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Related papers: Encoding Tasks and R\'enyi Entropy

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This paper deals with rate distortion or source coding with fidelity criterion, in measure spaces, for a class of source distributions. The class of source distributions is described by a relative entropy constraint set between the true and…

Information Theory · Computer Science 2013-05-07 Farzad Rezaei , Charalambos D. Charalambous , Photios A. Stavrou

This paper studies the complexity of estimating Renyi divergences of discrete distributions: $p$ observed from samples and the baseline distribution $q$ known \emph{a priori}. Extending the results of Acharya et al. (SODA'15) on estimating…

Information Theory · Computer Science 2017-02-09 Maciej Skorski

We ask the question whether entropy accumulates, in the sense that the operationally relevant total uncertainty about an $n$-partite system $A = (A_1, \ldots A_n)$ corresponds to the sum of the entropies of its parts $A_i$. The Asymptotic…

Quantum Physics · Physics 2022-10-05 Frederic Dupuis , Omar Fawzi , Renato Renner

In data-driven determination of Parton Distribution Functions (PDFs) in global QCD analyses, uncovering the true underlying distributions is complicated by a highly convoluted inverse problem. The determination of PDFs can be understood as…

High Energy Physics - Phenomenology · Physics 2025-11-12 Aurore Courtoy , Arturo Ibsen

We set out to demonstrate that the R\'enyi entropies with parameter $\alpha$ are better thought of as operating in a type of non-linear semiring called a positive semifield. We show how the R\'enyi's postulates lead to Pap's g-calculus…

Information Theory · Computer Science 2019-06-04 Francisco J. Valverde-Albacete , Carmen Peláez-Moreno

We study entropy-bounded computational geometry, that is, geometric algorithms whose running times depend on a given measure of the input entropy. Specifically, we introduce a measure that we call range-partition entropy, which unifies and…

Computational Geometry · Computer Science 2025-08-29 David Eppstein , Michael T. Goodrich , Abraham M. Illickan , Claire A. To

Scrambling is a process by which the state of a quantum system is effectively randomized due to the global entanglement that "hides" initially localized quantum information. In this work, we lay the mathematical foundations of studying…

Quantum Physics · Physics 2018-07-10 Zi-Wen Liu , Seth Lloyd , Elton Yechao Zhu , Huangjun Zhu

Estimating entropies from limited data series is known to be a non-trivial task. Naive estimations are plagued with both systematic (bias) and statistical errors. Here, we present a new 'balanced estimator' for entropy functionals Shannon,…

Statistical Mechanics · Physics 2008-04-30 Juan A. Bonachela , Haye Hinrichsen , Miguel A. Munoz

We revisit generalized entropic formulations of the uncertainty principle for an arbitrary pair of quantum observables in two-dimensional Hilbert space. R\'enyi entropy is used as uncertainty measure associated with the distribution…

Quantum Physics · Physics 2014-06-23 Steeve Zozor , Gustavo Martín Bosyk , Mariela Portesi

A receiver wants to compute a function of two correlated sources separately observed by two transmitters. One of the transmitters may send a possibly private message to the other transmitter in a cooperation phase before both transmitters…

Information Theory · Computer Science 2015-04-08 Milad Sefidgaran , Aslan Tchamkerten

R\'enyi entropies are conceptually valuable and experimentally relevant generalisations of the celebrated von Neumann entanglement entropy. After a quantum quench in a clean quantum many-body system they generically display a universal…

Statistical Mechanics · Physics 2022-08-04 Bruno Bertini , Katja Klobas , Vincenzo Alba , Gianluca Lagnese , Pasquale Calabrese

The penalty incurred by imposing a finite delay constraint in lossless source coding of a memoryless source is investigated. It is well known that for the so-called block-to-variable and variable-to-variable codes, the redundancy decays at…

Information Theory · Computer Science 2016-11-17 Ofer Shayevitz , Eado Meron , Meir Feder , Ram Zamir

It is well known that the entropy $H(X)$ of a discrete random variable $X$ is always greater than or equal to the entropy $H(f(X))$ of a function $f$ of $X$, with equality if and only if $f$ is one-to-one. In this paper, we give tight…

Information Theory · Computer Science 2017-12-22 Ferdinando Cicalese , Luisa Gargano , Ugo Vaccaro

Backwards analysis, first popularized by Seidel, is often the simplest most elegant way of analyzing a randomized algorithm. It applies to incremental algorithms where elements are added incrementally, following some random permutation,…

Data Structures and Algorithms · Computer Science 2017-04-18 Mathias Bæk Tejs Knudsen , Mikkel Thorup

We introduce a novel notion of invariance feedback entropy to quantify the state information that is required by any controller that enforces a given subset of the state space to be invariant. We establish a number of elementary properties,…

Systems and Control · Computer Science 2019-08-07 Mahendra Singh Tomar , Matthias Rungger , Majid Zamani

We study how the Shannon entropy of sequences produced by an information source converges to the source's entropy rate. We synthesize several phenomenological approaches to applying information theoretic measures of randomness and memory to…

Statistical Mechanics · Physics 2007-05-23 James P. Crutchfield , David P. Feldman

Computational complexity is examined using the principle of increasing entropy. To consider computation as a physical process from an initial instance to the final acceptance is motivated because many natural processes have been recognized…

Computational Complexity · Computer Science 2012-03-20 Arto Annila

We consider a simplified version of a solvable model by Mandal and Jarzynski, which constructively demonstrates the interplay between work extraction and the increase of the Shannon entropy of an information reservoir which is in contact…

Statistical Mechanics · Physics 2015-03-31 Neri Merhav

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 prove a lower estimate on the increase in entropy when two copies of a conditional random variable $X | Y$, with $X$ supported on $\mathbb{Z}_q=\{0,1,\dots,q-1\}$ for prime $q$, are summed modulo $q$. Specifically, given two i.i.d copies…

Information Theory · Computer Science 2014-11-27 Venkatesan Guruswami , Ameya Velingker