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The Renyi entropies as a generalization of the entanglement entropy imply much more information. We analytically calculate the Renyi entropies (with a spherical entangling surface) by means of a class of neutral hyperbolic black holes with…

High Energy Physics - Theory · Physics 2023-08-16 Xiaoxuan Bai , Jie Ren

In this paper, we consider the problem of variable-length source coding allowing errors. The exponential moment of the codeword length is analyzed in the non-asymptotic regime and in the asymptotic regime. Our results show that the smooth…

Information Theory · Computer Science 2015-12-22 Shigeaki Kuzuoka

The multi-entropy and dihedral measures are a class of tractable measures for multi-partite entanglement, which are labeled by the R\'enyi index (or replica number) $n$ as in the R\'enyi entanglement entropy. The purpose of this article is…

High Energy Physics - Theory · Physics 2025-06-13 Jonathan Harper , Ali Mollabashi , Tadashi Takayanagi , Kenya Tasuki

We derive a high-resolution formula for the quantization and entropy coding approximation quantities for fractional Brownian motion, respective to the supremum norm and L^p[0,1]-norm distortions. We show that all moments in the quantization…

Probability · Mathematics 2007-05-23 Steffen Dereich , Michael Scheutzow

We calculate analytically the Renyi entropy for the zeta-urn model with a Gibbs measure definition of the micro-state probabilities. This allows us to obtain the singularities in the R\'enyi entropy from those of the thermodynamic…

Statistical Mechanics · Physics 2023-12-07 Piotr Bialas , Zdzislaw Burda , Desmond A. Johnston

Entropy measures quantify the amount of information and correlation present in a quantum system. In practice, when the quantum state is unknown and only copies thereof are available, one must resort to the estimation of such entropy…

Quantum Physics · Physics 2024-03-27 Ziv Goldfeld , Dhrumil Patel , Sreejith Sreekumar , Mark M. Wilde

The matrix-based R\'enyi's entropy allows us to directly quantify information measures from given data, without explicit estimation of the underlying probability distribution. This intriguing property makes it widely applied in statistical…

Machine Learning · Computer Science 2022-12-01 Yuxin Dong , Tieliang Gong , Shujian Yu , Hong Chen , Chen Li

The asymptotics of the weighted $L_{p}$-norms of Hermite polynomials, which describes the R\'enyi entropy of order $p$ of the associated quantum oscillator probability density, is determined for $n\to\infty$ and $p>0$. Then, it is applied…

Mathematical Physics · Physics 2013-05-15 Alexander I. Aptekarev , Jesús S. Dehesa , Pablo Sánchez-Moreno , Dmitrii N. Tulyakov

Two maximization problems of R\'enyi entropy rate are investigated: the maximization over all stochastic processes whose marginals satisfy a linear constraint, and the Burg-like maximization over all stochastic processes whose…

Information Theory · Computer Science 2015-01-06 Christoph Bunte , Amos Lapidoth

In this letter we show that the R\'enyi entanglement entropy of a region of large size $\ell$ in a one-dimensional critical model whose ground state breaks conformal invariance (such as in those described by non-unitary conformal field…

High Energy Physics - Theory · Physics 2015-06-19 Davide Bianchini , Olalla A. Castro-Alvaredo , Benjamin Doyon , Emanuele Levi , Francesco Ravanini

Information theory on a time-discrete setting in the framework of time series analysis is generalized to the time-continuous case. Considerations of the Roessler and Lorenz dynamics as well as the Ornstein-Uhlenbeck process yield for…

Chaotic Dynamics · Physics 2008-06-04 Detlef Holstein

We describe an approach to improving model fitting and model generalization that considers the entropy of distributions of modelling residuals. We use simple simulations to demonstrate the observational signatures of overfitting on ordered…

Methodology · Statistics 2019-08-05 Barnaby Rowe

We consider the problem of distributed lossy linear function computation in a tree network. We examine two cases: (i) data aggregation (only one sink node computes) and (ii) consensus (all nodes compute the same function). By quantifying…

Information Theory · Computer Science 2017-01-16 Yaoqing Yang , Pulkit Grover , Soummya Kar

A framework for deriving R\'enyi entropy-power inequalities (EPIs) is presented that uses linearization and an inequality of Dembo, Cover, and Thomas. Simple arguments are given to recover the previously known R\'enyi EPIs and derive new…

Information Theory · Computer Science 2020-04-08 Olivier Rioul

An extension of the entropy power inequality to the form $N_r^\alpha(X+Y) \geq N_r^\alpha(X) + N_r^\alpha(Y)$ with arbitrary independent summands $X$ and $Y$ in $\mathbb{R}^n$ is obtained for the R\'enyi entropy and powers $\alpha \geq…

Information Theory · Computer Science 2017-10-25 Sergey Bobkov , Arnaud Marsiglietti

Estimating divergences in a consistent way is of great importance in many machine learning tasks. Although this is a fundamental problem in nonparametric statistics, to the best of our knowledge there has been no finite sample exponential…

Information Theory · Computer Science 2016-03-30 Shashank Singh , Barnabás Póczos

We study the class of self-similar probability density functions with finite mean and variance which maximize R\'{e}nyi's entropy. The investigation is restricted in the Schwartz space $S(\mathbb{R}^d)$ and in the space of…

Mathematical Physics · Physics 2015-10-28 Agapitos N. Hatzinikitas

We compute R\'enyi entropies for a spherical entangling surface in four-dimensional N=4 super-Yang-Mills at strong coupling using the AdS/CFT correspondence. Incorporating the effects of the leading \alpha' corrections to the low energy…

High Energy Physics - Theory · Physics 2015-06-16 Damian A. Galante , Robert C. Myers

The Renyi distribution ensuring the maximum of a Renyi entropy is investigated for a particular case of a power--law Hamiltonian. Both Lagrange parameters, $\alpha$ and $\beta$ can be excluded. It is found that $\beta$ does not depend on a…

Statistical Mechanics · Physics 2009-11-10 A. G. Bashkirov

Quantum information processing is limited, in practice, to efficiently implementable operations. This motivates the study of quantum divergences that preserve their operational meaning while faithfully capturing these computational…

Quantum Physics · Physics 2025-09-26 Álvaro Yángüez , Thomas A. Hahn , Jan Kochanowski