What I am reading about the theory of counting

Information Transfer Theory

Information transfer model of natural processes:
from the ideal gas law to the distance dependent redshift

Information theory provides shortcuts which allow to deal with complex systems. The basicidea one uses for this purpose is the maximum entropy principle developed by Jaynes. However, anextensions of this maximum entropy principle to systems far from thermal equilibrium or even to non-physical systems is problematic because it requires an adequate choice of constraints. In this paperwe apply the information theory in an even more abstract way and propose an information transfer model of natural processes which requires no choice of adequate constraints.

Here is the Jaynes. He lost the flat top in later years. Wiki summarizes:

He argued that the entropy of statistical mechanics and the information entropy of information theory are principally the same thing.

 And that is our hero for today.

This reading comes from Jason Smith who uses the model for the economy in price setting.

The basics is that minimal redundancy is a unique solution for aggregate systems, under generally relaxed assumptions. The main assumption is connectivity and locality. It may take a few steps but the process knows the path. That results in Hyperbolic differential wave solutions, I think though am to lazy to proof. So, I am happy man and not so nutty after all.

What did Jaynes miss?

Physical process may be modelled as finit sample rate information flows, and give equivalent results as a dual, quantized network, the thing that computes finite log. He gets this part. He misses that they physical process are not just duals, they are infact maximum entropy wave motion exactly as specified by information flow. It is it exactly. Hence the bound uncertainty about the sample rate of light, the Higgs field is really the position quant. And Occam's Razor tells us the simplest solution is the three bubble system under a curvature gradient. Slam dunked that baby.