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Let $I$ and $J$ be two intervals, and let $f, g: I \rightarrow \mathbb{R}$. If for any points $a$ and $b$ in $I$ and any positive numbers $p$ and $q$ such that $p + q = 1$, we have \begin{align} \nonumber p f(a) + q f(b) + g(pa + qb) \in J,…

General Mathematics · Mathematics 2023-01-13 Jun Liu

Information inequalities govern the ultimate limitations in information theory and as such play an pivotal role in characterizing what values the entropy of multipartite states can take. Proving an information inequality, however, quickly…

Quantum Physics · Physics 2025-10-23 Shao-Lun Huang , Tobias Rippchen , Mario Berta

A generalized Kullback-Leibler relative entropy is introduced starting with the symmetric Jackson derivative of the generalized overlap between two probability distributions. The generalization retains much of the structure possessed by the…

Statistical Mechanics · Physics 2015-05-13 Takuya Yamano

In this paper we introduce the intuitive notion of trivergence of probability distributions (TPD). This notion allow us to calculate the similarity among triplets of objects. For this computation, we can use the well known measures of…

Information Theory · Computer Science 2015-06-23 Juan-Manuel Torres-Moreno

There are many information and divergence measures exist in the literature on information theory and statistics. The most famous among them are Kullback-Leiber's (1951)relative information and Jeffreys (1946) J-divergence, Information…

Probability · Mathematics 2007-05-23 Inder Jeet Taneja

In this paper various notions of convexity of real functions with respect to Chebyshev systems defined over arbitrary subsets of the real line are introduced. As an auxiliary notion, a concept of a relevant divided difference and also a…

Classical Analysis and ODEs · Mathematics 2017-06-29 Zsolt Páles , Éva Székelyné Radácsi

This work is devoted to a vast extension of Sanov's theorem, in Laplace principle form, based on alternatives to the classical convex dual pair of relative entropy and cumulant generating functional. The abstract results give rise to a…

Probability · Mathematics 2019-12-12 Daniel Lacker

We prove the Shannon's inequality on non-collapsing $\mathsf{RCD}(0,N)$ spaces. In the proof, we use the characterization of the $\mathsf{EVI}_{0,N}$-gradient flow of the relative entropy and the infinitesimal behavior of the heat kernel.…

Metric Geometry · Mathematics 2024-11-08 Yu Kitabeppu

The Holevo quantity provides an upper bound for the mutual information between the sender of a classical message encoded in quantum carriers and the receiver. Applying the strong sub-additivity of entropy we prove that the Holevo quantity…

Quantum Physics · Physics 2015-05-18 Wojciech Roga , Mark Fannes , Karol Zyczkowski

An amended MaxEnt formulation for systems displaced from the conventional MaxEnt equilibrium is proposed. This formulation involves the minimization of the Kullback-Leibler divergence to a reference $Q$ (or maximization of Shannon…

Mathematical Physics · Physics 2009-11-11 Jean-François Bercher

In this short note, we prove that the square root of the quantum Jensen-Shannon divergence is a true metric on the cone of positive matrices, and hence in particular on the quantum state space.

Mathematical Physics · Physics 2021-01-25 Dániel Virosztek

In this paper, we give the refinement of an extension of Jensen's inequality to affine combinations. Furthermore, we present the functional form of Jensen's inequality for continuous 3-convex functions of one variable at a point.

Classical Analysis and ODEs · Mathematics 2016-01-25 Imran Abbas Baloch , Silvestru Sever Dragomir

The exponential ergodicity of partially dissipative McKean-Vlasov SDEs in the \(L^1\)-Wasserstein distance has been extensively studied using asymptotic reflection coupling. However, the reflection coupling method is not applicable for the…

Probability · Mathematics 2025-11-13 Xing Huang , Eva Kopfer , Panpan Ren

In a quadruply imaged lens system the angular distribution of images around the lens center is completely described by three relative angles. We show empirically that in the 3D space of these angles, spanning 180 x 180 x 90 degrees, quads…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 Addishiwot G. Woldesenbet , Liliya L. R. Williams

Distinguishability is fundamental to information theory and extends naturally to quantum systems. While quantum state discrimination is well understood, quantum channel discrimination remains challenging due to the dynamic nature of…

Quantum Physics · Physics 2025-07-15 Kun Fang , Gilad Gour , Xin Wang

In this article we review the standard versions of the Central and of the Levy-Gnedenko Limit Theorems, and illustrate their application to the convolution of independent random variables associated with the distribution known as…

Soft Condensed Matter · Physics 2007-12-16 Constantino Tsallis , Silvio M. Duarte Queiros

Based on the connection between Tsallis nonextensive statistics and fractional dimensional space, in this work we have introduced, with the aid of Verlinde's formalism, the Newton constant in a fractal space as a function of the…

High Energy Physics - Theory · Physics 2015-06-17 Everton M. C. Abreu , Jorge Ananias Neto , Cresus F. L. Godinho

In 1997, Z.Zhang and R.W.Yeung found the first example of a conditional information inequality in four variables that is not "Shannon-type". This linear inequality for entropies is called conditional (or constraint) since it holds only…

Information Theory · Computer Science 2011-09-27 Tarik Kaced , Andrei Romashchenko

Shannon entropy, a cornerstone of information theory, statistical physics and inference methods, is uniquely identified by the Shannon-Khinchin or Shore-Johnson axioms. Generalizations of Shannon entropy, motivated by the study of…

Data Analysis, Statistics and Probability · Physics 2026-04-20 Andrea Somazzi , Diego Garlaschelli

We provide novel information-theoretic generalization bounds for stochastic gradient Langevin dynamics (SGLD) under the assumptions of smoothness and dissipativity, which are widely used in sampling and non-convex optimization studies. Our…

Machine Learning · Computer Science 2023-11-03 Futoshi Futami , Masahiro Fujisawa