Fine structure, part 7

I suggested the fine srcture was related to the maximum entropy point by representing the modes of kinetic energy.

Define the kinetic energy as the relative change in mass of the system.  There is some variation in N, a fuzzy constant. Vacuum leaves and enters the system.  Then if we know the maximum entropy point as an integer, under quant rules, then we should also know that residual error in that point relative to perfect irrationality.

And, there should be a connection between that varying N and Planck. And the spread of the residual N should determine any symmetry around that spectral peak. This should be about a rotation around the Markov tree.

What am I noticing?

A bunch of prime numbers show up in the seemingly proper relationship to get all out physical constants.  But we would have expected that anyway as physicists reduced the problem. There are only so many small primes needed. The game got reversed, it became a game of reducing the outcome of physics to the fewest combinatorials.

But that is not all true. We connect the dots here when we consider the fuzzy distribution of N.   Then total energy makes us account for that, kinetic energy., and it must be undersampled operator in the next energy level. It makes some sense, and it connects all the physical constants to the integer. But it only rhymes with the atomic orbitals. The largest integer is the total integer count across all the energy levels, ignoring kinetic energy.

If you are measuring proton wobble then you are forcing the system to enter that next orbital.    And the ratio will always come out with that next  (1,x,y) tuple above as you are measuring on the soin axis. But the numbers fit, it was done right. I think the physicists managed a square root in correcting for their instrument. The interpretation needs a change. What is the momentum effect between electron and proton when nudged by the minimal force. They could cool and tune until they have just filled the next level, instrument and proton. Perfect, they adjusted for the variation in N.

So fine structure is a flat surface resolution.  It is actually the hemisphere surface, the Lie grid.  Hence Pi appears due to Euclidean mapping. A neat trick because it is essentially log grid, tuned to the 3D.  thus it automatically goes from sample space to Bayesian space.



This definition givers 1/137.  Break it up and I get:

The number pf planks that fit into a number of charges, broken up into 137 slices of the Lie pie. Area matching to flat surface. The c along with epsilon are the selected scale of path length to rectangular length. My simplification might be to let light equal two, then select a denominator that suits.

The physicists are very good at just filling up he next energy level. They do so by counting up Planks that fit into a sphere with the proper coulomb count.  They can tell when those tow counts are as good as possible getting the 137.  And that flattens out to a Lie log paper.