Finding Electron Counts Using “Lagrange” (Ease Point) Calculations

https://www.dropbox.com/s/5l0t4acqtmuyltp/Large%20And%20Small%20Body%20Orbital%20Calculator.txt?dl=0

This is the Python code for calculating L1-L3, along with an explanation on ratio mathematics, and maximum electron shell configurations. I will post a more detailed explanation on this soon, but it will take some time to write out. There are many things we got wrong. If you have any questions, please download Python, and play around with this code to see what it is doing. I’ll get an executable file uploaded at some point too.

Here are two examples of what this does:

Electrons:

Enter IN: 4
Enter N: 3
Enter NP: 1
——
Initial Entry is 2.0.
Baselimiter is 1.75.
Sub Ratio is 0.25.
Subdivide is 0.0625.

Wave Rules:
max_electron_count is 32.0.
shell_full_count is 4.0.
shell_half is 8.0.

Ease Points

Enter IN: 299209236.48 – Sun to earth diameter
Enter N: 768800 – Earth to moon diameter
Enter NP: 149604618.24 – Sun to earth radius/distance from center points
——
Initial Entry is 149604618.24.
Baselimiter is 37785554.56.
Sub Ratio is 111819063.68.
Subdivide is 0.37371528030176404.

Orbit Plots:

L3 is 377855.5456
L2 is 400317.1026862983
L1 is 337916.9286208069

Excerpt from text:

#### Python code for Ease Point (formerly Lagrange) calculations and Large Body Orbits
### Updated 12/17/18 to add electron counts using 1/2 subdivides (same formula)
## I have opted to rename from “Lagrange” for sake of *usefullness*. Naming functions after people is confusing.
# To calculate electron counts, please enter descending/ascending units. For example:

### IN = 4 Shells
### N = 3 Trivial
### NP = 1 Trivial
#max_electron_count is 32.0

### IN = 8 Shells
### N = 7 Trivial
### NP = 1 Trivial
#max_electron_count is 128.0

### You can also use a full count, with the ratio of 1 which acts as a subdivide, IE:
### IN = 4
### N = 4
### NP = 1
#max_electron_count is 32.0

### This scales, so you reach new ratio sets as you change things.
### IN = 4
### N = 2
### NP = 3
#max_electron_count is 32.0

### IN = 5
### N = 3
### NP = 3
#max_electron_count is 50.0

# And so on.

#### If you are wondering why this matters, it proves that all objects in the universe follow syncopation & wave functions
### Please see www.arisopus.com if you have any questions on syncopation or wave relationships.
## This may be a steep learning curve for some who are used to using particle theory.
# This ties quantum mechanics to everything…

#————#Begin Code#————#

IN = float(input(“Enter IN: “))
N = float(input(“Enter N: “))
NP = float(input(“Enter NP: “))

IN = 0.5 if IN == 0 else IN
N = 0.5 if N == 0 else N
NP = 0.5 if NP == 0 else NP

init = IN * 1/2
baselimiter = (N*1/2) + (IN*(1/2) * (NP*1/2) / IN)
sub_ratio = init – baselimiter
easepoint = sub_ratio / 100
sub_divide = sub_ratio / IN
lpoint1 = init / sub_ratio * 1000000
lpoint1balance = lpoint1 – 1000000
max_electron_count = (init / sub_ratio) *IN
shell_half = init / sub_ratio
shell_full_count = sub_divide * max_electron_count * 2

#PLEASE READ TO UNDERSTAND:

########## Max Electron Count Is Equivalent to L2 Ease Point. This is the function of sine wave (polarity) combinations
######### All calculations made for particle physics are not entirely accurate or relative to the natural state of quantum interactions.
######## This is why we see so much entropy. This calculation is more acurate; based on ratios from center point to orbit, to 3rd orbit – etc.
####### This is also why nobody understood the comet oumuamua.
###### This works perfectly for max counts in electron shells.
##### Orbits and Ease Points will always fluctuate depending on the location of other planets or syncopations of other atoms.
#### Those other planets have not been accounted for yet in the calculation. I need to complete a method to add these in.
### Doing so will also allow us to calculate shell counts using only the amount of electrons, and their shell locations.
## It will also allow us to visualize Atom combinations, and biological vitamin structures.
# Reminder that particles are just a visualization of the group function, not quantum mechanics.

#

#### I have removed some of the electrical feedback equations I was using as they were confusing almost everyone.
### They caused people to get really upset. It kept getting removed from forums.
## I did this to show that they were for something else.
# You need to accept the fact that physics is changing. It is a beautiful change for us.

init = 0 if init == 0.5 else init
baselimiter = 0 if baselimiter == 0.5 else baselimiter
sub_ratio = 0 if sub_ratio == 0.5 else sub_ratio
easepoint = 0 if easepoint == 0.5 else easepoint
sub_divide = 0 if sub_divide == 0.5 else sub_divide
lpoint1 = 0 if lpoint1 == 0.5 else lpoint1
lpoint1balance = 0 if lpoint1balance == 0.5 else lpoint1balance
max_electron_count = 0 if max_electron_count == 0.5 else max_electron_count
shell_half = 0 if shell_half == 0.5 else shell_half
shell_full_count = 0 if shell_full_count == 0.5 else shell_full_count

#### Sub_ratio is like saying how many times can you use an even number as 1/4 before you get to the whole number entered
### When an odd is entered IE: 7, you get 1.5 ‘bunches of (4)’ quarters up to 6, then .25 ‘bunches of 4’ quarters to get from 6 to 7.
## If you swap N and NP, you can see this happen in the answer for “sub_ratio”.
# This is because it allows multiples of halves to be used as sub-divides. It’s how our cells, and waves/quantum atomics work.

#### Atoms combine and the group waves grow and excite, and the groups themselves eventually snycopate, creating gravity
### Then more groups combine through the syncopations of the groups made from the atoms turned into elements/molecules
## This keeps happening over and over again until planets and life form
# All objects have a relationship to another based on the syncopations around it, and which formed it

# Shell half is equal to 8, because it is the 4 sub-divided through this rule.

#It all scales#

#These are base numbers you can enter to compare against the old calculations.

