Walking up the 1,y,z branch, the next stable spot often jumps to one of the 2,y,z nodes, a spectral gap between emission frequencies. That is the next best estimate of N, the total number of deviations on the closed surface. It is mathematics, not physics. N is under sampled at the conditions, 3/2; and counts integers. These conditions dictate an optimum N, mathematical again. There is a finite number of ways to count by 3/2 and estimate an irrational. The bounded uncertainty in N, as a ratio, is the fine structure.
As a ratio, N uncertainty should be the same everywhere in an entropy maximizing system. It is a form of Planck and light steps and the rest.
All of this is Bayes, even PV = nRT; where we ask the partition ration for some N with path minimization R at partition ratio T.
4D markov lets the user pick an expansion that gets the system to the nearest flat plane view, and they get Shannon condition, sample rate 2, so they can do Newton's grammar about the complex plane. Nature sticks to 3D I am sure, and pays the price in kinetic energy.
The general relativity is finding the minimal error path for N. he gravitational constant is mostly a sphere packing constant in 3D., a it it were the 1,1,1 node and scaled in N. They adjust the scales on their 4D so the Markov etc condition is met. They color their euclidean beach ball white with finite tri colored buttons.
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