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In this paper, we revisit the discrete lossy Gray-Wyner problem. In particular, we derive its optimal second-order coding rate region, its error exponent (reliability function) and its moderate deviations constant under mild conditions on…

Information Theory · Computer Science 2017-01-05 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

We leverage the Gibbs inequality and its natural generalization to R\'enyi entropies to derive closed-form parametric expressions of the optimal lower bounds of $\rho$th-order guessing entropy (guessing moment) of a secret taking values on…

Information Theory · Computer Science 2024-01-31 Julien Béguinot , Olivier Rioul

Recently, a new notion of quantum R\'enyi divergences has been introduced by M\"uller-Lennert, Dupuis, Szehr, Fehr and Tomamichel, J.Math.Phys. 54:122203, (2013), and Wilde, Winter, Yang, Commun.Math.Phys. 331:593--622, (2014), that has…

Quantum Physics · Physics 2016-06-24 Milán Mosonyi

In this paper, we generalize the log-Sobolev inequalities to R\'enyi--Sobolev inequalities by replacing the entropy with the two-parameter entropy, which is a generalized version of entropy and closely related to R\'enyi divergences. We…

Probability · Mathematics 2024-07-29 Lei Yu , Hao Wu

We calculate the mutual information (MI) of a two-layered neural network with noiseless, continuous inputs and binary, stochastic outputs under several assumptions on the synaptic efficiencies. The interesting regime corresponds to the…

Disordered Systems and Neural Networks · Physics 2009-10-31 Antonio Turiel , Elka Korutcheva , Nestor Parga

We show how entanglement entropies allow for the estimation of quasi-long-range order in one dimensional systems whose low-energy physics is well captured by the Tomonaga-Luttinger liquid universality class. First, we check our procedure in…

Strongly Correlated Electrons · Physics 2015-03-19 M. Dalmonte , E. Ercolessi , L. Taddia

We establish the rate region of an extended Gray-Wyner system for 2-DMS $(X,Y)$ with two additional decoders having complementary causal side information. This extension is interesting because in addition to the operationally significant…

Information Theory · Computer Science 2018-12-11 Cheuk Ting Li , Abbas El Gamal

An important notion of common information between two random variables is due to Wyner. In this paper, we derive a lower bound on Wyner's common information for continuous random variables. The new bound improves on the only other general…

Information Theory · Computer Science 2021-02-17 Erixhen Sula , Michael Gastpar

We use phase space distributions specifically, the Wigner distribution (WD) and Husimi distribution (HD) to investigate certain information-theoretic measures as descriptors for a given system. We extensively investigate and analyze…

Entropies are fundamental measures of uncertainty with central importance in information theory and statistics and applications across all the quantitative sciences. Under a natural set of operational axioms, the most general form of…

Information Theory · Computer Science 2026-02-02 Roberto Rubboli , Erkka Haapasalo , Marco Tomamichel

This paper establishes the exact strong converse exponent of the soft covering problem in the classical setting. This exponent characterizes the slowest achievable convergence speed of the total variation to one when a code of rate below…

Information Theory · Computer Science 2026-04-01 Xingyi He , S. Sandeep Pradhan , Andreas Winter

This paper investigates Distributed Hypothesis testing (DHT), in which a source $\mathbf{X}$ is encoded given that side information $\mathbf{Y}$ is available at the decoder only. Based on the received coded data, the receiver aims to decide…

Information Theory · Computer Science 2023-05-12 Ismaila Salihou Adamou , Elsa Dupraz , Tad Matsumoto

Tsallis and R\'{e}nyi entropies, which are monotone transformations of each other, are deformations of the celebrated Shannon entropy. Maximization of these deformed entropies, under suitable constraints, leads to the $q$-exponential family…

Probability · Mathematics 2022-01-14 Ting-Kam Leonard Wong , Jun Zhang

The simplest example of a quantum information source with memory is a mixed source which emits signals entirely from one of two memoryless quantum sources with given a priori probabilities. Considering a mixed source consisting of a general…

Quantum Physics · Physics 2016-06-27 Felix Leditzky , Nilanjana Datta

Renyi entropy with multiple disjoint intervals are computed from the improved swapping operations by two methods: one is from the direct diagonalization of the Hamiltonian and the other one is from the state-of-the-art machine learning…

Statistical Mechanics · Physics 2025-10-30 Han-Qing Shi , Hai-Qing Zhang

We propose an extension of the sandwiched R\'enyi relative $\alpha$-entropy to normal positive functionals on arbitrary von Neumann algebras, for the values $\alpha>1$. For this, we use Kosaki's definition of noncommutative $L_p$-spaces…

Quantum Physics · Physics 2020-06-02 Anna Jencova

In this paper, we examine the existence of the R\'enyi divergence between two time invariant general hidden Markov models with arbitrary positive initial distributions. By making use of a Markov chain representation of the probability…

Information Theory · Computer Science 2021-06-04 Cheng-Der Fuh , Su-Chi Fuh , Yuan-Chen Liu , Chuan-Ju Wang

R\'enyi entropy is a one-parameter generalization of Shannon entropy, which has been used in various fields of physics. Despite its wide applicability, the physical interpretations of the R\'enyi entropy are not widely known. In this paper,…

Statistical Mechanics · Physics 2024-08-29 Misaki Ozawa , Nina Javerzat

An information theoretic approach to bounds in superconformal field theories is proposed. It is proved that the supersymmetric R\'enyi entropy $\bar S_\alpha$ is a monotonically decreasing function of $\alpha$ and $(\alpha-1)\bar S_\alpha$…

High Energy Physics - Theory · Physics 2023-03-03 Yang Zhou

Measuring the relationship between any pair of variables is a rich and active area of research that is central to scientific practice. In contrast, characterizing the common information among any group of variables is typically a…

Machine Learning · Statistics 2017-06-20 Greg Ver Steeg , Shuyang Gao , Kyle Reing , Aram Galstyan