#Calculating L1-3

#Enter IN: 299209236.48 – Sun to earth diameter
#Enter N: 768800 – Earth to moon diameter
#Enter NP: 149604618.24 – Sun to earth radius/distance from center points#

## These are the most important, because they tell us the face locations for atoms or the distances from the nucleus
# It will help with atom combinations when we get there

# L4-5 still being worked out. They are amplitudes, similar to L2. They are also reliant on the inner planets more
# I am having troubles finding the actual measurements online for 4 & 5 and the previous formula is so unnecessarily complex

#Calculating best distance of moon (easepoint): Sun to earth, to moon

#Enter IN: 299209236.48
#Enter N: 149604618.24
#Enter NP: 149604618.24

print (“——\nInitial Entry is {0}.\nBaselimiter is {1}.\nSub Ratio is {2}.\nSubdivide is {4}.\n\n\n”
“Orbit Plots:\nOrbital Easepoint is {3}.\n L3 is {1}\n L2 is {7}\n L1 is {6}\n\n”
“Wave Rules:\n max_electron_count is {7}.\n shell_full_count is {9}.\n shell_half is {8}.”
.format(init, baselimiter, sub_ratio, easepoint, sub_divide, lpoint1, lpoint1balance, max_electron_count, shell_half, shell_full_count))

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A New Formula For Calculating Lagrange And Large Body Orbital Points

This is republished from earlier. No changes, just bringing it back to the top of the page:
Python code for Lagrange calculations, and large body orbits

Note this is the same formula as listed in my letter for science. This website format makes it somewhat difficult to read. Please use the text file here for easiest reading.

https://www.dropbox.com/s/30kp7r43f7f9ayq/Lagrange%20Points.txt?dl=0

IN = float(input(“Enter IN: “))
N = float(input(“Enter N: “))
NP = float(input(“Enter NP: “))

IN = 0.5 if IN == 0 else IN
N = 0.5 if N == 0 else N
NP = 0.5 if NP == 0 else NP

init = IN * 1/2
baselimiter = N*1/2 + (IN*1/2*NP*1/2 / IN)
lset = init – baselimiter
easepoint = lset / 100
subdivide = lset / IN
limitconverto1 = (lset / init) * (init / lset)
infalatetoinput = (((init * float(IN))) / init )
forwardlimit = limitconverto1 * infalatetoinput
lpoint1 = init / lset * 1000000
lpoint1balance = lpoint1 – 1000000

result = init, baselimiter, lset, easepoint, subdivide, lset / init, init / lset, limitconverto1, infalatetoinput, forwardlimit, lpoint1, lpoint1balance
result = 0 if result == 0.5 else result
print(result)


End of code*********

baselimiter will calculate for ***L3 , lpointbalance or init / lset will calculate for ***L1
L2 is not yet defined

noteable ratios = .85714
2.014147

EARTH

300000000 – sun to earth diameter, radius 150000000
3000000 – L2 diameter, radius 1500000
768000- earth to moon diameter, radius 384400

Known calculations for earth to moon:
652800 – L1 – 326400 km
897800 – L2 – 448900 km
763400 – L3 – 381700 km

Calculations made by this formula for earth to moon:
L1 – 337916.9286208069 km
L2 –
L3 – 37785554.56 km

384472.282  is current measured distance from Earth to Moon in km
Calculated distance for moon in km by this formula = 37401154.56

Calculating Earth to moon Lagrange points, starting with Sun to earth, earth to moon, and sun to earth radius. Please remember that these numbers vary in the real world as orbits are completed. They are not supposed to be static numbers.
At some point this will lead to being able to calculate the over time numbers. It can be done with perfect accuracy, that will take time to figure out.

Enter IN: 299209236.48 – Sun to earth diameter
Enter N: 768800 – Earth to moon diameter
Enter NP: 149604618.24 – Sun to earth radius/distance from center points
=
(149604618.24, 37785554.56, 111819063.68, 1118190.6368, 0.37371528030176404, 0.7474305606035281, 1.3379169286208068, 1.0, 299209236.48, 299209236.48, 1337916.928620807, 337916.9286208069, 419060.55529411766)
***L3 calculated as 37785554.56 ***L1 calculated as 337916.9286208069

Calculating best distance of moon (easepoint): Sun to earth, to moon

Enter IN: 299209236.48
Enter N: 149604618.24
Enter NP: 149604618.24
(149604618.24, 112203463.68, 37401154.56, 374011.5456, 0.125, 0.25, 4.0, 1.0, 299209236.48, 299209236.48, 4000000.0, 3000000.0, 419060.55529411766)

***384472.282 – current measured distance for moon in km

Calculated distance for moon in km by this formula = 37401154.56

 

Note that this does not include the ratios for planets between the sun and earth. I am still working out how to do that. This is plenty to show that I am on the right path.

Enter IN: 185920000
Enter N: 92900000
Enter NP: 92900000
(92960000.0, 69675000.0, 23285000.0, 232850.0, 0.1252420395869191, 0.2504840791738382, 3.9922697015245867, 1.0, 185920000.0, 185920000.0)

***238900 – current measured distance for moon in miles

Calculated distance for moon in miles by this formula = 232850.0,

JUPITER

Reminder: Please download the text file. It is MUCH easier to read.

Calculating best distance for Jupiters moons Sun to Jupiter, to moon

1557201254.4 diameter around sun (perfect circle)
778600627.2 (radius from sun)

***CALLISTO
Enter IN: 1557201254.4
Enter N: 778600627.2
Enter NP: 778600627.2
(778600627.2, 583950470.4000001, 194650156.79999995, 1946501.5679999995, 0.12499999999999996, 0.24999999999999992, 4.000000000000001, 0.9999999999999999, 1557201254.4, 1557201254.3999999, 4000000.000000001, 3000000.000000001, 2180954.137815126)
3759426 ***1879713 – current measured distance for farthest moon (Callisto) in km

***GANYMEDE
Enter IN: 1557201254.4
Enter N: 1879713
Enter NP: 3759426 (Diameter for Callisto to Jupiter)
(778600627.2, 1879713.0, 776720914.2, 7767209.142000001, 0.4987928901324163, 0.9975857802648326, 1.002420062297326, 1.0, 1557201254.4, 1557201254.4, 1002420.062297326, 2420.062297326047, 2180954.137815126)

***1,070,000 is current measured distance from Jupiter (Ganymede) in km 2*420 = 840, 1879713 – 840000 is 1039713 ***
***This formula calculated 1,102,993. (1879713-776720=***1102993) and (1946501-776720=***1169781) 1,070,000 is current measured distance from Jupiter (Callisto) in km

***EUROPA
Enter IN: 1557201254.4
Enter N: 1102993 (Radius from Ganymede to Jupiter)
Enter NP: 2205986 (Diameter for Ganymede to Jupiter)
(778600627.2, 1102993.0, 777497634.2, 7774976.342, 0.4992916824354698, 0.9985833648709396, 1.001418644831164, 1.0, 1557201254.4, 1557201254.4, 1001418.6448311639, 1418.6448311639251, 2180954.137815126)
1*418 = 418, 1070000 – 418000 – is 652000***
1*418 = 418, 1102993 – 418000 – is 684993***
1*418 = 418, 1169781 – 418000 – is 751781***
671,000 is current measured distance from Jupiter (Europa) in km

