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Related papers: Weighted Approach to R\'enyi Entropy

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We investigate quantum R\'enyi entropic quantities, specifically those derived from 'sandwiched' divergence. This divergence is one of several proposed R\'enyi generalisations of the quantum relative entropy. We may define R\'enyi…

Quantum Physics · Physics 2021-10-04 Alexander McKinlay

We consider optimal scalar quantization with $r$th power distortion and constrained R\'enyi entropy of order $\alpha$. For sources with an absolutely continuous distribution the high rate asymptotics of the quantizer distortion has long…

Information Theory · Computer Science 2011-07-06 Wolfgang Kreitmeier , Tamas Linder

The R\'{e}nyi cross-entropy measure between two distributions, a generalization of the Shannon cross-entropy, was recently used as a loss function for the improved design of deep learning generative adversarial networks. In this work, we…

Information Theory · Computer Science 2022-08-09 Ferenc Cole Thierrin , Fady Alajaji , Tamás Linder

Relative entropy is a measure of distinguishability for quantum states, and plays a central role in quantum information theory. The family of Renyi entropies generalizes to Renyi relative entropies that include as special cases most entropy…

High Energy Physics - Theory · Physics 2014-12-12 Nima Lashkari

We provide the sandwiched R\'enyi divergence of order $\alpha\in(\frac{1}{2},1)$, as well as its induced quantum information quantities, with an operational interpretation in the characterization of the exact strong converse exponents of…

Quantum Physics · Physics 2024-05-29 Ke Li , Yongsheng Yao

R\'enyi transfer entropy (RTE) is a generalization of classical transfer entropy that replaces Shannon's entropy with R\'enyi's information measure. This, in turn, introduces a new tunable parameter $\alpha$, which accounts for sensitivity…

Pattern Formation and Solitons · Physics 2026-01-06 Zlata Tabachová , Petr Jizba , Hynek Lavička , Milan Paluš

The entropy accumulation theorem, and its subsequent generalized version, is a powerful tool in the security analysis of many device-dependent and device-independent cryptography protocols. However, it has the drawback that the finite-size…

Quantum Physics · Physics 2025-12-22 Amir Arqand , Thomas A. Hahn , Ernest Y. -Z. Tan

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

A task is randomly drawn from a finite set of tasks and is described using a fixed number of bits. All the tasks that share its description must be performed. Upper and lower bounds on the minimum $\rho$-th moment of the number of performed…

Information Theory · Computer Science 2014-10-07 Christoph Bunte , Amos Lapidoth

The $\alpha$-$z$ R\'enyi relative entropies are a two-parameter family of R\'enyi relative entropies that are quantum generalizations of the classical $\alpha$-R\'enyi relative entropies. In \cite{zhang20CFL} we decided the full range of…

Mathematical Physics · Physics 2020-11-02 Haonan Zhang

We show that in the continuum limit, the average spectrum method (ASM) is equivalent to maximizing R\'enyi entropies of order $\eta$, of which Shannon entropy is the special case $\eta=1$. The order of R\'enyi entropy is determined by the…

Strongly Correlated Electrons · Physics 2023-07-24 Khaldoon Ghanem , Erik Koch

A two-parameter family of complexity measures $\tilde{C}^{(\alpha,\beta)}$ based on the R\'enyi entropies is introduced and characterized by a detailed study of its mathematical properties. This family is the generalization of a continuous…

Quantum Physics · Physics 2015-05-13 R. Lopez-Ruiz , A. Nagy , E. Romera , J. Sanudo

We consider the maximum entropy problems associated with R\'enyi $Q$-entropy, subject to two kinds of constraints on expected values. The constraints considered are a constraint on the standard expectation, and a constraint on the…

Information Theory · Computer Science 2008-12-18 Jean-François Bercher

A number of inequalities for the weighted entropies is proposed, mirroring properties of a standard (Shannon) entropy and related quantities.

Information Theory · Computer Science 2015-10-12 Yuri Suhov , Salimeh Yasaei Sekeh

Following [1], the aim of this paper is to analyze the relative weighted entropy involving the central moments weight functions. We compare the standard relative entropy with the weighted case in two particular forms of Gaussian…

Information Theory · Computer Science 2015-06-23 Salimeh Yasaei Sekeh , Adriano Polpo

We apply a common measure of randomness, the entropy, in the context of iterated functions on a finite set with n elements. For a permutation, it turns out that this entropy is asymptotically (for a growing number of iterations) close to…

Number Theory · Mathematics 2017-12-20 Joachim von zur Gathen

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

We generalize the topological entanglement entropy to a family of topological Renyi entropies parametrized by a parameter alpha, in an attempt to find new invariants for distinguishing topologically ordered phases. We show that,…

Strongly Correlated Electrons · Physics 2010-01-05 Steven T. Flammia , Alioscia Hamma , Taylor L. Hughes , Xiao-Gang Wen

Shannon's entropy and other entropy-based concepts are derived from the new, more general concept of relative divergence of one "grading' function on a linearly ordered set from another such function. The definition of relative divergence…

Probability · Mathematics 2019-03-14 Alexander Dukhovny

We present simple and computationally efficient nonparametric estimators of R\'enyi entropy and mutual information based on an i.i.d. sample drawn from an unknown, absolutely continuous distribution over $\R^d$. The estimators are…

Machine Learning · Statistics 2010-10-27 Dávid Pál , Barnabás Póczos , Csaba Szepesvári