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In quantum Shannon theory, various kinds of quantum entropies are used to characterize the capacities of noisy physical systems. Among them, min-entropy and its smooth version attract wide interest especially in the field of quantum…

Quantum Physics · Physics 2025-07-15 Rong Wang , H. F. Chau

Various lower bounds are established for the entropy of sums, products and their combinations. First, we derive a prime-field analogue of a version of the entropy power inequality established by Tao over torsion-free groups. Next, we prove…

Combinatorics · Mathematics 2026-04-30 Lampros Gavalakis , Marcel K. Goh , Ioannis Kontoyiannis

In this Thesis, several results in quantum information theory are collected, most of which use entropy as the main mathematical tool. *While a direct generalization of the Shannon entropy to density matrices, the von Neumann entropy behaves…

Quantum Physics · Physics 2018-10-25 Christian Majenz

It is known that the variance and entropy of quantum observables decompose into intrinsically quantum and classical contributions. Here a general method of constructing quantum-classical decompositions of resources such as uncertainty is…

Quantum Physics · Physics 2023-07-07 Michael J. W. Hall

Entanglement entropy quantifies the amount of uncertainty of a quantum state. For quantum fields in curved space, entanglement entropy of the quantum field theory degrees of freedom is well-defined for a fixed background geometry. In this…

High Energy Physics - Theory · Physics 2020-10-28 Xi Dong , Xiao-Liang Qi , Zhou Shangnan , Zhenbin Yang

In a recent paper, the authors proposed a general methodology for probabilistic learning on manifolds. The method was used to generate numerical samples that are statistically consistent with an existing dataset construed as a realization…

Probability · Mathematics 2018-03-30 C. Soizea , R. Ghanem , C. Safta , X. Huan , Z. P. Vane , J. Oefelein , G. Lacaz , H. N. Najm , Q. Tang , X. Chen

Our capacity to process information depends on the computational power at our disposal. Information theory captures our ability to distinguish states or communicate messages when it is unconstrained with unrivaled beauty and elegance. For…

Quantum Physics · Physics 2026-04-08 Johannes Jakob Meyer , Asad Raza , Jacopo Rizzo , Lorenzo Leone , Sofiene Jerbi , Jens Eisert

The measured relative entropy and measured R\'enyi relative entropy are quantifiers of the distinguishability of two quantum states $\rho$ and $\sigma$. They are defined as the maximum classical relative entropy or R\'enyi relative entropy…

Quantum Physics · Physics 2025-11-25 Zixin Huang , Mark M. Wilde

In this paper we study certain properties of R\'{e}nyi entropy functionals $H_\alpha(\mathcal{P})$ on the space of probability distributions over $\mathbb{Z}_+$. Primarily, continuity and convergence issues are addressed. Some properties…

Information Theory · Computer Science 2020-08-13 Mladen Kovačević , Ivan Stanojević , Vojin Šenk

This paper introduces the variational R\'enyi bound (VR) that extends traditional variational inference to R\'enyi's alpha-divergences. This new family of variational methods unifies a number of existing approaches, and enables a smooth…

Machine Learning · Statistics 2016-10-31 Yingzhen Li , Richard E. Turner

In recent years, several hacking attacks have broken the security of quantum cryptography implementations by exploiting the presence of losses and the ability of the eavesdropper to tune detection efficiencies. We present a simple attack of…

Quantum Physics · Physics 2016-01-28 Antonio Acín , Daniel Cavalcanti , Elsa Passaro , Stefano Pironio , Paul Skrzypczyk

Conventional information-theoretic quantities assume access to probability distributions. Estimating such distributions is not trivial. Here, we consider function-based formulations of cross entropy that sidesteps this a priori estimation…

Information Theory · Computer Science 2021-09-27 Isaac J. Sledge , Jose C. Principe

We propose a generalized entropy maximization procedure, which takes into account the generalized averaging procedures and information gain definitions underlying the generalized entropies. This novel generalized procedure is then applied…

Statistical Mechanics · Physics 2015-05-13 G. Baris Bagci , Ugur Tirnakli

A novel definition of the conditional smooth Renyi entropy, which is different from that of Renner and Wolf, is introduced. It is shown that our definition of the conditional smooth Renyi entropy is appropriate to give lower and upper…

Information Theory · Computer Science 2019-01-25 Shigeaki Kuzuoka

The recently developed matrix based Renyi's entropy enables measurement of information in data simply using the eigenspectrum of symmetric positive semi definite (PSD) matrices in reproducing kernel Hilbert space, without estimation of the…

Machine Learning · Statistics 2023-01-10 Tieliang Gong , Yuxin Dong , Shujian Yu , Bo Dong

We develop a quantum version of the probability estimation framework [arXiv:1709.06159] for randomness generation with quantum side information. We show that most of the properties of probability estimation hold for quantum probability…

Quantum Physics · Physics 2023-02-06 Emanuel Knill , Yanbao Zhang , Honghao Fu

We compare three proof techniques for composable finite-size security of quantum key distribution under collective attacks, with emphasis on how the resulting secret-key rates behave at practically relevant block lengths. As a benchmark, we…

Quantum Physics · Physics 2026-01-08 Gabriele Staffieri , Giovanni Scala , Cosmo Lupo

The fact that the quantum relative entropy is non-increasing with respect to quantum physical evolutions lies at the core of many optimality theorems in quantum information theory and has applications in other areas of physics. In this…

Quantum Physics · Physics 2015-09-24 Mark M. Wilde

The Renyi entropies constitute a family of information measures that generalizes the well-known Shannon entropy, inheriting many of its properties. They appear in the form of unconditional and conditional entropies, relative entropies or…

Quantum Physics · Physics 2014-01-28 Martin Müller-Lennert , Frédéric Dupuis , Oleg Szehr , Serge Fehr , Marco Tomamichel

Randomness is a vital resource for modern day information processing, especially for cryptography. A wide range of applications critically rely on abundant, high quality random numbers generated securely. Here we show how to expand a random…

Quantum Physics · Physics 2016-11-02 Carl A. Miller , Yaoyun Shi
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