Making the M+1 world from the M world

This one is fun, at stability we have a distributive property on error generators.  So we imagine the fourth prime wants to organize all the spheres of the three primes. I just needs to feed them via the entanglement, which becomes one Poisson queue feeding another. But, with distributive property, we can move that down the generator tree. life is dandy when your little guys make a ring, is what the mathematicians call it.

So that proves it, the M  dimensional world is a set of the first M primes serving as arrival rates for a M coloring of a beach ball, but frozen to a constant to the unique nearest integer set of error updates. There is a point of maximum multiplicity, always.

I need to mention one thing. The error generator basically groups the update events that are equally likely at each step of the generator.  These are not maximizing entropy, else they would be unique. Then the error generator emits the most likely and steps down the tree, which in 3D is the bottom, the error account, and it gets the least likely. The tree carries the equally likely in the tree until resolved. This is the minimal pruning of a M factorial tree.

The entanglement issue is all about N, it is not known anymore precisely then the multiplicity. The kinetic mismatch with out of count species ultimately stabilizes local N density. Think directed graph, no loops under stable flow. Then we get the proofs we need for theory if you can get that model. Entropy maximizing (or equally, Redundancy minimizing )model.  Redundancy minimizing is the easier term, Boltzmann hard a hard time explaining the other. Really, removing the 'been there, done that'  paths in the graph and keeping a straight path along the 'deju vu'.

So it is simple to understand the 4D standard model.  There are two charge types, one at 1/3, and the other at 1/5, and they can both emit and leave the new magnetic field to reverts thins to precision. So if the three eyed human squints a bit, it can pick differing photon paths back to the source and get some split resolution and focus. Light is still constant as the number of steps through the error generator. The photons just take more or else curved paths. So the images are slightly out of resolution,  as we have in 3D optics on focus.

In optics, the Fraunhofer diffraction equation is used to model the diffraction of waves when the diffraction pattern is viewed at a long distance from the diffracting object, and also when it is viewed at the focal plane of an imaging lens.^[1][2] In contrast, the diffraction pattern created near the object, in the near field region, is given by the Fresnel diffraction equation.

We see the slight interference pattern by slightly defocusing.  We still will do this in 4D. If you made a microscope with perfect focus you would always see a dot. Defocus see more stuff but slightly fuzzy.