics · Physics 2009-11-07 Hiroki Suyari

The information content of a source is defined in terms of the minimum number of bits needed to store the output of the source in a perfectly recoverable way. A similar definition can be given in the case of quantum sources, with qubits…

Quantum Physics · Physics 2023-04-03 Paolo Perinotti , Alessandro Tosini , Leonardo Vaglini

A definition of the nonadditive (nonextensive) conditional entropy indexed by q is presented. Based on the composition law in terms of it, the Shannon-Khinchin axioms are generalized and the uniqueness theorem is established for the Tsallis…

Quantum Physics · Physics 2007-05-23 Sumiyoshi Abe , A. K. Rajagopal

The field of Information Theory is founded on Claude Shannon's seminal ideas relating to entropy. Nevertheless, his well-known avoidance of meaning (Shannon, 1948) still persists to this day, so that Information Theory remains poorly…

Information Theory · Computer Science 2022-01-17 Philip Tetlow , Dinesh Garg , Leigh Chase , Mark Mattingley-Scott , Nicholas Bronn , Kugendran Naidoo , Emil Reinert

This article serves as a brief introduction to the Shannon information theory. Concepts of information, Shannon entropy and channel capacity are mainly covered. All these concepts are developed in a totally combinatorial flavor. Some issues…

Information Theory · Computer Science 2021-04-26 Ricky X. F. Chen

Statements of Shannon's Noiseless Coding Theorem by various authors, including the original, are reviewed and clarified. Traditional statements of the theorem are often unclear as to when it applies. A new notation is introduced and the…

Information Theory · Computer Science 2010-11-01 L. F. Johnson

Information theory is introduced in this lecture note with a particular emphasis on its relevance to algebraic coding theory. The document develops the mathematical foundations for quantifying uncertainty and information transmission by…

Information Theory · Computer Science 2025-12-08 El Mahdi Mouloua , Essaid Mohamed

The nonextensive statistics based on the $q$-entropy $S_q=-\frac{\sum_{i=1}^v(p_i-p_i^q)}{1-q}$ has been so far applied to systems in which the $q$ value is uniformly distributed. For the systems containing different $q$'s, the…

Statistical Mechanics · Physics 2007-05-23 L. Nivanen , M. Pezeril , Q. A. Wang , A. Le Mehaute

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

In the 21st century, many of the crucial scientific and technical issues facing humanity can be understood as problems associated with understanding, modelling, and ultimately controlling complex systems: systems comprised of a large number…

Information Theory · Computer Science 2025-01-20 Thomas F. Varley

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

In this work, we derive information-theoretic properties for a modified Tsallis entropy, hereinafter referred to as q-entropy. We introduce the notions of joint q-entropy, conditional q-entropy, relative q-entropy, conditional mutual…

Mathematical Physics · Physics 2026-03-31 Marco A. S. Trindade

Recently, Suyari has defined nonextensive information content measure with unique class of functions which satisfies certain set of axioms. Nonextensive entropy is then defined as the appropriate expectation value of nonextensive…

Information Theory · Computer Science 2012-10-30 Velimir M. Ilic , Miomir S. Stankovic

In this article we discuss the formal structure of a generalized information theory based on the extension of the probability calculus of Kolmogorov to a (possibly) non-commutative setting. By studying this framework, we argue that quantum…

Quantum Physics · Physics 2016-01-19 F. Holik , G. M. Bosyk , G. Bellomo

Shannon based his information theory on the notion of probability measures as it we developed by Kolmogorov. In this paper we study some fundamental problems in information theory based on expectation measures. In the theory of expectation…

Information Theory · Computer Science 2025-01-30 Peter Harremoës

The Shannon-Khinchin axioms for the ordinary information entropy are generalized in a natural way to the nonextensive systems based on the concept of nonextensive conditional entropy, and a complete proof of the uniqueness theorem for the…

Statistical Mechanics · Physics 2009-10-31 Sumiyoshi Abe

In this Thesis, several results in quantum information theory are collected, most of which use entropy as the main mathematical tool. *While a direct generalization of the Shannon entropy to density matrices, the von Neumann entropy behaves…

Quantum Physics · Physics 2018-10-25 Christian Majenz

An information theory description of finite systems explicitly evolving in time is presented. We impose a MaxEnt variational principle on the Shannon entropy at a given time while the constraints are set at a former time. The resulting…

Nuclear Theory · Physics 2008-11-26 F. Gulminelli , Ph. Chomaz , O. Juillet , M. J. Ison , C. O. Dorso

Whereas Shannon entropy is related to the growth rate of multinomial coefficients, we show that the quadratic entropy (Tsallis 2-entropy) is connected to their $q$-deformation; when $q$ is a prime power, these $q$-multinomial coefficients…

Mathematical Physics · Physics 2020-03-27 Juan Pablo Vigneaux

We characterize information as risk reduction between knowledge states represented by partitions of the underlying probability space. Entropy corresponds to risk reduction from no (or partial) knowledge to full knowledge about a random…

Information Theory · Computer Science 2026-02-24 Sebastian Gottwald , Daniel A. Braun
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