is there antimatter 3

This post is a little complicated, but will conceptually lays out the AuT-Matter/Anti Matter argument by way of example.  While a single model is used for reasons given below, other models, loosely within this framework, can exist.  This will likely end this series which serves the purpose of providing a possible mechanism for defining how AuT addresses the issue of matter and anti-matter.

IDEA: The idea is that the "state" of fpix drives Matter vs anti-matter.

FRAMEWORK: To make this argument, we have to understand how fpix states build.
How do the positive and negative results at the fpix level (ct1 space) build.

We already know that actual compression is loading of ct2 arms with ct1.  So the only effect that fpix solutions can have is how those arms load or what the resulting charge of the loaded arms equals.

If we look at the model there is are two sides of each arm, the 2 if the 2f(x) portion of the compression equation.

We can assume these arms are positive and negative fpix states for ct1 loaded onto ct2, but which side is positive and which is negative can vary and this variance can give rise to the matter/antimatter difference, by way of example. 

There are extensive discussions regarding this already set out in books 1-6 of Algorithm Universe theory. 
The net positive vs net negative results in terms of quantity give a reason why we might observe more matter than anti-matter although the exact mechanism and how it is tied to sequential solution order is a more involved question.

BASED EQUATION: Let us look at the parts of the fpix equation:
1) The equation itself: (-1^x+2x(-1)^x-1)
2) The results 
     a) Alternating positive and negative solutions
     b) Separation of results equal to 4x (-3 to 5 is an absolute value 2*4=8, for example.  Note 1 to -3 is 4)
          Note: fpix solutions can start for x=1, although this draws a solution from -1^0
     c) x as a counter for marking separation
     d) Possible common solution orders
     e) An absolute total (compare to the separation total of non absolute) as a f(x) solution.
    
EXAMPLE: The idea is that this relatively simple equation with a single variable generates a number of different results.
The number of ways these results might be generated is also subject to many different conceptual framework and for comparison purposes, several are give below,  but if AuT has taught us anything, what it teaches is that the model must match observation and must be consistent, it must generate the observed results.
For this, the generated result for Fpix must generate a Fibonacci framework and, thankfully, this can occur from this equation.

x	ABS Sum
	Also Total	fpix
	0
1	3	-3
2	8	5	-3
3	15	-7	5	-3
4	24	9	-7	5	-3
5	35	-11	9	-7	5	-3
6	48	13	-11	9	-7	5	-3
7	63	-15	13	-11	9	-7	5	-3
8	80	17	-15	13	-11	9	-7	5	-3
9	99	-19	17	-15	13	-11	9	-7	5	-3
column sum		-11	8	-9	6	-7	4	-5	2	-3

The example above shows one way in which Fpix can generate Fpix to f(x) solutions using this single equation and memorized results.

This chart shows a very early universe, x=9.  The universe at x=1 would only have the first two columns filled with 3 and -3 respectively.  For x=2 you would add the second column starting at 8.

As can be seen, if you do the absolute sum of any row=sum of abs(x-1)+fpix.  While not strictly an f-series equation, it works according to the same basic principle.


Here are some features of this simple chart:

4*x	regular sum	difference	sum	x
separation	each column	from	all columns
from prior	d-k	prior m	c-h
4	-3		-3	1
8	2	5	-1	2
12	-5	-7	-6	3
16	4	9	-2	4
20	-7	-11	-9	5
24	6	13	-3	6
28	-9	-15	-12	7
32	8	17	-4	8
36	-11	-19	-15	9

It is worth noting before we discuss this chart that it is one of many ways to look at how this combination occurs.  This is the most simple method.  While other variations are discussed below, there is not enough information from which to pick one or the other at this stage.  Instead, the intent is just to pick an example to show: 1) how fpix can transition to f(x); (2) how fpix can lead to either a single value (all negative in the 4th column above) or to alternating periods of net positive or negative (column 2 above) and to show how the separation can increase between individual solutions but lso how they can transition from net solution.

