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We survey and introduce concepts and tools located at the intersection of information theory and network biology. We show that Shannon's information entropy, compressibility and algorithmic complexity quantify different local and global…

Molecular Networks · Quantitative Biology 2015-12-14 Hector Zenil , Narsis A. Kiani , Jesper Tegnér

The paper deals with the generalization of both Boltzmann entropy and distribution in the light of most-probable interpretation of statistical equilibrium. The statistical analysis of the generalized entropy and distribution leads to some…

Quantum Physics · Physics 2009-11-13 C. G. Chakrabarti , Indranil Chakrabarty

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

Information decompositions quantify how the Shannon information about a given random variable is distributed among several other random variables. Various requirements have been proposed that such a decomposition should satisfy, leading to…

Information Theory · Computer Science 2023-07-11 Johannes Rauh , Pradeep Kr. Banerjee , Eckehard Olbrich , Guido Montúfar , Jürgen Jost

In Hall's reformulation of the uncertainty principle, the entropic uncertainty relation occupies a core position and provides the first nontrivial bound for the information exclusion principle. Based upon recent developments on the…

Quantum Physics · Physics 2016-07-28 Yunlong Xiao , Naihuan Jing , Xianqing Li-Jost

We generalize the Shannon's information theory in a nonadditive way by focusing on the source coding theorem. The nonadditive information content we adopted is consistent with the concept of the form invariance structure of the nonextensive…

Statistical Mechanics · Physics 2009-10-31 Takuya Yamano

Thermodynamic uncertainty relations reveal a fundamental trade-off between the precision of a trajectory observable and entropy production, where the uncertainty of the observable is quantified by its variance. In information theory,…

Statistical Mechanics · Physics 2025-11-25 Yoshihiko Hasegawa , Tomohiro Nishiyama

Most psychophysical experiments discard half the data collected. Specifically, experiments discard reaction time data, and use binary responses (e.g. yes/no) to measure performance. Here, Shannon's information theory is used to define…

Neurons and Cognition · Quantitative Biology 2021-12-14 James V Stone

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

Existing polarization theories have mostly been concerned with Shannon's information measures, such as Shannon entropy and mutual information, and some related measures such as the Bhattacharyya parameter. In this work, we extend…

Information Theory · Computer Science 2019-07-16 Mengfan Zheng , Ling Liu , Cong Ling

Analysis of a probabilistic system often requires to learn the joint probability distribution of its random variables. The computation of the exact distribution is usually an exhaustive precise analysis on all executions of the system. To…

Information Theory · Computer Science 2023-07-19 Fabrizio Biondi , Yusuke Kawamoto , Axel Legay , Louis-Marie Traonouez

We examine the majorization properties of general thermal-like mixed states depending on a set of parameters. Sufficient conditions which ensure the increase in mixedness, and hence of any associated entropic form, when these parameters are…

Statistical Mechanics · Physics 2015-05-13 N. Canosa , R. Rossignoli , M. Portesi

We introduce a novel notion of probability within quantum history theories and give a Gleasonesque proof for these assignments. This involves introducing a tentative novel axiom of probability. We also discuss how we are to interpret these…

Quantum Physics · Physics 2015-06-26 Thomas Marlow

Using the generalized entropies which depend on two parameters we propose a set of quantitative characteristics derived from the Information Geometry based on these entropies. Our aim, at this stage, is modest, as we are first constructing…

Mathematical Physics · Physics 2018-02-14 Demetris P. K. Ghikas , Fotios Oikonomou

Motivated by the idea of entanglement loss along Renormalization Group flows, analytical majorization relations are proven for the ground state of (1+1)-dimensional conformal field theories. For any of these theories, majorization is proven…

Quantum Physics · Physics 2014-11-18 Roman Orus

How much information is added to the Review of Particle Physics when a new decay branching ratio of a hadron is measured and reported? This is quantifiable by Shannon's information entropy $S(i) =-\sum_{f}BR_{(i\longrightarrow f)}\log…

What does it mean for one quantum process to be more disordered than another? Here we provide a precise answer to this question in terms of a quantum-mechanical generalization of majorization. The framework admits a complete description in…

Quantum Physics · Physics 2018-12-21 Gilad Gour , David Jennings , Francesco Buscemi , Runyao Duan , Iman Marvian

The information entropy budget and the rate of information transfer between variables is studied in the context of a nonlinear reduced-order atmospheric model. The key ingredients of the dynamics are present in this model, namely the…

Atmospheric and Oceanic Physics · Physics 2024-04-02 Stéphane Vannitsem , Carlos A. Pires , David Docquier

Researchers have proposed formal definitions of quantitative information flow based on information theoretic notions such as the Shannon entropy, the min entropy, the guessing entropy, and channel capacity. This paper investigates the…

Cryptography and Security · Computer Science 2010-04-02 Hirotoshi Yasuoka , Tachio Terauchi

Information-theoretic quantities reveal dependencies among variables in the structure of joint, marginal, and conditional entropies, but leave some fundamentally different systems indistinguishable. Furthermore, there is no consensus on how…

Information Theory · Computer Science 2023-05-09 Abel Jansma