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Open AccessArticle

Information Gain in Event Space Reflects Chance and Necessity Components of an Event

University of Cincinnati, Cincinnati, OH 45221, USA
Information 2019, 10(11), 358; https://doi.org/10.3390/info10110358
Received: 23 October 2019 / Revised: 8 November 2019 / Accepted: 15 November 2019 / Published: 19 November 2019
Information flow for occurrences in phase space can be assessed through the application of the Lyapunov characteristic exponent (multiplicative ergodic theorem), which is positive for non-linear systems that act as information sources and is negative for events that constitute information sinks. Attempts to unify the reversible descriptions of dynamics with the irreversible descriptions of thermodynamics have replaced phase space models with event space models. The introduction of operators for time and entropy in lieu of traditional trajectories has consequently limited—to eigenvectors and eigenvalues—the extent of knowable details about systems governed by such depictions. In this setting, a modified Lyapunov characteristic exponent for vector spaces can be used as a descriptor for the evolution of information, which is reflective of the associated extent of undetermined features. This novel application of the multiplicative ergodic theorem leads directly to the formulation of a dimension that is a measure for the information gain attributable to the occurrence. Thus, it provides a readout for the magnitudes of chance and necessity that contribute to an event. Related algorithms express a unification of information content, degree of randomness, and complexity (fractal dimension) in event space. View Full-Text
Keywords: chance; necessity; trajectory; phase space; operator; event space chance; necessity; trajectory; phase space; operator; event space
MDPI and ACS Style

Weber, G.F. Information Gain in Event Space Reflects Chance and Necessity Components of an Event. Information 2019, 10, 358.

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