Enter IN: 778600627.2 (using radius because there are more moons in orbit now)
Enter N: 1102993 (Radius from Ganymede Jupiter)
Enter NP: 2205986 (Diameter for Ganymede to Jupiter
(389300313.6, 1102993.0, 388197320.6, 3881973.2060000002, 0.49858336487093957, 0.9971667297418791, 1.0028413204869504, 1.0, 778600627.2, 778600627.2, 1002841.3204869505, 2841.3204869504552, 1090477.068907563)
***388,197
***671,000 is current measured distance from Jupiter (Europa) in km
***This formula calculated 681,803. (1070000-388197=***681803) and (1169781-388197=***781584)

***IO
Enter IN: 1557201254.4
Enter N: 681803 (Radius from Europa to Jupiter)
Enter NP: 1363606 (Diameter for Europa to Jupiter)
(778600627.2, 681803.0, 777918824.2, 7779188.242000001, 0.4995621612825744, 0.9991243225651488, 1.0008764449178886, 1.0, 1557201254.4, 1557201254.4, 1000876.4449178886, 876.4449178886134, 2180954.137815126)
***876,000-671,000 = 205,000
***671,000-205,000 = 466,000
422,000 is current measured distance from from Jupiter (IO) in km

Enter IN: 389300313.5 (divided radius by 2 to account for additional body)
Enter N: 681803 (Radius from Europa to Jupiter)
Enter NP: 1363606 (Diameter for Europa to Jupiter)
(194650156.75, 681803.0, 193968353.75, 1939683.5375, 0.4982486451298478, 0.9964972902596956, 1.003515021841546, 0.9999999999999999, 389300313.5, 389300313.49999994, 1003515.021841546, 3515.021841546055, 545238.5343137255)
***193,968
***422,000 is current measured distance from Jupiter (IO) in km
***This formula calculated 477,032. (671000-193968=***477,032) and (781584-193968=***587,616)

Notes:
Enter IN: 483800000
Enter N: 241900000
Enter NP: 241900000
(241900000.0, 181425000.0, 60475000.0, 604750.0, 0.125, 0.25, 4.0, 1.0, 483800000.0, 483800000.0)
***1208500 – unsure why this needs to be doubled for miles, but not km – guessing it has to do with the ratio function
***1168000 current measured distance for farthest moon (Callisto) in miles

19465015.679999996
1879713
1946501

375000
384472.282

Note that this does not include the ratios for planets between the sun and jupiter. I am still working out how to do that to increase accuracy. This is plenty to show that I am on the right path.

Essentially, this is a form of Fourier transform for planetary/large body orbits.

 

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Some Added Understandings Regarding Lagrange/Orbital Calculations

Some questions I have been asked answered:

 

Rewrite for Lagrange point calculations (without weights or velocities), along with large body orbital distances. (Python code included) from r/math

A New Formula For Calculating Lagrange And Large Body Orbital Points

Note: This doesn’t change what zero is. This is where the issue is, and why nobody understands what I mean. This is completely new to everyone besides me. I am literally the only person who gets it at this point, because I am the only person who has ever done it. This calculation (again, look at the numbers, they prove it) shows that the real zero is far below anything we can actually measure. The only base zero in this universe is the point in which nothing exists. This only defines the scale of the system, where you don’t actually use zero at all. There is no reason we should ever be using that real zero when we are making quantifiable measurements.

To fully grasp how this works, I would suggest watching the videos I’ve made showing sine-sine, and other wave-shape relationships. This is a ratio system, which does not use zero at all. It is entirely new to mathematics in this format; but something which is already understood through Fourier transforms, and it does not make any numbers meaningless. It is built to mimic real atomic and spacial functions taking place in our universe through the use of sub-dividers – as both the ratio of the input, and a chosen ratio; in this case, 1/2, which is the ratio defining the switch from negative to positive poles, or plot points.

There are so many questions coming up in science right now, because nobody is willing to just do away with old ideas. Everyone is too attached to old systems. It’s ok to change the system when that system is math, because there are no definitive laws besides what the numbers are capable of, and when the system you create is more efficient, and it works – it should be paid attention to instead of erroneously insulted with no real grounded understanding of what it is doing. It is also necessary to become concerned with the system when that system is science and something like this comes along. Ultimately, this just provides a better explanation of what is actually going on atomically, and with spacial structures. We took it too far when we started teaching theories as fact.

It is on the path to using (sine) wave ratios to plot points in systems. What I discovered was that when we start stretching numbers over to 1 to make up for the singularity (infinite zero) point in a true zero system we begin to show overcomplications, and large groups of entropy (why the Birch and Swinnerton conjecture is so hard to figure out).

By turning 0 into 1/2, it allows for linear movement through all xyz plots, as there is no longer an infinite zero to work with. It’s just like how we recently changed the way we measure the kilogram. It’s defined atomically now instead of based on what all of the atoms weigh as a group.

This is actually closer to solving the Birch and Swinnerton conjecture now, because it is calculating orbits using only the ratios of the system, point A and B are entered, and it determines the radius, or diameter (ellipses), and it works because you can combine sine waves in such a way as seen in these videos I made: https://www.youtube.com/watch?v=5S3rRI6eaB0&list=PLcfuEHD26MBS3llzRK9VFTWqVTpG1w5-4&index=3 Make sure you watch both generating ellispes videos to see what I mean.

This is also very close to completing Navier stokes, as it won’t need velocities to enact the compressing function that is required to show viscosities/stress or pressure, but instead just needs to know how the (sine) waves are acting.

Really, Riemann answers itself once you know that zero is equal to 1/2. This is a surprise when you think about it, we spent so many years not trying it that way, it just sits between -1, and 1 on the graph. So 1/2, but it can become more complex than that when you really start to think about it.

Think of it like this

Fahrenheit has a 0, which is measure-able only in Fahrenheit. 0°F is equal to -17.78° Celsius. 0° Celsius is equal to 273.15 Kelvin.

That means that we turn the zero point for each measurement scale into an actual number or ratio by there existing another scale outside of it. All objects in this universe are on a scale outside of the exact point in which our universe went from nothing to the big bang. No zero is a zero, but can be defined using ratios.

This means that by creating a scale using the ratio input, you can now measure things like 0 mph over 0 distance, or 0 miles over 0 seconds. It closes the system, by putting it into a fully defined state and allows for measurement of all things.

I tried to explain this to mathematicians before, but it didn’t have as much definition as it does now, so it just got ignored.

My aim is to turn this into something you can enter plot points for to begin to plot out solar systems. It should prove you can also calculate body masses using the ratios of the system. Neither is much more important over the other, as doing so should eventually prove all 3, and consequentially potentially knock the other questions off the board in the process.

Oh, and the statement in there, I realized that the ratio was compressing itself, you can see that when the numbers drop to 0.125, 0.25, 4.0, 1.0. That’s the over-all ratio of what is used to bring things down and back up. It does that using the inputs, and the ratio of 1/2, so I just need to work out a way to plot it, and refine it a bit. I came close, but lost interest for a while.

