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Of the various attempts to generalize information theory to multiple variables, the most widely utilized, interaction information, suffers from the problem that it is sometimes negative. Here we reconsider from first principles the general…

Information Theory · Computer Science 2010-04-16 Paul L. Williams , Randall D. Beer

A well-interpretable measure of information has been recently proposed based on a partition obtained by intersecting a random sequence with its moving average. The partition yields disjoint sets of the sequence, which are then ranked…

Statistical Finance · Quantitative Finance 2018-08-01 Linda Ponta , Anna Carbone

Convexity is a key concept in information theory, namely via the many implications of Jensen's inequality, such as the non-negativity of the Kullback-Leibler divergence (KLD). Jensen's inequality also underlies the concept of Jensen-Shannon…

Information Theory · Computer Science 2008-04-11 Andre Martins , Pedro Aguiar , Mario Figueiredo

It is not obvious how to extend Shannon's original information entropy to higher dimensions, and many different approaches have been tried. We replace the English text symbol sequence originally used to illustrate the theory by a discrete,…

Information Theory · Computer Science 2016-09-06 Kieran G. Larkin

With the advent of massive data outputs at a regular rate, admittedly, signal processing technology plays an increasingly key role. Nowadays, signals are not merely restricted to physical sources, they have been extended to digital sources…

Information Theory · Computer Science 2018-01-22 Yi Janet Lu

An existing conjecture states that the Shannon mutual information contained in the ground state wavefunction of conformally invariant quantum chains, on periodic lattices, has a leading finite-size scaling behavior that, similarly as the…

Statistical Mechanics · Physics 2016-09-27 F. C. Alcaraz

The participation coefficient is a widely used metric of the diversity of a node's connections with respect to a modular partition of a network. An information-theoretic formulation of this concept of connection diversity, referred to here…

Physics and Society · Physics 2023-07-25 Pavle Cajic , Dominic Agius , Oliver M. Cliff , James M. Shine , Joseph T. Lizier , Ben D. Fulcher

Quantum processes can exhibit scenarios beyond a fixed order of events. We propose information inequalities that, when violated, constitute sufficient conditions to certify quantum processes without a fixed causal order -- causally…

Quantum Physics · Physics 2025-05-21 Matheus Capela , Kaumudibikash Goswami

We present graphs of information versus disturbance for general quantum measurements of completely unknown states. Each piece of information and disturbance is quantified by two measures: (i) the Shannon entropy and estimation fidelity for…

Quantum Physics · Physics 2017-08-31 Hiroaki Terashima

We discuss linear programming techniques that help to deduce corollaries of non classic inequalities for Shannon's entropy. We focus on direct applications of the copy lemma. These applications involve implicitly some (known or unknown)…

Information Theory · Computer Science 2019-07-04 Emirhan Gürpınar , Andrei Romashchenko

The statistical analysis of data stemming from dynamical systems, including, but not limited to, time series, routinely relies on the estimation of information theoretical quantities, most notably Shannon entropy. To this purpose, possibly…

Information Theory · Computer Science 2021-09-01 Leonardo Ricci , Alessio Perinelli , Michele Castelluzzo

Comparisons of the positive and negative halves of the distributions of parity-odd event variables in particle-physics experimental data can provide sensitivity to sources of non-standard parity violation. Such techniques benefit from…

High Energy Physics - Phenomenology · Physics 2022-07-14 Christopher G. Lester , Ward Haddadin , Ben Gripaios

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

We investigate how to measure and define the entropy of a simple chaotic system, three hard spheres on a ring. A novel approach is presented, which does not assume the ergodic hypothesis. It consists of transforming the particles collision…

Computational Physics · Physics 2023-05-08 Matej Vedak , Graeme J Ackland

Determining the strength of non-linear statistical dependencies between two variables is a crucial matter in many research fields. The established measure for quantifying such relations is the mutual information. However, estimating mutual…

Data Analysis, Statistics and Probability · Physics 2019-07-24 Damián G. Hernández , Inés Samengo

We live in the information age. Claude Shannon, as the father of the information age, gave us a theory of communications that quantified an "amount of information," but, as he pointed out, "no concept of information itself was defined."…

Information Theory · Computer Science 2021-12-06 David Ellerman

This paper considers an information bottleneck problem with the objective of obtaining a most informative representation of a hidden feature subject to a R\'enyi entropy complexity constraint. The optimal bottleneck trade-off between…

Information Theory · Computer Science 2021-02-01 Jian-Jia Weng , Fady Alajaji , Tamás Linder

We provide a condition under which a version of Shannon's Entropy Power Inequality will hold for dependent variables. We provide information inequalities extending those found in the independent case.

Probability · Mathematics 2007-05-23 Oliver Johnson

Entropic uncertainty relations are interesting in their own rights as well as for a lot of applications. Keeping this in mind, we try to make the corresponding inequalities as tight as possible. The use of parametrized entropies also allows…

Quantum Physics · Physics 2023-05-30 Alexey E. Rastegin

We show that an information-theoretic property of Shannon's entropy power, known as concavity of entropy power, can be fruitfully employed to prove inequalities in sharp form. In particular, the concavity of entropy power implies the…

Information Theory · Computer Science 2012-07-13 Giuseppe Toscani
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