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Related papers: Quantum Skew Divergence

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We introduce modified generalized Wigner-Yanase-Dyson (MGWYD) skew information and modified weighted generalized Wigner-Yanase-Dyson (MWGWYD) skew information. By revisiting state-channel interaction based on MGWYD skew information, a…

Quantum Physics · Physics 2020-04-27 Zhaoqi Wu , Lin Zhang , Shao-Ming Fei , Xianqing Li-Jost

Coupling arguments are a central tool for bounding the deviation between two stochastic processes, but traditionally have been limited to Wasserstein metrics. In this paper, we apply the shifted composition rule--an information-theoretic…

Statistics Theory · Mathematics 2024-12-25 Jason M. Altschuler , Sinho Chewi

In this paper we consider one parameter generalizations of some non - symmetric divergence measures. Measures are \textit{relative information}, $\chi ^2 - $\textit{divergence}, \textit{relative J-divergence}, \textit{relative…

Statistics Theory · Mathematics 2007-06-13 Inder Jeet Taneja , Pranesh Kumar

We introduce an estimation method for the scaled skewness coefficient of the sample mean of short and long memory linear processes. This method can be extended to estimate higher moments such as curtosis coefficient of the sample mean. Also…

Statistics Theory · Mathematics 2020-05-25 Masoud M Nasari , Mohamedou Ould-Haye

In this paper we develop tools for studying limit theorems by means of convexity. We establish bounds for the discrepancy in total variation between probability measures $\mu$ and $\nu$ such that $\nu$ is log-concave with respect to $\mu$.…

Probability · Mathematics 2022-10-24 Arturo Jaramillo , James Melbourne

The Kullback-Leibler (KL) divergence is a fundamental equation of information theory that quantifies the proximity of two probability distributions. Although difficult to understand by examining the equation, an intuition and understanding…

Information Theory · Computer Science 2014-04-09 Jonathon Shlens

The variance of quantum channels involving a mixed state gives a hybrid of classical and quantum uncertainties. We seek certain decomposition of variance into classical and quantum parts in terms of the Wigner-Yanase skew information.…

Quantum Physics · Physics 2023-12-21 Qing-Hua Zhang , Jing-Feng Wu , Shao-Ming Fei

A 2022 paper arXiv:2009.10305v4 introduced the notion of true positive and negative skewness for continuous random variables via Fr\'echet $p$-means. In this work, we find novel criteria for true skewness, establish true skewness for the…

Probability · Mathematics 2022-09-23 Yevgeniy Kovchegov , Alex Negrón , Clarice Pertel , Christopher Wang

In this letter, we propose a novel statistical method to measure which system is better suited to probe small deviations from the usual quantum behavior. Such deviations are motivated by a number of theoretical and phenomenological…

We report a refinement of Robertson-Schroedinger uncertainty relation via Wigner-Yanase skew information. Besides the well known quantum uncertainty arising from the noncommutativity of observables, there is classical uncertainty arising…

Quantum Physics · Physics 2013-03-27 Sixia Yu , C. H. Oh

In this paper, we introduce new classes of divergences by extending the definitions of the Bregman divergence and the skew Jensen divergence. These new divergence classes (g-Bregman divergence and skew g-Jensen divergence) satisfy some…

Statistics Theory · Mathematics 2018-09-21 Tomohiro Nishiyama

In this paper we will give a short presentation of the quantum Levy-Khinchin formula and of the formulation of quantum continual measurements based on stochastic differential equations, matters which we had the pleasure to work on in…

Quantum Physics · Physics 2007-05-23 Alberto Barchielli , Giancarlo Lupieri

A new canonical divergence is put forward for generalizing an information-geometric measure of complexity for both, classical and quantum systems. On the simplex of probability measures it is proved that the new divergence coincides with…

Mathematical Physics · Physics 2019-06-11 Domenico Felice , Stefano Mancini , Nihat Ay

The detection of multipartite entanglement in multipartite quantum systems is a fundamental and key issue in quantum information theory. In this paper, we investigate $k$-nonseparability and $k$-partite entanglement of $N$-partite quantum…

Quantum Physics · Physics 2025-03-13 Yan Hong , Yabin Xing , Limin Gao , Ting Gao , Fengli Yan

In this paper we shall consider one parametric generalization of some non-symmetric divergence measures. The \textit{non-symmetric divergence measures} are such as: Kullback-Leibler \textit{relative information}, $\chi…

Statistics Theory · Mathematics 2007-06-13 Pranesh Kumar , Inder Jeet Taneja

Variance is a ubiquitous quantity in quantum information theory. Given a basis, we consider the averaged variances of a fixed diagonal observable in a pure state under all possible permutations on the components of the pure state and call…

Quantum Physics · Physics 2022-07-14 Ming-Jing Zhao , Lin Zhang , Shao-Ming Fei

We show that a quantum state may be represented as the sum of a joint probability and a complex quantum modification term. The joint probability and the modification term can both be observed in successive projective measurements. The…

Quantum Physics · Physics 2007-11-21 Lars M. Johansen

Uncertainty relations and complementarity relations are core issues in quantum mechanics and quantum information theory. By use of the generalized Wigner-Yanase-Dyson (GWYD) skew information, we derive several uncertainty and…

Quantum Physics · Physics 2021-08-06 Huaijing Huang , Zhaoqi Wu , Shao-Ming Fei

Multipartite quantum entanglement, as a core quantum resource, is fundamental to the advancement of quantum science and technology. In multipartite quantum systems, there are two kinds of quantum entanglement: $k$-nonseparability and…

Quantum Physics · Physics 2025-10-27 Xiaofei Qi , Yuyang Pang , Jinchuan Hou

We introduce a novel family of distances, called the chord gap divergences, that generalizes the Jensen divergences (also called the Burbea-Rao distances), and study its properties. It follows a generalization of the celebrated statistical…

Machine Learning · Computer Science 2017-11-15 Frank Nielsen