Here’s the code for the limiter without the Lagrange stuff. It’s fun to put numbers into it, and watch the output always come out to the input.

https://www.dropbox.com/home/NP%20Information?preview=Forwardlimiter.txt

Some people seem to think that tuning the numbers down to 1 like that is “cheating”, but in the sense of completing the Navier-Stokes question it’s probably going to be necessary to use such a function. It’s done in a way that I perceive to be how atomics work, as you essentially should have a dual input system (open circuit) which acts like a closed circuit until something is introduced. This is meant to act out a limit on a larger formula for a feedback system, something I haven’t written yet. These are all modular components. I’m not even using that limitconverto1 portion in this Lagrange formula for those who are questioning all of this, and it really is probably needed to act out the Navier-Stokes question anyways, it doesn’t need to stay at a ratio of 1/1 though. Mostly it is something I want to use one day for electrical feedback systems.

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A New Formula For Calculating Lagrange And Large Body Orbital Points

Python code for Lagrange calculations, and large body orbits

Note this is the same formula as listed in my letter for science. This website format makes it somewhat difficult to read. Please use the text file here for easiest reading.

https://www.dropbox.com/s/30kp7r43f7f9ayq/Lagrange%20Points.txt?dl=0

IN = float(input(“Enter IN: “))
N = float(input(“Enter N: “))
NP = float(input(“Enter NP: “))

IN = 0.5 if IN == 0 else IN
N = 0.5 if N == 0 else N
NP = 0.5 if NP == 0 else NP

init = IN * 1/2
baselimiter = N*1/2 + (IN*1/2*NP*1/2 / IN)
lset = init – baselimiter
easepoint = lset / 100
subdivide = lset / IN
limitconverto1 = (lset / init) * (init / lset)
infalatetoinput = (((init * float(IN))) / init )
forwardlimit = limitconverto1 * infalatetoinput
lpoint1 = init / lset * 1000000
lpoint1balance = lpoint1 – 1000000

result = init, baselimiter, lset, easepoint, subdivide, lset / init, init / lset, limitconverto1, infalatetoinput, forwardlimit, lpoint1, lpoint1balance
result = 0 if result == 0.5 else result
print(result)


End of code*********

baselimiter will calculate for ***L3 , lpointbalance or init / lset will calculate for ***L1
L2 is not yet defined

noteable ratios = .85714
2.014147

EARTH

300000000 – sun to earth diameter, radius 150000000
3000000 – L2 diameter, radius 1500000
768000- earth to moon diameter, radius 384400

Known calculations for earth to moon:
652800 – L1 – 326400 km
897800 – L2 – 448900 km
763400 – L3 – 381700 km

Calculations made by this formula for earth to moon:
L1 – 337916.9286208069 km
L2 –
L3 – 37785554.56 km

384472.282  is current measured distance from Earth to Moon in km
Calculated distance for moon in km by this formula = 37401154.56

Calculating Earth to moon Lagrange points, starting with Sun to earth, earth to moon, and sun to earth radius. Please remember that these numbers vary in the real world as orbits are completed. They are not supposed to be static numbers.
At some point this will lead to being able to calculate the over time numbers. It can be done with perfect accuracy, that will take time to figure out.

Enter IN: 299209236.48 – Sun to earth diameter
Enter N: 768800 – Earth to moon diameter
Enter NP: 149604618.24 – Sun to earth radius/distance from center points
=
(149604618.24, 37785554.56, 111819063.68, 1118190.6368, 0.37371528030176404, 0.7474305606035281, 1.3379169286208068, 1.0, 299209236.48, 299209236.48, 1337916.928620807, 337916.9286208069, 419060.55529411766)
***L3 calculated as 37785554.56 ***L1 calculated as 337916.9286208069

Calculating best distance of moon (easepoint): Sun to earth, to moon

Enter IN: 299209236.48
Enter N: 149604618.24
Enter NP: 149604618.24
(149604618.24, 112203463.68, 37401154.56, 374011.5456, 0.125, 0.25, 4.0, 1.0, 299209236.48, 299209236.48, 4000000.0, 3000000.0, 419060.55529411766)

***384472.282 – current measured distance for moon in km

Calculated distance for moon in km by this formula = 37401154.56

 

Note that this does not include the ratios for planets between the sun and earth. I am still working out how to do that. This is plenty to show that I am on the right path.

Enter IN: 185920000
Enter N: 92900000
Enter NP: 92900000
(92960000.0, 69675000.0, 23285000.0, 232850.0, 0.1252420395869191, 0.2504840791738382, 3.9922697015245867, 1.0, 185920000.0, 185920000.0)

***238900 – current measured distance for moon in miles

Calculated distance for moon in miles by this formula = 232850.0,

JUPITER

Reminder: Please download the text file. It is MUCH easier to read.

Calculating best distance for Jupiters moons Sun to Jupiter, to moon

1557201254.4 diameter around sun (perfect circle)
778600627.2 (radius from sun)

***CALLISTO
Enter IN: 1557201254.4
Enter N: 778600627.2
Enter NP: 778600627.2
(778600627.2, 583950470.4000001, 194650156.79999995, 1946501.5679999995, 0.12499999999999996, 0.24999999999999992, 4.000000000000001, 0.9999999999999999, 1557201254.4, 1557201254.3999999, 4000000.000000001, 3000000.000000001, 2180954.137815126)
3759426 ***1879713 – current measured distance for farthest moon (Callisto) in km

***GANYMEDE
Enter IN: 1557201254.4
Enter N: 1879713
Enter NP: 3759426 (Diameter for Callisto to Jupiter)
(778600627.2, 1879713.0, 776720914.2, 7767209.142000001, 0.4987928901324163, 0.9975857802648326, 1.002420062297326, 1.0, 1557201254.4, 1557201254.4, 1002420.062297326, 2420.062297326047, 2180954.137815126)

***1,070,000 is current measured distance from Jupiter (Ganymede) in km 2*420 = 840, 1879713 – 840000 is 1039713 ***
***This formula calculated 1,102,993. (1879713-776720=***1102993) and (1946501-776720=***1169781) 1,070,000 is current measured distance from Jupiter (Callisto) in km

***EUROPA
Enter IN: 1557201254.4
Enter N: 1102993 (Radius from Ganymede to Jupiter)
Enter NP: 2205986 (Diameter for Ganymede to Jupiter)
(778600627.2, 1102993.0, 777497634.2, 7774976.342, 0.4992916824354698, 0.9985833648709396, 1.001418644831164, 1.0, 1557201254.4, 1557201254.4, 1001418.6448311639, 1418.6448311639251, 2180954.137815126)
1*418 = 418, 1070000 – 418000 – is 652000***
1*418 = 418, 1102993 – 418000 – is 684993***
1*418 = 418, 1169781 – 418000 – is 751781***
671,000 is current measured distance from Jupiter (Europa) in km

