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MiS Preprint Repository

We have decided to discontinue the publication of preprints on our preprint server as of 1 March 2024. The publication culture within mathematics has changed so much due to the rise of repositories such as ArXiV (www.arxiv.org) that we are encouraging all institute members to make their preprints available there. An institute's repository in its previous form is, therefore, unnecessary. The preprints published to date will remain available here, but we will not add any new preprints here.

MiS Preprint
75/2020

Confounding Ghost Channels and Causality: A New Approach to Causal Information Flows

Nihat Ay

Abstract

Information theory provides a fundamental framework for the quantification of information flows through channels, formally Markov kernels. However, quantities such as mutual information and conditional mutual information do not necessarily reflect the causal nature of such flows. We argue that this is often the result of conditioning based on sigma algebras that are not associated with the given channels. We propose a version of the (conditional) mutual information based on families of sigma algebras that are coupled with the underlying channel. This leads to filtrations which allow us to prove a corresponding causal chain rule as a basic requirement within the presented approach.

Received:
Jul 7, 2020
Published:
Jul 7, 2020
Keywords:
information flow, causality, mutual information, conditional mutual information, filtration

Related publications

inJournal
2021 Journal Open Access
Nihat Ay

Confounding ghost channels and causality : a new approach to causal information flows

In: Vietnam journal of mathematics, 49 (2021) 2, pp. 547-576