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Related papers: The problem of infinite information flow

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We propose a novel approach framed in terms of information theory and entropy to tackle the issue of conspiracy theories propagation. We start with the report of an event (such as 9/11 terroristic attack) represented as a series of…

Physics and Society · Physics 2015-10-28 Natasa Golo , Serge Galam

Mutual Information (MI) and Conditional Mutual Information (CMI) are multi-purpose tools from information theory that are able to naturally measure the statistical dependencies between random variables, thus they are usually of central…

Machine Learning · Computer Science 2022-11-22 Bao Duong , Thin Nguyen

We provide a unified thermodynamic formalism describing information transfers in autonomous as well as nonautonomous systems described by stochastic thermodynamics. We demonstrate how information is continuously generated in an auxiliary…

Statistical Mechanics · Physics 2014-08-06 Jordan M. Horowitz , Massimiliano Esposito

'Causal' direction is of great importance when dealing with complex systems. Often big volumes of data in the form of time series are available and it is important to develop methods that can inform about possible causal connections between…

Statistical Mechanics · Physics 2014-01-24 Fatimah Abdul Razak , Henrik Jeldtoft Jensen

Traditional channel capacity based on the discrete spatial dimensions mismatches the continuous electromagnetic fields. For the wireless communication system in a limited region, the spatial discretization may results in information loss…

Information Theory · Computer Science 2023-02-21 Zhongzhichao Wan , Jieao Zhu , Zijian Zhang , Linglong Dai , Chan-Byoung Chae

Making decisions freely presupposes that there is some indeterminacy in the environment and in the decision making engine. The former is reflected on the behavioral changes due to communicating: few changes indicate rigid environments;…

Artificial Intelligence · Computer Science 2020-09-23 Luis A. Pineda

Maximum entropy estimation is of broad interest for inferring properties of systems across many different disciplines. In this work, we significantly extend a technique we previously introduced for estimating the maximum entropy of a set of…

Data Analysis, Statistics and Probability · Physics 2016-01-05 Elliot A. Martin , Jaroslav Hlinka , Alexander Meinke , Filip Děchtěrenko , Jörn Davidsen

Identifying the central people in information flow networks is essential to understanding how people communicate and coordinate as well as who controls the information flows in the network. However, the appropriate usage of centrality…

Social and Information Networks · Computer Science 2018-12-17 Chintan Amrit , Joanne ter Maat

Constraints on entropies are considered to be the laws of information theory. Even though the pursuit of their discovery has been a central theme of research in information theory, the algorithmic aspects of constraints on entropies remain…

Information Theory · Computer Science 2020-04-28 Mahmoud Abo Khamis , Phokion G. Kolaitis , Hung Q. Ngo , Dan Suciu

Turbulence theory is usually concerned with the statistical moments of the velocity or its fluctuations. One could also analyze the implicit probability distributions. This is the purview of information theory. Here we use information…

Chaotic Dynamics · Physics 2016-02-15 Rory T. Cerbus , Walter I. Goldburg

Mutual information is used as a purely geometrical regularization of entanglement entropy applicable to any QFT. A coefficient in the mutual information between concentric circular entangling surfaces gives a precise universal prescription…

High Energy Physics - Theory · Physics 2015-06-23 Horacio Casini , Marina Huerta , Robert C. Myers , Alexandre Yale

These lectures deal with the problem of inductive inference, that is, the problem of reasoning under conditions of incomplete information. Is there a general method for handling uncertainty? Or, at least, are there rules that could in…

Data Analysis, Statistics and Probability · Physics 2016-09-08 Ariel Caticha

Mutual information $I(X;Y)$ is a useful definition in information theory to estimate how much information the random variable $Y$ holds about the random variable $X$. One way to define the mutual information is by comparing the joint…

Information Theory · Computer Science 2022-04-14 Bulut Kuskonmaz , Jaron Skovsted Gundersen , Rafal Wisniewski

The uncertainty principle can be expressed in entropic terms, also taking into account the role of entanglement in reducing uncertainty. The information exclusion principle bounds instead the correlations that can exist between the outcomes…

Quantum Physics · Physics 2014-02-26 Patrick J. Coles , Marco Piani

Information transfer between coupled stochastic dynamics, measured by transfer entropy and information flow, is suggested as a physical process underlying the causal relation of systems. While information transfer analysis has booming…

Statistical Mechanics · Physics 2022-04-29 Yang Tian , Hedong Hou , Yaoyuan Wang , Ziyang Zhang , Pei Sun

In this paper we aim to find a measure for the diversity of cash flows between agents in an economy. We argue that cash flows can be linked to probabilities of finding a currency unit in a given cash flow. We then use the information…

General Finance · Quantitative Finance 2013-01-24 Ulrich Kirchner , Simon Moolman

Information estimates such as the ``direct method'' of Strong et al. (1998) sidestep the difficult problem of estimating the joint distribution of response and stimulus by instead estimating the difference between the marginal and…

Neurons and Cognition · Quantitative Biology 2008-07-19 Vincent Q. Vu , Bin Yu , Robert E. Kass

In this paper, we show through examples, how the existing definitions of information transfer, namely directed information and transfer entropy fail to capture true causal interaction between states in control dynamical system. We propose a…

Optimization and Control · Mathematics 2018-07-24 Subhrajit Sinha , Umesh Vaidya

A new finite form of de Finetti's representation theorem is established using elementary information-theoretic tools. The distribution of the first $k$ random variables in an exchangeable vector of $n\geq k$ random variables is close to a…

Information Theory · Computer Science 2024-04-29 Mario Berta , Lampros Gavalakis , Ioannis Kontoyiannis

A message of any sort can be regarded as a source of information. Claude. E. Shannon showed in the last century that information ("what we don't already know") is equivalent to the entropy as defined in statistical mechanics. A string of…

Fluid Dynamics · Physics 2016-09-05 W. I. Goldburg , R. T. Cerbus