Enter IN: 778600627.2 (using radius because there are more moons in orbit now)
Enter N: 1102993 (Radius from Ganymede Jupiter)
Enter NP: 2205986 (Diameter for Ganymede to Jupiter
(389300313.6, 1102993.0, 388197320.6, 3881973.2060000002, 0.49858336487093957, 0.9971667297418791, 1.0028413204869504, 1.0, 778600627.2, 778600627.2, 1002841.3204869505, 2841.3204869504552, 1090477.068907563)
***388,197
***671,000 is current measured distance from Jupiter (Europa) in km
***This formula calculated 681,803. (1070000-388197=***681803) and (1169781-388197=***781584)

***IO
Enter IN: 1557201254.4
Enter N: 681803 (Radius from Europa to Jupiter)
Enter NP: 1363606 (Diameter for Europa to Jupiter)
(778600627.2, 681803.0, 777918824.2, 7779188.242000001, 0.4995621612825744, 0.9991243225651488, 1.0008764449178886, 1.0, 1557201254.4, 1557201254.4, 1000876.4449178886, 876.4449178886134, 2180954.137815126)
***876,000-671,000 = 205,000
***671,000-205,000 = 466,000
422,000 is current measured distance from from Jupiter (IO) in km

Enter IN: 389300313.5 (divided radius by 2 to account for additional body)
Enter N: 681803 (Radius from Europa to Jupiter)
Enter NP: 1363606 (Diameter for Europa to Jupiter)
(194650156.75, 681803.0, 193968353.75, 1939683.5375, 0.4982486451298478, 0.9964972902596956, 1.003515021841546, 0.9999999999999999, 389300313.5, 389300313.49999994, 1003515.021841546, 3515.021841546055, 545238.5343137255)
***193,968
***422,000 is current measured distance from Jupiter (IO) in km
***This formula calculated 477,032. (671000-193968=***477,032) and (781584-193968=***587,616)

Notes:
Enter IN: 483800000
Enter N: 241900000
Enter NP: 241900000
(241900000.0, 181425000.0, 60475000.0, 604750.0, 0.125, 0.25, 4.0, 1.0, 483800000.0, 483800000.0)
***1208500 – unsure why this needs to be doubled for miles, but not km – guessing it has to do with the ratio function
***1168000 current measured distance for farthest moon (Callisto) in miles

19465015.679999996
1879713
1946501

375000
384472.282

Note that this does not include the ratios for planets between the sun and jupiter. I am still working out how to do that to increase accuracy. This is plenty to show that I am on the right path.

Essentially, this is a form of Fourier transform for planetary/large body orbits.

 

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A Better Explanation Regarding Riemann/Navier Q

10/24/18 Sorry for the long read. I’ll explain it a little better here:

Think of it all like how light is a combination of sine waves.

That equation is part of a formula. It’s a modular system. Open up the proof tables and check the proof for Riemann to see what I mean. It’s all right there. Basically, I need to also finish the proof to the Navier-Stokes to make this more plausible to people who don’t get it, but I don’t really have the time at the moment or feel like working it out. I will at some point.

https://docs.google.com/spreadsheets/d/1J5C2A0XGWX85PTFrR3ulihqyX4u3Smu4ueDDRXma3A4/edit#gid=0

Everything is a matter of wave interactions. We equate all measurements as if we know what 0 is, but there is no actual 0 for measurement of atomic structures, unless nothing were to exist at all. The fact that we even know what 1 is, is a measurement in itself of atomic structures.

That is why an input (in) is required to define 0. Something created what we perceive; regardless of whether we perceive it as not there or there, and that something is a combination of waves (at the micro scale). The true zero for any tangible system in our universe would be placed on the farthest left point of the graph, with no negative numbers being used at all. Zero can be redefined as a ratio (1/2) because of this. That is done to allow us to use negative numbers without stretching and resampling things. It replaces square functions with divisors, and instead allows you to create larger wholes by subdividing; or making room to allow you to fit more into the system just like atomic processes.

It’s very similar to equating the 0 velocity point for something like a rock before it is pushed down a hill. That 0 means something. It’s just not a true 0.

Think of it like this:

Fahrenheit has a 0, which is measure-able only in Fahrenheit. 0°F is equal to -17.78° Celsius. 0° Celsius is equal to 273.15 Kelvin.

That means that we turn the zero point for each measurement scale into an actual number or ratio by there existing another scale outside of it. All objects in this universe are on a scale outside of the exact point in which our universe went from nothing to the big bang. No zero is a zero, but can be defined using ratios.

This means that by creating a scale using the ratio input, you can now measure things like 0 mph over 0 distance, or 0 miles over 0 seconds. It closes the system, by putting it into a fully defined state and allows for measurement of all things.

As soon as we begin to apply this to all formulas (rewrite them), you will find that accuracies will be where we need them to be. This is because, at this stage in our understanding; both universally and atomically, there is no such thing as an at rest state; in its truest form – as a matter of definition, without a definition of what that state is.

Riemann theorized this, but he didn’t seem to understand it fully, or at least he didn’t think to just do away with his perception of what zero was. It’s not his fault that was a long time ago. He thought (and everyone else still does) that we needed to keep zero in the middle. We still sort of do in order to measure things in a way that makes sense for now, but we need to do so with the understanding that all measurements unless the true source (wave) are not ever going to equate to zero, but that there is the possibility that zero itself can be defined for that group function. Ultimately, we might wind up doing away with zero entirely for all but the most extreme scenarios.

Look if you don’t understand it now it might take you a while to get it. It took me a few months to even begin to draw these conclusions, and you have to understand that we got a lot wrong in order to even do so.

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Burden of Proof

 

0*1267 – (+0*922 + 0*1267(0*345)

= 633.5 – (461 + (((633.5(172.5))/in))) = 258.75

= 258.75 / 1267 *(in / 258.75)

= 1 * (( 0 *in ) * in )) / ( 0 *in ))

= 1267

0*0; – (0*0 + 0*0(0*0)

= .25 – (.25 + (.25(.25);…/.50) = .125

= .125 / 0 *(in / .125)

= 1 * (( 0 *in ) * in )) / ( 0 *in ))

= 0

0*1; – (0*1 + 0*1(0*0)

= .5 – (.5 + (.5(.25);…/1) = .375

= .375 / 1 *(in / .375)

= 1 * (( 0 *in ) * in )) / ( 0 *in ))

= 1

0*2; – (0*1 + 0*2(0*1)

= 1 – (.5 + (1(.5);…/2) = .75

= .75 / 2 *(2 / .75)

= 1 * (( 0 *in ) * in )) / ( 0 *in ))

= 2

0*3; – (0*1 + 0*3(0*2)

