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Related papers: Relative Entropy and Statistics

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In special relativity the mathematical expressions, defining physical observables as the momentum, the energy etc, emerge as one parameter (light speed) continuous deformations of the corresponding ones of the classical physics. Here, we…

High Energy Physics - Theory · Physics 2009-11-11 G. Kaniadakis

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

The relative entropy is a principal measure of distinguishability in quantum information theory, with its most important property being that it is non-increasing with respect to noisy quantum operations. Here, we establish a remainder term…

Quantum Physics · Physics 2015-08-31 Mario Berta , Marius Lemm , Mark M. Wilde

Convergence properties of Shannon Entropy are studied. In the differential setting, it is shown that weak convergence of probability measures, or convergence in distribution, is not enough for convergence of the associated differential…

Information Theory · Computer Science 2016-11-18 Francisco J. Piera , Patricio Parada

We show that the natural scaling of measurement for a particular problem defines the most likely probability distribution of observations taken from that measurement scale. Our approach extends the method of maximum entropy to use…

Quantitative Methods · Quantitative Biology 2010-03-02 Steven A. Frank , D. Eric Smith

The random matrix ensembles (RME), especially Gaussian random matrix ensembles GRME and Ginibre random matrix ensembles, are applied to following quantum systems: nuclear systems, molecular systems, and two-dimensional electron systems…

Statistical Mechanics · Physics 2007-05-23 Maciej M. Duras

Algebraic statistics is a recently evolving field, where one would treat statistical models as algebraic objects and thereby use tools from computational commutative algebra and algebraic geometry in the analysis and computation of…

Information Theory · Computer Science 2007-07-13 Ambedkar Dukkipati

We study concentration inequalities for the Kullback--Leibler (KL) divergence between the empirical distribution and the true distribution. Applying a recursion technique, we improve over the method of types bound uniformly in all regimes…

Information Theory · Computer Science 2019-10-22 Jay Mardia , Jiantao Jiao , Ervin Tánczos , Robert D. Nowak , Tsachy Weissman

We define an entropy based on a chosen governing probability distribution. If a certain kind of measurements follow such a distribution it also gives us a suitable scale to study it with. This scale will appear as a link function that is…

Data Analysis, Statistics and Probability · Physics 2007-10-24 Peter Sunehag

The random matrix ensembles (RME) of quantum statistical Hamiltonian operators, e.g. Gaussian random matrix ensembles (GRME) and Ginibre random matrix ensembles (Ginibre RME), are applied to following quantum statistical systems: nuclear…

Statistical Mechanics · Physics 2007-05-23 Maciej M. Duras

This paper extends some geometric properties of a one-parameter family of relative entropies. These arise as redundancies when cumulants of compressed lengths are considered instead of expected compressed lengths. These parametric relative…

Information Theory · Computer Science 2011-05-31 Ashok Kumar M. , Rajesh Sundaresan

Counting ad infinitum is the holographic observable to a statistical dynamics with finite states under independent repeated sampling. Entropy provides the infinitesimal probability for an observed frequency $\hat{\boldsymbol{\nu}}$ w.r.t. a…

Statistical Mechanics · Physics 2025-01-14 Hong Qian

Entropy-like functionals on operator algebras have been studied since the pioneering work of von Neumann, Umegaki, Lindblad, and Lieb. The most well-known are the von Neumann entropy $trace (\rho\log \rho)$ and a generalization of the…

Optimization and Control · Mathematics 2008-07-19 Tryphon T. Georgiou

Mutual information $I(X;Y)$ is a useful definition in information theory to estimate how much information the random variable $Y$ holds about the random variable $X$. One way to define the mutual information is by comparing the joint…

Information Theory · Computer Science 2022-04-14 Bulut Kuskonmaz , Jaron Skovsted Gundersen , Rafal Wisniewski

The article presents new sup-sums principles for integral F-divergence for arbitrary convex function F and arbitrary (not necessarily positive and absolutely continuous) measures. As applications of these results we derive the corresponding…

Statistics Theory · Mathematics 2019-09-17 V. I. Bakhtin , A. V. Lebedev

Statistical inference can be seen as information processing involving input information and output information that updates belief about some unknown parameters. We consider the Bayesian framework for making inferences about dynamical…

Statistics Theory · Mathematics 2022-01-17 Artur O. Lopes , Silvia R. C. Lopes , Paulo Varandas

This study explores information measures based on extropy, introducing dynamic relative extropy measures for residual and past lifetimes, and investigating their various properties. Furthermore, the study analyzes the relationships between…

Applications · Statistics 2025-03-11 Saranya P. , Sunoj S. M.

Many quantum chemical similarity measures have been derived and substantiated by applying concepts and quantities from information theory to the electron density. To justify the use of information theory, the electron density is usually…

Chemical Physics · Physics 2024-10-14 Guillaume Acke , Daria Van Hende , Ruben Van der Stichelen , Patrick Bultinck

General characterization of physical measurements is discussed within the framework of a classical information theory. Uncertainty relation for simultaneous measurements of two physical observables is defined in this framework for…

Quantum Physics · Physics 2012-12-18 Yoshimasa Kurihara

The ability to identify reliably a positive or negative partial correlation between the expression levels of two genes is influenced by the number $p$ of genes, the number $n$ of analyzed samples, and the statistical properties of the…

Statistics Theory · Mathematics 2013-09-24 Maya Shevlyakova , Stephan Morgenthaler