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Related papers: The case for shifting the Renyi Entropy

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Quantum information measures such as the entropy and the mutual information find applications in physics, e.g., as correlation measures. Generalizing such measures based on the R\'enyi entropies is expected to enhance their scope in…

Quantum Physics · Physics 2015-04-10 Mario Berta , Kaushik P. Seshadreesan , Mark M. Wilde

The analogues of Arimoto's definition of conditional R\'enyi entropy and R\'enyi mutual information are explored for abstract alphabets. These quantities, although dependent on the reference measure, have some useful properties similar to…

Information Theory · Computer Science 2021-10-20 Gautam Aishwarya , Mokshay Madiman

Based on the problem of quantum data compression in a lossless way, we present here an operational interpretation for the family of quantum R\'enyi entropies. In order to do this, we appeal to a very general quantum encoding scheme that…

Quantum Physics · Physics 2017-10-05 G. Bellomo , G. M. Bosyk , F. Holik , S. Zozor

Most of the existing classification methods are aimed at minimization of empirical risk (through some simple point-based error measured with loss function) with added regularization. We propose to approach this problem in a more information…

Machine Learning · Computer Science 2015-01-22 Wojciech Marian Czarnecki , Jacek Tabor

Entropy is the measure of uncertainty in any data and is adopted for maximisation of mutual information in many remote sensing operations. The availability of wide entropy variations motivated us for an investigation over the suitability…

Computer Vision and Pattern Recognition · Computer Science 2014-05-26 S. K. Katiyar , P. V. Arun

We prove a tight uniform continuity bound for Arimoto's version of the conditional $\alpha$-R\'enyi entropy, for the range $\alpha \in [0, 1)$. This definition of the conditional R\'enyi entropy is the most natural one among the multiple…

Information Theory · Computer Science 2022-03-29 Michael G. Jabbour , Nilanjana Datta

R\'enyi divergence is related to R\'enyi entropy much like Kullback-Leibler divergence is related to Shannon's entropy, and comes up in many settings. It was introduced by R\'enyi as a measure of information that satisfies almost the same…

Information Theory · Computer Science 2014-04-25 Tim van Erven , Peter Harremoës

In this paper we derive explicit formulas of the R\'enyi information, Shannon entropy and Song measure for the invariant density of one dimensional ergodic diffusion processes. In particular, the diffusion models considered include the…

Probability · Mathematics 2007-11-13 Alessandro De Gregorio , Stefano Iacus

The R\'enyi entropies $R_{p}[\rho]$, $p>0,\neq 1$ of the highly-excited quantum states of the $D$-dimensional isotropic harmonic oscillator are analytically determined by use of the strong asymptotics of the orthogonal polynomials which…

Mathematical Physics · Physics 2016-10-07 A. I. Aptekarev , D. N. Tulyakov , I. V. Toranzo , J. S. Dehesa

Transfer entropy is capable of capturing nonlinear source-destination relations between multi-variate time series. It is a measure of association between source data that are transformed into destination data via a set of linear…

Information Theory · Computer Science 2019-05-28 David Sigtermans

R\'enyi entropies are conceptually valuable and experimentally relevant generalisations of the celebrated von Neumann entanglement entropy. After a quantum quench in a clean quantum many-body system they generically display a universal…

Statistical Mechanics · Physics 2022-08-04 Bruno Bertini , Katja Klobas , Vincenzo Alba , Gianluca Lagnese , Pasquale Calabrese

We consider a probability distribution depending on a real parameter $x$. As functions of $x$, the R\'enyi entropy and the Tsallis entropy can be expressed in terms of the associated index of coincidence $S(x)$. We establish recurrence…

Classical Analysis and ODEs · Mathematics 2019-10-31 Alexandra Maduta , Diana Otrocol , Ioan Rasa

We extend the approach of Casini, Huerta and Myers to a new calculation of the Renyi entropy of a general CFT in d dimensions with a spherical entangling surface, in terms of certain thermal partition functions. We apply this approach to…

High Energy Physics - Theory · Physics 2012-11-07 Janet Hung , Robert C. Myers , Michael Smolkin , Alexandre Yale

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

Sharpness (of the loss minima) is a common measure to investigate the generalization of neural networks. Intuitively speaking, the flatter the landscape near the minima is, the better generalization might be. Unfortunately, the correlation…

Machine Learning · Computer Science 2025-10-17 Qiaozhe Zhang , Jun Sun , Ruijie Zhang , Yingzhuang Liu

It is shown that R\'enyi statistics provides a plausible basis to describe the hadron distributions measured in high energy particle interactions. Generalized Boltzmann and gamma distributions obtained by maximization of R\'enyi entropy…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. Kropivnitskaya , A. Rostovtsev

Product probability property, known in the literature as statistical independence, is examined first. Then generalized entropies are introduced, all of which give generalizations to Shannon entropy. It is shown that the nature of the…

Statistics Theory · Mathematics 2009-11-13 A. M. Mathai , H. J. Haubold

We develop a quantum Monte Carlo procedure, in the valence bond basis, to measure the Renyi entanglement entropy of a many-body ground state as the expectation value of a unitary {\it Swap} operator acting on two copies of the system. An…

Strongly Correlated Electrons · Physics 2012-01-18 Matthew B. Hastings , Ivan Gonzalez , Ann B. Kallin , Roger G. Melko

In this paper, I expand Shannon's definition of entropy into a new form of entropy that allows integration of information from different random events. Shannon's notion of entropy is a special case of my more general definition of entropy.…

Machine Learning · Computer Science 2008-11-04 Stefan Jaeger

Shannon entropy for discrete distributions is a fundamental and widely used concept, but its continuous analogue, known as differential entropy, lacks essential properties such as positivity and compatibility with the discrete case. In this…

Probability · Mathematics 2025-08-07 Yuliya Mishura , Kostiantyn Ralchenko