= 1.5 – (.5 + (1.5(1);…/3) = -.5

= .5 / 3 *(3 / .5)

= 1 * (( 0 *in ) * in )) / ( 0 *in ))

= 3

0*4; – (0*1 + 0*4(0*3)

= 2 – (.5 + (2(1.5);…/4) = -1.5

= -1.5 / 4 * (4 / -1.5)

= 1 * (( 0 *in ) * in )) / ( 0 *in ))

= 4

0*2761; – (0*1245 + 0*2761(0*1516)

= 1380.5 – (622.5 + (1380.5(758);…/2761) = 378.862731
= 378.862731 / 2761 * (2761 / 378.862731)

= 1 * (( 0 *2761 ) * 2761 )) / ( 0 *2761 ))

= 2761

0*3376547; – (0*1278314 + 0*3376547(0*2098233)

= 1688273.5 – (639157 + (1688273.5(1049116.5);…/3376547) = 524558.25
= 524558.25 / 3376547 * (3376547 / 524558.25)

= 1 * (( 0 *3376547 ) * 3376547 )) / ( 0 *3376547 ))

= 3376547

0*934; – (0*105 + 0*934(0*829)

= 467 – (52.5 + (467(414.5);…/934) = 621.75

= 621.75 / 934 * (934 / 621.75)

= 1 * (( 0 *in ) * in )) / ( 0 *in ))

= 934

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Letter For Science

NP Test and Proof Tables: Spreadsheet
Letter for Science: Document

4th October, 2018 — Dear Reader,

Please refer to attached tables, formulas and proofs as needed throughout this letter. This is an open formula, and one which you may feel free to add to at any point should you feel you are capable of doing so. Please note that although my views are stern, there is in-fact proof. I must ask you to continue reading. If you feel inclined to overlook this paper, please briefly scroll through to see all highlighted points so you may develop an understanding of what you have chosen to ignore.

This is an answer to the Riemann hypothesis (0 = 1/2), and some others. This math is going to be new to you, and will seem unconventional.

Here is an example. I have explained in detail what is going on here below.
0*3376547; – (0*1278314 + 0*3376547(0*2098233)

= 1688273.5 – (639157 + (1688273.5(1049116.5);…/3376547) = 524558.25
= 524558.25 / 3376547 * (3376547 / 524558.25)

= 1 * (( 0 *3376547 ) * 3376547 )) / ( 0 *3376547 ))

= 3376547

( in(0) – (n(0) + [ in(0) *np(0) /in ] /in ) * ( in / [ in(0) – (n(0) + [ in(0) *np(0) /in ]) * [ (( 0 * in ) * in)) / ( 0 * in )) ] – This proof has been tested into the millions and completed.

Dirac delta function: “In mathematics, the Dirac delta function (δ function) is a generalized function or distribution introduced by the physicist Paul Dirac. It is used to model the density of an idealized point mass or point charge as a function equal to zero everywhere except for zero and whose integral over the entire real line is equal to one. As there is no function that has these properties, the computations made by the theoretical physicists appeared to mathematicians as nonsense until the introduction of distributions by Laurent Schwartz to formalize and validate the computations.” https://en.wikipedia.org/wiki/Dirac_delta_function

This formula also directly conflicts with the statement that: “Third Law Of Thermodynamics: “It is impossible for any process, no matter how idealized, to reduce the entropy of a system to its absolute zero value in a finite number of operations”. I literally did that.

More tangible proof of what I am trying to show. https://www.sciencedaily.com/releases/2018/10/181004110027.htm

The reason this works is because of phase differences, and that is why it doesn’t work so well with these types of objects and light. I have included videos below showing exactly this; done with sine waves.

The videos above are related to the Birch and Swinnerton Q. Here is some more proof of zero definition (Riemann Hypothesis):

Calculated for 12:

Reminder: Please see proof tables

This letter has been written to establish a new, and better response to our universe and the objects interacting within.

The formulas set within are modular, and meant to open your thought to what will become possible using these foundations. The formulas which are being added, are being built off of input functions, and ratios. They are meant for simplicity; and are valued in that it will not require extensive knowledge of multiple different theories to begin to work within of your own accord.

These ideas are being set forth because they are ideas which must be completed by multiple people, as no one person is the key to our universal cognizance. There is to be no discrimination between capabilities. If it works, it works. But find out why.

We will require at some point an open, ongoing discussion in which to more freely share ideas through the use of our internet; which does not rely on the bottleneck of news outlets, or caveat of degrees; which are all built upon information we ourselves have invented. We will require one which does not build upon view statistics, and is open to any individual to add to. This is needed because our mathematical system is broken. It is far too divided and undefined. We have begun to create whole imaginary systems to attempt to define numbers which are perceived as irrational; when in reality, they exist; therefore they are rational. – And we are teaching these ideas as definite answers in our school systems.

One of the larger issues in current math is our use of symbols which have no real definition, or group functions which don’t fully understand the inputs. We are also using roots and squares for systems which are largely circular, and relying on the ratio of one set of numbers (22/7) to define all. For the time being, our perception needs to change to that of; Our world is not built upon 1 single ratio. The universe may be, but our existence is a combination of many, which are a function of the whole.

In order to describe how this all works, I will need to further define the paragraph above. I will do this by walking you through the answer, or proof to the Riemann hypothesis, or as I would prefer to call it; the proof that zeros must in all cases be a defined value. I must do this by also describing to you the answer of the Birch and Swinnerton conjecture, or as I would prefer to call it; Does NP allow for time-independent location discovery? (The ellipses conjecture)

The answer to that second one is yes. You might need to go over the tables now, and even some of the stuff I have been writing about over the past couple of months to fully comprehend why, but I will explain it in reference to the formula. Please keep in mind that some of my past writings include old information or theories which led to this page and were incomplete at the time. I still need to go over those and apply all of this new information to it. This may one day become obsolete.

(( n + in (np) – in ) / np )) ; Where 0 = 0

What does that mean? This is a function which should work, but it does not. Because it does not have an input. If it had an input, it would be adding points together, and then removing the ratio of one or sets of points to determine the maximum distance from the initial point, or the diameter of a circle. You could picture it as reading phase points, or spiraling outwards to read points like one of today’s computers might do so as to become familiar with the idea, but that isn’t exactly it. It is using ratios to determine ratios.

This equation is generating ellipses at the moment (in its presented form), as it always gives an answer which is less than that of the maximum values surrounding it.

It is actually possible to allow a broader function to deflate itself using this set with an input; and/or when in combination with zero definitions by repeating the function until the ratio reaches itself, and then inflate itself through combinations with 0. (generate spheres) – it is more complicated than written though, and matches more of the final equation shown in this letter than the one above. Unfortunately, I chose not to keep that equation when I discovered it, because I didn’t realize its importance until I actually wrote this out. It shouldn’t be too hard for you to find yourself though. It probably needed to be rewritten anyways.

