Infodynamics

Abstract

The title for this was almost "Is Matter in our Universe Performing Asymmetric Hypothesis Tests to Find Itself?", but the work isn't complete. The work here is a preliminary description of how information may be represented similarly to thermodynamic quantities. There are obvious applications to machine learning/AI, but potentially there is also a physical understanding. The work so far looks at distribution tests, outlier detection, and classification. The understanding / approach detailed is completely nonparametric and easily programmed. The main idea is then extrapolated to the physical world by the Hiesenberg Uncertainty Principle , and starts to explain phenomena such as the Casimir effect without the need for the machinery in quantum field theory. Although this is preliminary , I decided to share this publicly because I want to discuss some of the ideas with a select group of people and look for interested parties for collaboration.