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We deploy Shannon's information entropy to the distribution of branching fractions in a particle decay. This serves to quantify how important a given new reported decay channel is, from the point of view of the information that it adds to…

The uncertainty relation based on the Shannon entropies of the probability densities in position and momentum spaces is improved for quantum systems in arbitrary $D$-dimensional spherically symmetric potentials. To find it, we have used the…

Mathematical Physics · Physics 2013-05-22 Łukasz Rudnicki , Pablo Sánchez-Moreno , Jesús S. Dehesa

The goal of this note is to show that some convolution type inequalities from Harmonic Analysis and Information Theory, such as Young's convolution inequality (with sharp constant), Nelson's hypercontractivity of the Hermite semi-group or…

Functional Analysis · Mathematics 2009-07-17 Dario Cordero-Erausquin , Michel Ledoux

We consider the entropy of sums of independent discrete random variables, in analogy with Shannon's Entropy Power Inequality, where equality holds for normals. In our case, infinite divisibility suggests that equality should hold for…

Information Theory · Computer Science 2010-10-21 Oliver Johnson , Yaming Yu

The paper examines relationships between the conditional Shannon entropy and the expectation of $\ell_{\alpha}$-norm for joint probability distributions. More precisely, we investigate the tight bounds of the expectation of…

Information Theory · Computer Science 2020-08-24 Yuta Sakai , Ken-ichi Iwata

It is well known that a Shannon based definition of information entropy leads in the classical case to the Boltzmann entropy. It is tempting to regard the Von Neumann entropy as the corresponding quantum mechanical definition. But the…

Quantum Physics · Physics 2009-11-10 Alexander Stotland , Andrei A. Pomeransky , Eitan Bachmat , Doron Cohen

We have presented a new axiomatic derivation of Shannon Entropy for a discrete probability distribution on the basis of the postulates of additivity and concavity of the entropy function.We have then modified shannon entropy to take account…

Quantum Physics · Physics 2007-05-23 C. G. Chakrabarti , Indranil Chakrabarty

This paper introduces time into information theory, gives a more accurate definition of information, and unifies the information in cognition and Shannon information theory. Specially, we consider time as a measure of information, giving a…

Information Theory · Computer Science 2024-10-30 Yilun Liu , Lidong Zhu

Kolmogorov argued that the concept of information exists also in problems with no underlying stochastic model (as Shannon's information representation) for instance, the information contained in an algorithm or in the genome. He introduced…

Discrete Mathematics · Computer Science 2008-07-01 Joel Ratsaby

The notion of Shannon entropy is crucial for the theory of classical information. In quantum information theory, an analogous key role is played by the von Neumann entropy: quantum information processing is closely related to entropy…

Quantum Physics · Physics 2026-04-15 Arul Lakshminarayan , Karol Życzkowski

There are numerous characterizations of Shannon entropy and Tsallis entropy as measures of information obeying certain properties. Using work by Faddeev and Furuichi, we derive a very simple characterization. Instead of focusing on the…

Information Theory · Computer Science 2017-08-22 John C. Baez , Tobias Fritz , Tom Leinster

Within its range of applicability, the Boltzmann equation seems unique in its capacity to accurately describe the transition from almost any initial state to a self-equilibrated thermal state. Using information-theoretic methods to rephrase…

Statistical Mechanics · Physics 2025-10-07 Jürgen T. Stockburger

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

When a measurement is made on a quantum system in which classical information is encoded, the measurement reduces the observers average Shannon entropy for the encoding ensemble. This reduction, being the {\em mutual information}, is always…

Quantum Physics · Physics 2009-11-10 Kurt Jacobs

We derive a few extended versions of the Kraft inequality for lossy compression, which pave the way to the derivation of several refinements and extensions of the well known Shannon lower bound in a variety of instances of rate-distortion…

Information Theory · Computer Science 2025-12-15 Neri Merhav

It is known that the high-dimensional quantum state space is notoriously complicated in contrast with the beautiful Bloch ball of the qubit. We examined the mechanism behind this fact in the frame work of general probabilistic theory (GPT),…

Quantum Physics · Physics 2022-03-17 Keiji Matsumoto , Gen Kimura

A possible link between Holography and Information Theory is presented. Using the relation between the Shannon and Boltzmann formulas Holography can be seen as the best encoding scheme.

High Energy Physics - Theory · Physics 2007-05-23 L. Alejandro Correa-Borbonet

We share a small connection between information theory, algebra, and topology - namely, a correspondence between Shannon entropy and derivations of the operad of topological simplices. We begin with a brief review of operads and their…

Algebraic Topology · Mathematics 2021-09-13 Tai-Danae Bradley

Symmetry considerations are key towards our understanding of the fundamental laws of Nature. The presence of a symmetry implies that a physical system is invariant under specific transformations and this invariance may have deep…

Quantum Physics · Physics 2022-05-30 Paul Brookes , Tikai Chang , Marzena Szymanska , Eytan Grosfeld , Eran Ginossar , Michael Stern

We study a quantity called discrete layered entropy, which approximates the Shannon entropy within a logarithmic gap. Compared to the Shannon entropy, the discrete layered entropy is piecewise linear, approximates the expected length of the…

Information Theory · Computer Science 2026-01-27 Cheuk Ting Li