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We survey the different properties of an intuitive notion of redundancy, as a function of the precise semantics given to the notion of partial implication. The final version of this survey will appear in the Proceedings of the Int. Conf.…

Logic in Computer Science · Computer Science 2015-04-15 José L. Balcázar

These notes pose a "proof challenge": a proof, or disproof, of the proposition that "For any given body of information, I, expressed as a one-dimensional sequence of atomic symbols, a multiple alignment concept, described in the document,…

Artificial Intelligence · Computer Science 2014-03-06 J Gerard Wolff

Factor graphs are a ubiquitous tool for multi-source inference in robotics and multi-sensor networks. They allow for heterogeneous measurements from many sources to be concurrently represented as factors in the state posterior distribution,…

Information Theory · Computer Science 2023-03-14 Jesse Milzman , Andre Harrison , Carlos Nieto-Granda , John Rogers

Quantum Darwinism recognizes the role of the environment as a communication channel: Decoherence can selectively amplify information about the pointer states of a system of interest (preventing access to complementary information about…

Quantum Physics · Physics 2016-08-23 Michael Zwolak , C. Jess Riedel , Wojciech H. Zurek

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Robin A. A. Ince , Stefano Panzeri , Simon R. Schultz

We consider an approximation scheme for multivariate information assuming that synergistic information only appearing in higher order joint distributions is suppressed, which may hold in large classes of systems. Our approximation scheme…

Methodology · Statistics 2020-09-03 Masahiro Takimoto

The framework of Partial Information Decomposition (PID) unveils complex nonlinear interactions in network systems by dissecting the mutual information (MI) between a target variable and several source variables. While PID measures have…

Data Analysis, Statistics and Probability · Physics 2024-09-23 Chiara Barà , Yuri Antonacci , Marta Iovino , Ivan Lazic , Luca Faes

We study quantum Darwinism--the redundant recording of information about the preferred states of a decohering system by its environment--for an object illuminated by a black body. In the cases of point-source and isotropic illumination, we…

Quantum Physics · Physics 2010-07-13 C. Jess Riedel , Wojciech H. Zurek

We present a possible approach to the study of the renormalization group (RG) flow based entirely on the information theory. The average information loss under a single step of Wilsonian RG transformation is evaluated as a conditional…

Statistical Mechanics · Physics 2011-10-13 S. M. Apenko

This paper presents a generalization of the disjunctive paraconsistent relational data model in which disjunctive positive and negative information can be represented explicitly and manipulated. There are situations where the closed world…

Databases · Computer Science 2007-05-23 Haibin Wang , Yuanchun He , Rajshekhar Sunderraman

Consider a joint quantum state of a system and its environment. A measurement on the environment induces a decomposition of the system state. Using algorithmic information theory, we define the preparation information of a pure or mixed…

Quantum Physics · Physics 2015-06-26 Andrei N. Soklakov , Ruediger Schack

Accurately determining dependency structure is critical to discovering a system's causal organization. We recently showed that the transfer entropy fails in a key aspect of this---measuring information flow---due to its conflation of dyadic…

Information Theory · Computer Science 2017-11-22 Ryan G. James , James P. Crutchfield

A general notion of information-related complexity applicable to both natural and man-made systems is proposed. The overall approach is to explicitly consider a rational agent performing a certain task with a quantifiable degree of success.…

Data Analysis, Statistics and Probability · Physics 2013-01-18 Eugene Perevalov , David Grace

As conventional communication systems based on classic information theory have closely approached the limits of Shannon channel capacity, semantic communication has been recognized as a key enabling technology for the further improvement of…

Information Theory · Computer Science 2023-06-06 Jiancheng Tang , Qianqian Yang , Zhaoyang Zhang

Entropy and information provide natural measures of correlation among elements in a network. We construct here the information theoretic analog of connected correlation functions: irreducible $N$--point correlation is measured by a decrease…

Biological Physics · Physics 2016-09-08 Elad Schneidman , Susanne Still , Michael J. Berry , William Bialek

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

Amplification was regarded, since the early days of quantum theory, as a mysterious ingredient that endows quantum microstates with macroscopic consequences, key to the "collapse of the wavepacket", and a way to avoid embarrassing problems…

Quantum Physics · Physics 2014-04-15 Michael Zwolak , C. Jess Riedel , Wojciech H. Zurek

We deploy Shannon's information entropy to the distribution of branching fractions in a particle decay. This serves to quantify how important a given new reported decay channel is, from the point of view of the information that it adds to…

Given two channels that convey information about the same random variable, we introduce two measures of the unique information of one channel with respect to the other. The two quantities are based on the notion of generalized weighted Le…

Information Theory · Computer Science 2019-12-10 Pradeep Kr. Banerjee , Eckehard Olbrich , Jürgen Jost , Johannes Rauh

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
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