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The sandwiched R\'enyi divergences of two finite-dimensional density operators quantify their asymptotic distinguishability in the strong converse domain. This establishes the sandwiched R\'enyi divergences as the operationally relevant…

Quantum Physics · Physics 2025-08-12 Milán Mosonyi

Defining suitable quantum extensions of classical divergences often poses a challenge due to the non-commutative nature of quantum information. In this work, we propose a new approach via what we call the layer cake representation. The…

Quantum Physics · Physics 2025-07-11 Po-Chieh Liu , Christoph Hirche , Hao-Chung Cheng

We study the generalisation of relative entropy, the Renyi divergence $D_{\alpha} ( \rho||\rho_\beta) $ in 2$d$ CFTs between an excited state density matrix $\rho$, created by deforming the Hamiltonian, and the thermal density matrix…

High Energy Physics - Theory · Physics 2020-05-20 Barsha G. Chowdhury , Shouvik Datta , Justin R. David

We study a proper definition of R\'enyi mutual information (RMI) in quantum field theory as defined via the Petz R\'enyi relative entropy. Unlike the standard definition, the RMI we compute is a genuine measure of correlations between…

High Energy Physics - Theory · Physics 2023-01-16 Jonah Kudler-Flam

Quantum information decoupling is a fundamental quantum information processing task, which also serves as a crucial tool in a diversity of topics in quantum physics. In this paper, we characterize the reliability function of catalytic…

Quantum Physics · Physics 2024-06-28 Ke Li , Yongsheng Yao

It has been shown that the $\alpha-z$ R{\'e}nyi relative entropy satisfies the Data Processing Inequality (DPI) for a certain range of $\alpha$'s and $z$'s. Moreover, the range is completely characterized by Zhang in `20. We prove necessary…

Mathematical Physics · Physics 2020-10-28 Sarah Chehade

We give systematic ways of defining monotone quantum relative entropies and (multi-variate) quantum R\'enyi divergences starting from a set of monotone quantum relative entropies. Despite its central importance in information theory, only…

Quantum Physics · Physics 2025-08-12 Milán Mosonyi , Gergely Bunth , Péter Vrana

Many axiomatic definitions of entropy, such as the R\'enyi entropy, of a random variable are closely related to the $\ell_{\alpha}$-norm of its probability distribution. This study considers probability distributions on finite sets, and…

Information Theory · Computer Science 2016-05-06 Yuta Sakai , Ken-ichi Iwata

Properties of scalar quantization with $r$th power distortion and constrained R\'enyi entropy of order $\alpha\in (0,1)$ are investigated. For an asymptotically (high-rate) optimal sequence of quantizers, the contribution to the R\'enyi…

Information Theory · Computer Science 2012-03-27 Wolfgang Kreitmeier , Tamas Linder

This paper studies a specific class of statistical divergences for spectral densities of time series: the spectral $\alpha$-R\'{e}nyi divergences, which include the Itakura-Saito divergence as a limiting case. The aim of this paper is to…

Statistics Theory · Mathematics 2026-04-22 Tetsuya Takabatake , Keisuke Yano

Quantum f-divergences are a quantum generalization of the classical notion of f-divergences, and are a special case of Petz' quasi-entropies. Many well known distinguishability measures of quantum states are given by, or derived from,…

Mathematical Physics · Physics 2017-06-28 F. Hiai , M. Mosonyi , D. Petz , C. Beny

Estimation of Shannon and R\'enyi entropies of unknown discrete distributions is a fundamental problem in statistical property testing and an active research topic in both theoretical computer science and information theory. Tight bounds on…

Quantum Physics · Physics 2023-07-19 Tongyang Li , Xiaodi Wu

The entropy of a quantum system is a measure of its randomness, and has applications in measuring quantum entanglement. We study the problem of measuring the von Neumann entropy, $S(\rho)$, and R\'enyi entropy, $S_\alpha(\rho)$ of an…

Quantum Physics · Physics 2022-04-19 Jayadev Acharya , Ibrahim Issa , Nirmal V. Shende , Aaron B. Wagner

Minimum divergence estimators provide a natural choice of estimators in a statistical inference problem. Different properties of various families of these divergence measures such as Hellinger distance, power divergence, density power…

Statistics Theory · Mathematics 2025-07-08 Subhrajyoty Roy , Supratik Basu , Abhik Ghosh , Ayanendranath Basu

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

A new upper bound on the relative entropy is derived as a function of the total variation distance for probability measures defined on a common finite alphabet. The bound improves a previously reported bound by Csisz\'ar and Talata. It is…

Information Theory · Computer Science 2015-10-20 Igal Sason , Sergio Verdu

We extend the definitions of different types of quantum R\'enyi relative entropy from the finite dimensional setting of density matrices to density spaces of $C^*$-algebras. We show that those quantities (which trivially coincide in the…

Operator Algebras · Mathematics 2019-06-26 Lajos Molnár

The doubly minimized Petz Renyi mutual information of order $\alpha$ is defined as the minimization of the Petz divergence of order $\alpha$ of a fixed bipartite quantum state relative to any product state. The doubly minimized sandwiched…

Quantum Physics · Physics 2026-04-07 Laura Burri

We show that Araki and Masuda's weighted non-commutative vector valued $L_p$-spaces [Araki \& Masuda, Publ. Res. Inst. Math. Sci., 18:339 (1982)] correspond to an algebraic generalization of the sandwiched R\'enyi divergences with parameter…

Mathematical Physics · Physics 2018-12-12 Mario Berta , Volkher B. Scholz , Marco Tomamichel

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
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