Moreover, the solution can have common solution order by column (or even row) relative to other columns giving a situation where there is a dimensional character and a non dimensional characteristic based on these ratios.  Going from left to right you have the first 3 columns totalling 1) -3, 2) 2, 3)-5, 4)4, 5)-7 so if you were able to combine rows, you would have a net -1 for the first two, just by way of example.

This whole idea of having solution order govern but having the ability to "bunch solution order" so that you have two different solution orders working together further complicates the model and serves as an example of how this seemingly simple algorithm can yield extremely complicated results and where transitions embodied within them can lead to extender solutions which are positive, increasingly one negative, etc.

Just one example the sum of all columns never goes positive.  If this was driving the concept of how matter vs antimatter is generated, then this would provide a mechanism eliminating antimatter.

It also shows where the total of any row or  column or sum of rows can change as positive or negative and can steadily shifts upward (here by 2 from the next lower similar charge).

It is easy to see other examples, but since this not been accomplished with any mathematical precision, the prior example taking precedence only because it gives a possible mechanism for shifting between fpix and f(x) the following is just to give some perspective and is of limited value.

THEORY:  The most important aspect is that if you pick a range of solutions anywhere within this matrix, you will have a net value as positive or negative and for that area of space, this is the charge state of the space.  Whether matter or antimatter is formed at that point in space is controlled by that net charge for the entire space around a given particle and if it is not properly balanced, the two states cancel each other out and compression loading cannot occur and it remains as space.

CONCLUSION:  In conclusion the argument is that the positive and negative values form some net arrangement locally and overall that defines how much loading occurs based on a net negative value of fpix regionally and how much loading occurs based compression possible within that space is matter or anti-matter based on a net charge value of that same space.

While it remains possible that the amount of matter to antimatter will decrease increase, perhaps shifting the entire universe to an anti-time universe at some point during a decompression cycle; it appears more likely that the underlying universe may compress or decompress as a net anti-matter or net matter universe as net ct1 positive or negative and net compression or decompression remain separate.

          It also appears likely that because of this net feature, that adjacent, dimension independent ct1 states cancel each other out, so that only the net values of ct1 control the charge of the universe at any point in time.  This raises idea of “dual universes.”

          A universe may have varying degrees of net charge yielding a larger or smaller amount of compression of either matter or antimatter universes in a time and dimension free base environment and the universe as either matter or antimatter can have varying degrees of compression or decompression related to the dimensional state of the universe.

***

OTHER EXAMPLES JUST FOR CONCEPT PURPOSES: look at it in this way: plus,minus,plus,plus,plus,plus,minus,plus,plus,minus,minus,minus.
This is how at any point in time the universe can appear with the variations being wildly skewed.  There can be billions of pluses (or minuses) in a row when x is high enough and there can be periods where they alternate, although it seems likely that alternating forms that were adjacent at high levels might be rare.
There is, as always, an attempt to look at this which has already been done for very low values of x.

There are some other comments worth considering
The fpix adjacent (solution order) change 4 points apart, but for lengths that are very long.
Looking at 1.4x10^8 for example the -1.400000002x10^8 corresponding next negative state will change to positive in this:
-3,-3,-3,5,5,5,5,5,--7,-7,-7,-7,-7,-7,-7,9,9,9,9,9,9,9,9,9 by way of example, so the length of time between these shifts gets very convoluted and long over time, negatives and positives at very high numbers would be largely unrelated.
This may be complicated by the regeneration of numbers, the -3 are generated by every change in x so that the 5s come after every 3x and a -7 after every 7 x changes and this creates a very complicated picture.
Looking at just the simple example above it may look like this (1 is added in this example, although the model allows for both -1 and1 which may cancel each other out.
111-31-31-135-135-135-135-135-135-71-35-7...and as is clear at very high numbers these transitions would get very long and might look many different ways. since where the -3 are added changes like this, for example, now with -1 and 1added.