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Related papers: Quantifying synergistic mutual information

200 papers

We present a generalized information-theoretic measure of synchronization in quantum systems. This measure is applicable to dynamics of anharmonic oscillators, few-level atoms, and coupled oscillator networks. Furthermore, the new measure…

Shannon mutual information provides a measure of how much information is, on average, contained in a set of neural activities about a set of stimuli. It has been extensively used to study neural coding in different brain areas. To apply a…

Neurons and Cognition · Quantitative Biology 2007-05-23 Michele Bezzi

The information theoretic quantity known as mutual information finds wide use in classification and community detection analyses to compare two classifications of the same set of objects into groups. In the context of classification…

Social and Information Networks · Computer Science 2020-04-29 M. E. J. Newman , George T. Cantwell , Jean-Gabriel Young

The information shared among observables representing processes of interest is traditionally evaluated in terms of macroscale measures characterizing aggregate properties of the underlying processes and their interactions. Traditional…

Information Theory · Computer Science 2018-01-31 Rui A. P. Perdigão

An information theoretic measure is derived that quantifies the statistical coherence between systems evolving in time. The standard time delayed mutual information fails to distinguish information that is actually exchanged from shared…

Chaotic Dynamics · Physics 2009-10-31 Thomas Schreiber

This article introduces a model-agnostic approach to study statistical synergy, a form of emergence in which patterns at large scales are not traceable from lower scales. Our framework leverages various multivariate extensions of Shannon's…

Information Theory · Computer Science 2019-09-18 Fernando Rosas , Pedro A. M. Mediano , Michael Gastpar , Henrik J. Jensen

Fields like public health, public policy, and social science often want to quantify the degree of dependence between variables whose relationships take on unknown functional forms. Typically, in fact, researchers in these fields are…

Statistics Theory · Mathematics 2019-12-10 Octavio César Mesner , Cosma Rohilla Shalizi

To fully characterize the information that two `source' variables carry about a third `target' variable, one must decompose the total information into redundant, unique and synergistic components, i.e. obtain a partial information…

Information Theory · Computer Science 2015-05-13 Adam B. Barrett

Relevance of key quantum information measures for analysis of quantum systems is discussed. It is argued that possible ways of measuring quantum information are based on compatibility/incompatibility of the quantum states of a quantum…

Quantum Physics · Physics 2015-06-26 B. A. Grishanin , V. N. Zadkov

For readers already familiar with Partial Information Decomposition (PID), we show that PID's definition of synergy enables quantifying at least four different notions of irreducibility. First, we show four common notions of "parts" give…

Information Theory · Computer Science 2013-12-13 Virgil Griffith , Jonathan Harel

The decomposition of channel information into synergies of different order is an open, active problem in the theory of complex systems. Most approaches to the problem are based on information theory, and propose decompositions of mutual…

Information Theory · Computer Science 2015-12-14 Paolo Perrone , Nihat Ay

A novel measure, quantumness of correlations is introduced here for bipartite states, by incorporating the required measurement scheme crucial in defining any such quantity. Quantumness coincides with the previously proposed measures in…

Quantum Physics · Physics 2008-04-20 A. R. Usha Devi , A. K. Rajagopal

Scientists often seek simplified representations of complex systems to facilitate prediction and understanding. If the factors comprising a representation allow us to make accurate predictions about our system, but obscuring any subset of…

Machine Learning · Computer Science 2017-10-12 Greg Ver Steeg , Rob Brekelmans , Hrayr Harutyunyan , Aram Galstyan

Forecasting techniques for assessing the power of future experiments to discriminate between theories or discover new laws of nature are of great interest in many areas of science. In this paper, we introduce a Bayesian forecasting method…

Data Analysis, Statistics and Probability · Physics 2024-09-24 Mohammad Hossein Namjoo

Estimating mutual information from observed samples is a basic primitive, useful in several machine learning tasks including correlation mining, information bottleneck clustering, learning a Chow-Liu tree, and conditional independence…

Information Theory · Computer Science 2018-10-11 Weihao Gao , Sreeram Kannan , Sewoong Oh , Pramod Viswanath

Quantifying coherence has received increasing attention, and considerable work has been directed towards finding coherence measures. While various coherence measures have been proposed in theory, an important issue following is how to…

Quantum Physics · Physics 2018-05-02 Da-Jian Zhang , C. L. Liu , Xiao-Dong Yu , D. M. Tong

Reshef et al. recently proposed a new statistical measure, the "maximal information coefficient" (MIC), for quantifying arbitrary dependencies between pairs of stochastic quantities. MIC is based on mutual information, a fundamental…

Quantitative Methods · Quantitative Biology 2015-06-12 Justin B. Kinney , Gurinder S. Atwal

The phenomenon of spontaneous synchronization is universal and only recently advances have been made in the quantum domain. Being synchronization a kind of temporal correlation among systems, it is interesting to understand its connection…

Quantum Physics · Physics 2018-02-13 Fernando Galve , Gian Luca Giorgi , Roberta Zambrini

The concept of randomized measurements on individual particles has proven to be useful for analyzing quantum systems and is central for methods like shadow tomography of quantum states. We introduce $\textit{collective}$ randomized…

Quantum Physics · Physics 2024-08-12 Satoya Imai , Géza Tóth , Otfried Gühne

The problem of how to properly quantify redundant information is an open question that has been the subject of much recent research. Redundant information refers to information about a target variable S that is common to two or more…

Information Theory · Computer Science 2017-07-14 Robin A. A. Ince