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Information theoretic measures (entropies, entropy rates, mutual information) are nowadays commonly used in statistical signal processing for real-world data analysis. The present work proposes the use of Auto Mutual Information (Mutual…

Data Analysis, Statistics and Probability · Physics 2019-07-24 C Granero-Belinchón , S. Roux , P. Abry , N. Garnier

We develop information-theoretic measures of spatial structure and pattern in more than one dimension. As is well known, the entropy density of a two-dimensional configuration can be efficiently and accurately estimated via a converging…

Statistical Mechanics · Physics 2009-11-07 David P. Feldman , James P. Crutchfield

The concept of entropy, firstly introduced in information theory, rapidly became popular in many applied sciences via Shannon's formula to measure the degree of heterogeneity among observations. A rather recent research field aims at…

Methodology · Statistics 2017-03-20 Linda Altieri , Daniela Cocchi , Giulia Roli

In classical and quantum information theory, operational quantities such as the amount of randomness that can be extracted from a given source or the amount of space needed to store given data are normally characterized by one of two…

Quantum Physics · Physics 2011-03-18 Marco Tomamichel , Roger Colbeck , Renato Renner

Information entropic measures such as Fisher information, Shannon entropy, Onicescu energy and Onicescu Shannon entropy of a symmetric double-well potential are calculated in both position and momentum space. Eigenvalues and eigenvectors of…

Quantum Physics · Physics 2019-04-26 Neetik Mukherjee , Arunesh Roy , Amlan K. Roy

Entropy and information can be considered dual: entropy is a measure of the subspace defined by the information constraining the given ambient space. Negative entropies, arising in na\"ive extensions of the definition of entropy from…

Probability · Mathematics 2023-03-06 Daniel Lazarev

Entropic measures of complexity are able to quantify the information encoded in complex network structures. Several entropic measures have been proposed in this respect. Here we study the relation between the Shannon entropy and the Von…

Disordered Systems and Neural Networks · Physics 2011-09-30 Kartik Anand , Ginestra Bianconi , Simone Severini

The study is devoted to definition of generalized metrical and topological (informational entropy) characteristics of neural signals via their well-known theoretical models. We have shown that time dependence of action potential of neurons…

Neurons and Cognition · Quantitative Biology 2016-10-06 Z. Zh. Zhanabaev , T. Yu. Grevtseva , Y. T. Kozhagulov

We consider discrete stochastic processes, modeled by classical master equations, on networks. The temporal growth of the lack of information about the system is captured by its non-equilibrium entropy, defined via the transition…

Statistical Mechanics · Physics 2017-04-26 Oliver Muelken , Sarah Heinzelmann , Maxim Dolgushev

General characterizations of physical measurements are discussed within the framework of the classical information theory. The uncertainty relation for simultaneous measurements of two physical observables is defined in this framework for…

Quantum Physics · Physics 2018-01-30 Yoshimasa Kurihara

We use the concept of entropy power to derive a new one-parameter class of information-theoretic uncertainty relations for pairs of conjugate observables in an infinite-dimensional Hilbert space. This class constitutes an infinite tower of…

Quantum Physics · Physics 2016-06-30 Petr Jizba , Yue Ma , Anthony Hayes , Jacob A. Dunningham

Quantum systems can display particle- or wave-like properties, depending on the type of measurement that is performed on them. The Bell-state quantum eraser is an experiment that brings the duality to the forefront, as a single measurement…

Quantum Physics · Physics 2017-01-11 Jennifer R. Glick , Christoph Adami

We introduce \emph{Information Topology}: a framework that unifies information theory and algebraic topology by treating \emph{cycle closure} as the primitive operation of inference. The starting point is the \emph{dot-cycle dichotomy},…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Xin Li

The uncertainty principle can be expressed in entropic terms, also taking into account the role of entanglement in reducing uncertainty. The information exclusion principle bounds instead the correlations that can exist between the outcomes…

Quantum Physics · Physics 2014-02-26 Patrick J. Coles , Marco Piani

Part 1 has studied the conversion of observed random process with its hidden information to related dynamic process, applying entropy functional measure (EF) of the random process and path functional information measure (IPF) of the dynamic…

Adaptation and Self-Organizing Systems · Physics 2013-08-20 Vladimir S. Lerner

Upper and lower bounds are obtained for the joint entropy of a collection of random variables in terms of an arbitrary collection of subset joint entropies. These inequalities generalize Shannon's chain rule for entropy as well as…

Information Theory · Computer Science 2024-05-07 Mokshay Madiman , Prasad Tetali

The Shannon entropy, one of the cornerstones of information theory, is widely used in physics, particularly in statistical mechanics. Yet its characterization and connection to physics remain vague, leaving ample room for misconceptions and…

Statistical Mechanics · Physics 2021-07-28 Gabriele Carcassi , Christine A. Aidala , Julian Barbour

A special feature of the ground state in a topologically ordered phase is the existence of large scale correlations depending only on the topology of the regions. These correlations can be detected by the topological entanglement entropy or…

Quantum Physics · Physics 2016-02-15 Kohtaro Kato , Fabian Furrer , Mio murao

A density-dependent conformal killing vector (CKV) field is attained from a conformally transformed action composed of a unique constraint and a Klein-Gordon field. The CKV is re-expressed into an information identity and studied in its…

High Energy Physics - Theory · Physics 2020-03-24 Dor Gabay

We consider the analysis of probability distributions through their associated covariance operators from reproducing kernel Hilbert spaces. We show that the von Neumann entropy and relative entropy of these operators are intimately related…

Information Theory · Computer Science 2022-08-29 Francis Bach