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When Coincidence has Meaning: Understanding Emergence Through Networks of Information Token Recurrence

2019/11/14 by Markus Luczak–Roesch, Markus Luczak-Roesch, Luczak-Roesch, Markus
Biochemistry, Genetics and Molecular Biology · Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Chaotic Dynamics (nlin.CD) #Complex Systems and Time Series Analysis #Data Analysis #Dynamical Systems (math.DS) #FOS: Mathematics #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Protein Structure and Dynamics #Statistics and Probability (physics.data-an) #math.DS #nlin.CD #physics.data-an #physics.soc-ph

paper · pdf · doi:10.48550/arxiv.1911.07642

13 pages, this conceptual paper is based on a number of talks I gave on the underlying idea and synthesises a research programme that is work in progress

arxiv created 2019/11/14 · openalex publication_date 2019/11/14 · arxiv updated 2019/11/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper I conceptualise a novel approach for capturing coincidences between events that have not necessarily an observed causal relationship. Building on the Transcendental Information Cascades approach I outline a tensor theory of the interaction between rare micro-level events and macro-level system changes. Afterwards, I discuss a number of application areas that are promising candidates for the validation of the theoretical assumptions outlined here in practice. This is preliminary work that is sought to lay the foundation to discover universal mathematical properties of coincidences that have a measurable impact on the macroscopic state of a complex system and are therefore to be considered meaningful.

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