This happens to be one set which will be used throughout the rest of this letter, and some version of it is used so far in almost all of the formulas I have found. This was my start point. Please keep in mind that all of this information appears to be things we know already. I can assure you it is not.

What happens when you add an input?

In – (( n + in (np) – in ) / np )) ; Where 0 = 0

You would expect the answer to come out to the input minus the ratio, but that is not really the case. It is a definition for a path, or ((the start point – (the amount of points remaining, minus the input combined with the amount of points traveled, minus the input of that, divided by the traveled points));

or the input being added, and then immediately being removed with a calculation of new inputs and divisions which are based on the first.

It is a piece to a functional form of feedback capable of generating new points which are based only on ratios in relation to themselves.

This is the biggest hurdle in understanding why this all works, and I still struggle defining it sometimes. What I eventually found was that it was incomplete, and that zero and 1 weren’t working. I also found that you needed to continue feeding back to start to calculate many points; good news I am finding ways to remedy that too. I needed to redefine what zero meant, and I also needed to find a way to create a ceiling. I will go into more detail on this later on in this letter, as it is a function which solves the Birch and Swinnerton conjecture, or as I would prefer to call it; Does NP allow for time-independent location discovery? Now that this has been described, I can describe what I mean by zero having a definition.

Basically Riemann said 0 isn’t 0. It should equal ½, and he was pretty much exactly right. Technically it really doesn’t matter what zero equals as long as it equals something (more on that later too), but in our current context ½ is about the right number to use.

Why did I need to do this? Because first of all, you can’t have an input that is nothing (Not yet, we don’t know enough to do that) – (Also, NP = N; also solvable), if you do have an input from nothing then you have to start making up numbers to create that input. This is why 0 on an XY is equal to infinity. Honestly, I find it to be a huge mistake on our part that we even still see it that way. I think it is only because I never followed math enough until now to care, and I never had it instilled into my head that it absolutely had to be that way.

In other words; you can make things up to solve things, but you have to remember that you made things up and remove them from the formula.

Small offshoot, this has everything to do with our universe right now. We need to get more on track with what we don’t need to make up, but it is required sometimes to go outside of the box.

So is making 0 equal to ½ making something up? Absolutely not. Right now if you look at an XY graph, you see -1, 0, 1. Zero is exactly halfway between -1, and 1. The real zero doesn’t exist so it shouldn’t be on the graph. Zero doesn’t even need to be the center.

For some reason we are stretching everything over to 1 to solve our problems, when all we needed to do was fold the number sequence, or forget that zero exists (remove it from the equation). This also meant rewriting everything, which kinda sucks; but we should have done it much sooner. I’ve added some images to this statement as an attachment to you, or they can be found on my website. The images are using the formula above to show you why it works (with circles), and how beautifully it matches magnetic fields.

My first step towards solving this issue with locating points was to turn 0 into a -0, and a +0, which is basically what we do now when we think we are sliding the graph over to one.

The equation I used was:

(( n + in (np) – in ) / np ) * np) / np)) ; Where 0 = 1/2. 0 is halfway between 1 and -1. There should be a -0 and positive 0.

Reminder: Please see proof tables

This is a determination function, so I could use it to work out limited points to obtain diameters for (0,0), (0,1), (1,1), (2,1), and so on. I stopped very early on because it was clear that it wasn’t the best way to do it. Things were symmetrical, but not creating natural shapes. This is visible in the picture where there is a clear gap between -0, and 0 (actual zero still exists). I did make a mistake in not using an input here for more accurate results, but it technically didn’t matter because I was equating for input = input. Something to note when you do these things yourself, is to always use an input. Luckily this was just a diameter function. I might have never learned of this otherwise.

So what now? I needed the graph to work better, and I needed to also ensure that I could make the limiters output equal its input, without the complications of all the made up stuff we are using right now. I had to find a way to make 0 = 0. You can’t do that right? No you can’t at this exact moment in time, not if 0 actually equals nothing.

So I made 0 equal ½ (.5). This seemed like it was the most reasonable number to use. It was right in-between 1 and -1. Later on I discovered that this means negative numbers aren’t really negative, and that it solved another millenial problem. This will play a very large role in understanding our universe better.

This doesn’t just solve millenial problems by the way.

Once I made 0 equal to ½, I found that I could graph what I expected to be correct out, and it worked fantastically, and symmetrically. There was now little issue defining everything down to 1, but I still struggled with 0 – which was .5. It took a little while longer to figure out. One very nice discovery that came out of this was I could now use 0 to increase numbers by a factor of two, or decrease them by a factor of ½, and I had already found that there were ways to turn evens into odds. These two combinations helped very much.

The equations had now become forms of feedback which could rectify itself. They aren’t just for FFT anymore, which I am getting closer to rewriting, but a part of a much more intricate function.

I had done all of that, but I didn’t even understand it until a few days later. I started looking up more conjectures and found the timing of some new discoveries was perfect for this. Especially the Collatz Conjecture (if n even n -> n/2 & if n odd n -> 3n +1). The only issue I had was that conjecture is using too much undefined information.

What is my obsession with 0’s and 1’s? It is what everything is made up of. Our current formats are using whole group functions that we don’t even have the quantum definitions for yet. I really don’t like that. It needs to be simpler until we understand what exactly it is that we are doing. This is also going to allow us to actually use quantum computers one day. I’m not saying we were wrong in taking this path to the present, but it is time to start removing some of the things we made up to define the groups. We partially understand them now and need to take it further.

I had also started to notice ideas which were turned away from because it didn’t fit what we thought was right, and ideas which were ridiculous because we thought we were right. Even this could one day be broken for something new which we couldn’t discover yet, but could only have discovered with it. It is a very uneasy feeling seeing something work, and thinking; “no that can’t be right.”

 

First Iteration
[in – [(( n + in (np) – in ) / np ); * np)) / np)) *np )) /0 )) *in )) *0)) = ans;] / ((ans)] * (in))] – Where 0 = 1/2. Input equals output – Whole Limiter. No Imaginary Information. Another easier way to understand why it works

 

Proof #1:
( in(0) – (n(0) + [ in(0) *np(0) /in ] /in ) * ( in / [ in(0) – (n(0) + [ in(0) *np(0) /in ]) * [ (( 0 * in ) * in)) / ( 0 * in )) ] – This proof has been tested into the millions and completed.

Can be easier understood as:

input = in; 0*in; – ((0*n + 0*in(0*np))

= in – (n + in(np))

-> new function added; /in

= where does the new function go?: in – (((n + ((in(np);/in)))

= output ; {Hold value} waiting for:

= output of ; /(in) ;

Or in other words:

= output ; {Hold value} … wait for … 0*in – ((0*n + 0*in(0*np))) … wait for … value of new function /in “(in – (((n + ((in(np)/in)))” AKA: (feedback)

= output ; *(in / feedback value) or the output multiplied by (the input divided by the feedback value)

= output now equals 1 – Because it has followed a path that allowed a division by the outcome multiplied by the original input value/feedback value.

