Aut-the parmenides requirement

The charts that are generated from the various features of the equations that average in a compression state to what we observe.

The key to understanding the relationships is to understanding that the geometrical relationships are built on the base mathematics.  Slope and dimension are secondary effects to the underlying algorithm.

As long as the fantasy of reality is solved based on fixed values of n (the single variable) there are solutions to otherwise infinite series and the Parmenides requirement is met.  Hence you have the solutions yield the graphs on the right so that the approximation of angles, due to the approach of x to infinity, appear to exist despite their illusory nature, that is there is not center to a circle, only a specific number for pi allowing the illusion that the solution and an actual angle, shown on the left, exists.  Similarly the exact wave function is only an approximation based on very specific inflection points from a fixed value of the information involved. 

Over the next few posts, I am going to be clearing this part of up.  I could go back and edit the old posts as I am sort of doing now by writing this, but I think it makes little difference.

For book 3 which is essentially 60,000 words long with the words in pictures, I am 1/3 of the way through on chapter 27 page 44.  I may break it into small parts but I am not in a hurry since the leaps of mathematics are stumbles and book 2, which I need to read again, needs to be written into book 3's disclosures.  Thankfully book 2 is short. 

While you don't see much in what occurs below, it is important because between the disclosures lies the underling explanations for relationships that lead to stacking and compression.  I only have to look backwards through the mirror hard enough and I will see it.

Base equations Fibonacci Series N=n-1+n-2;f(n)=n+n-1+n-2 Information theory based on two solution bits I=2^n	Converts under compression to (F(n)^(2^n)
F(pix)=n/[n+n/f(pluspix)] F(pluspix) based on -1^n: )=[(-1)^x]+[2x(-1)^x-1] yielding the denominator of pi The theorized global modeling function for maximum compression and decompression X^1/x and Converging series solution to the globel modeling function e=sum(x=0 to inf)1/x!=1/1+1/(1*1)+1/(1*2)+1/(1*2*3)+… vs the alternate definition of (1+1/n)^n And the single variable algorithm x which varies by compression state. Since e can be derived from algebra where inf=x for any maximum amount of information, it is possible to get to a state type equation based on nothing more than the changing value of x for F(n) and e(n) where n represents the maximum value of x based on Sum(k) for compression and the value of 1/k! for the point of compression.	This combination results in compression y(t)=A*sin(wt+phi) where w=2pif(rad/s) for pi(n) where n=4 and with one observed model for a lower ct state being: C(t)=E(1-e^-t/RC) where 1/x corresponds to –(t/RC) corresponding to an evolving value of e and the resulting evolution of pi and decompression is defined by D(t)=QRCe^-t/RC which is the opposite effect.
The global max of f(x)=x^1/x is at e compare (f(n)-^2^n).  as a location of the  phase shift which generates pi (figure 8 below). Sin and cos vary between 1 and negative 1 just as f(pluspix). At the quantum level these are the same, but they diverge and hence the consistence (pluses in a row) of f(pluspix) must increase as you get compression.	C(t) corresponds to C(x-1) in the compression approximation.