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The requirement that an entropy function be composable is key: it means that the entropy of a compound system can be calculated in terms of the entropy of its independent components. We prove that, under mild regularity assumptions, the…

Mathematical Physics · Physics 2018-01-17 Alberto Enciso , Piergiulio Tempesta

The generalized entropic measure, which is optimized by a given arbitrary distribution under the constraints on normalization of the distribution and the finite ordinary expectation value of a physical random quantity, is considered and its…

Statistical Mechanics · Physics 2009-11-10 Sumiyoshi Abe , G. Kaniadakis , A. M. Scarfone

We study minimization of a parametric family of relative entropies, termed relative $\alpha$-entropies (denoted $\mathscr{I}_{\alpha}(P,Q)$). These arise as redundancies under mismatched compression when cumulants of compressed lengths are…

Information Theory · Computer Science 2014-10-21 M. Ashok Kumar , Rajesh Sundaresan

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

We develop a theory of Lp spaces based on outer measures rather than measures. This theory includes the classical Lp theory on measure spaces as special case. It also covers parts of potential theory and Carleson embedding theorems. The…

Classical Analysis and ODEs · Mathematics 2014-08-25 Yen Do , Christoph Thiele

The entropy is one of the most applicable uncertainty measures in many statistical and en- gineering problems. In statistical literature, the entropy is used in calculation of the Kullback- Leibler (KL) information which is a powerful mean…

Computation · Statistics 2011-06-10 Morteza Amini , M. Mehdizadeh , N. R. Arghami

Quantum mechanics and information theory are among the most important scientific discoveries of the last century. Although these two areas initially developed separately it has emerged that they are in fact intimately related. In this…

Quantum Physics · Physics 2009-11-07 V. Vedral

We give a characterization of Maximum Entropy/Minimum Relative Entropy inference by providing two `strong entropy concentration' theorems. These theorems unify and generalize Jaynes' `concentration phenomenon' and Van Campenhout and Cover's…

Information Theory · Computer Science 2008-09-17 Peter Grunwald

We revisit entropic formulations of the uncertainty principle for an arbitrary pair of positive operator-valued measures (POVM) $A$ and $B$, acting on finite dimensional Hilbert space. Salicr\'u generalized $(h,\phi)$-entropies, including…

Quantum Physics · Physics 2015-06-18 S. Zozor , G. M. Bosyk , M. Portesi

We present a quantum information theory that allows for a consistent description of entanglement. It parallels classical (Shannon) information theory but is based entirely on density matrices (rather than probability distributions) for the…

Quantum Physics · Physics 2009-10-30 Nicolas J. Cerf , Chris Adami

R\'enyi divergence is related to R\'enyi entropy much like information divergence (also called Kullback-Leibler divergence or relative entropy) is related to Shannon's entropy, and comes up in many settings. It was introduced by R\'enyi as…

Information Theory · Computer Science 2010-05-28 Tim van Erven , Peter Harremoës

Logical entropy gives a measure, in the sense of measure theory, of the distinctions of a given partition of a set, an idea that can be naturally generalized to classical probability distributions. Here, we analyze how fundamental concepts…

Quantum Physics · Physics 2022-03-14 Boaz Tamir , Ismael L. Paiva , Zohar Schwartzman-Nowik , Eliahu Cohen

We first show how a new definition of entropy, which is intuitively very simple, as a divergence in cluster-size space, leads to a generalized form that is nonextensive for correlated units, but coincides exactly with the conventional one…

Disordered Systems and Neural Networks · Physics 2007-11-20 Fariel Shafee

Recently it has been argued that entropy can be a direct measure of complexity, where the smaller value of entropy indicates lower system complexity, while its larger value indicates higher system complexity. We dispute this view and…

Statistical Mechanics · Physics 2020-08-26 Jarosław Klamut , Ryszard Kutner , Zbigniew R. Struzik

By using the Verlinde's formalism[1], we propose that the positive numerical factor, in which Klinkhamer[2] states that it is necessary to define the fundamental length, can be associated to the parameter q of the Tsallis' nonextensive…

High Energy Physics - Theory · Physics 2015-05-27 Jorge Ananias Neto

The quantum relative entropy is a measure of the distinguishability of two quantum states, and it is a unifying concept in quantum information theory: many information measures such as entropy, conditional entropy, mutual information, and…

Quantum Physics · Physics 2021-04-01 Mark M. Wilde

We shall prove that the celebrated R\'enyi entropy is the first example of a new family of infinitely many multi-parametric entropies. We shall call them the $Z$-entropies. Each of them, under suitable hypotheses, generalizes the celebrated…

Mathematical Physics · Physics 2017-02-07 Piergiulio Tempesta

We present a general approach to quantum entanglement and entropy that is based on algebras of observables and states thereon. In contrast to more standard treatments, Hilbert space is an emergent concept, appearing as a representation…

Mathematical Physics · Physics 2013-08-09 A. P. Balachandran , T. R. Govindarajan , Amilcar R. de Queiroz , A. F. Reyes-Lega

The Shannon entropy of a random variable has much behaviour analogous to a signed measure. Previous work has explored this connection by defining a signed measure on abstract sets, which are taken to represent the information that different…

Information Theory · Computer Science 2025-05-28 Keenan J. A. Down , Pedro A. M. Mediano

We consider the well-known max-(relative) entropy problem $\Theta$(y) = infQ$\ll$P DKL(Q P ) with Kullback-Leibler divergence on a domain $\Omega$ $\subset$ R d , and with ''moment'' constraints h dQ = y, y $\in$ R m . We show that when m…

Optimization and Control · Mathematics 2026-01-08 Jean B Lasserre
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