= output ; *((0 *in) *in)) / (0 *in))

= Now you have found the original input value – found through separate, non-destructive paths

Proof #2:
Same as the first iteration

What is this doing?: Picture a reservoir system or electrical current circuit. It has two paths, with one input. There is a gate at the end of both paths, and each path is fed different portions of the input.

Once the path which has received a higher portion is filled, all of its excess is then fed into the second path until both are filled, and nothing is allowed past the gate until it has reached the fill point for both.

Then picture the paths being subdivided by the initial input values in such a way that it allows for two paths to fill at the same rate. Each time you multiply by 0, you have a subdivision, because 0 equals 1/2.

This is where things become much more interesting.

First off, simplified doesn’t mean it is more effective. It only does if it has the same path. You can compute the same results with different paths (also one day important for quantum computing).

Sidenote: you can use this for pole reversals

This is all understandable without complex math. It needs to stay that way. The only way it should ever become complex is through combinations of functions; but still overall readable without memorization of a hundred different ideas.

What is this all doing? Well it’s making 0 = 0 on the graph, where 0 = .5. This is the first iteration of a definition of zero. It creates a floor (0), and has a limiting function of a whole number for the input, where it does not get higher than the input.

What do I need to do next? I need to generate a ceiling, or a maximum number allowed to be sent into this function. I do this by creating a ratio. The ratio can be X/Y, where the input is the ratio of ⅔. Now the function is that of a ratio, and there are no numbers being used as a definition, but rather the numbers are defined by the ratio sent into the function. That ratio is further defined by computing it as a combination of 0, and ⅔. This means that the function allows for multiple inputs. What you see in the formula above is a combination of 0, and 1/1.

What does that mean? It means you can add up all the points on a graph, and use their combined ratios, plus a definition for the lowest possible and highest possible point combined with a definition for 0 to locate each position, or each upcoming position relative to the ratio of all other points.

In other words, it is part of a new form of FFT.

It also means that you can combine the ratios of X, Y, and Z to feed them as inputs to calculate all plot points together. (multiple calculations at once).

Why is this more than the millenial questions?

Reminder: Please see proof tables; at this point I would suggest reading some other theory answers I have provided such as the explanation for the double slit (page 17) – no. It’s not entanglement, and it has nothing to do with observation; and an explanation for gravitational lensing (page 18). This is all proven, mathematically; it is not drivel.

If you manage to ignore all of this with this much information at your hands, I’m not sure what to say.

This shows the importance of phase, frequency, and interval relationships in our universe, which I cannot stress enough.

It proves the relationships of point locations (vibrations), and electromagnetism.

It proves that it is not just how strong a magnetic field is, but also its frequency and intervals, along with phase relationships of the objects interacting within, and how those objects then interact with each other. Where objects created within one may interact with others entirely differently than an object created at an outside location.

It removes space-time (singularities) from existence. I believe for good, but can’t discount that we just had the wrong version of it. (I would suggest reading some of my notebook entries if you still disagree at this point)

It removes string theory from existence. I believe for good, but can’t discount that we just had the wrong version of it.

It proves that zero can be any number. All numbers are just ratios relative to another.

It disproves the Hodge conjecture

It will help to solve the three body problem

It disables sampling issues with the Nyquist Theorem (mainly known for sound and digital photography)

It will eventually prove the possibility and help to create perpetual motion outside of atomic structures

It will allow us to map atomic structures

It is a viewport to the universe

It shows that the observation affects you just as much as it affects the observed

It will help redefine PI. Basically, I don’t think PI should exist the way that we see it. PI is kind of like our input ratio. I consider it to be an indeterminate which is being used out of place in the current context.

It will help cure cancer. I had to put this last strictly to keep you from rolling your eyes and going back to what you think you know.

This may sound dramatic, but it will change the way we see the universe, and put emphasis on things we have been ignoring

Some things to always keep in mind when developing your own sets, rules, or functions:

•0 *in ) * in ) Is a simple form for obtaining some answers (ans), but it is not complete due to lack of inputs. This is a helpful shortcut, but not to be relied on for first formulations.

•May be possible to simplify other locations. Note that using phrasing such as “2n” requires a function within the 2 to define. I am working to remove that from previous formulas. Even doing it once turns out to be a complicated mistake to fix.
( 0 *in ) * in )) / ( 0 *in ) * in )) = .125 / .125 – Can be used to balance/inflate numbers.
( 0 *in ) * in )) / ( 0 *in )) = .5 – Can be used to inflate numbers.

•Do not use a predetermined negative number which is not an output from another function until we understand more about why this works.

•Define all numbers leading up to 10 as an equation. Define additional numbers as needed.

•Don’t stop at 0 = .5 – try many different combinations

•Keep everything a function of combinations of 0’s and 1’s.
This is necessary for improving upon computational language. Please avoid using numbers to the power of anything. There are better ways to write out what needs to be done.

•Please also do not use indeterminate numbers such as Pi.

Sincerely,

E

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NP Time Independent (Point Based) Calculations

The items in this specific post are old iterations, and some of these formulas are obsolete. This has been left here for reference purposes. Please see Letter for Science and/or notebook for more recent formulas or ideas.

Stationary Ellipses (Limiter/Maximum)

(n + in(np) – in) / np

 

Calculating 3 Points (Reverse/Exact Point)

-in + ( n + np (in) – in) / np * 2

 

Calculating The 4th Point (Reverse/Exact Point):

 -in + ( n + np (in) – in) / np * 2)
——————————————– 
( n + np (in) – in) / np ) * 2in + ( -2n + np ); * (n(np))

 

Or (denominator):

 

(( n + np (in) – in) / np ) * 2in + ( -2n + np ))

* (n(np))

 

Please note this equation pulls from itself. The final calculation is the answer of the bottom line (denominator) multiplied by N(NP); where say the answer comes to .1333333, it is then brought up to its whole number by multiplying it through a factor of (n(np).

Legend:

N = Point 2 (b) Traveled From 0 Axis
IN = Total Distance Traveled From First And Last Point
NP = New Point Distance (Final) From First Point

 

( n + in (np) – in ) / np
Stationary Ellipses (Limiter/Maximum)
Determination
-in + ( n + np (in) – in) / np * 2
Calculating 3 Points (Reverse/Exact Point)
Lookup
(( -in + ( n + np (in) – in) / np * 2)) / (( n + np (in) – in) / np ) * 2in + ( -2n + np ); * (n(np))
Calculating 4th Point (Reverse/Exact Point)
Lookup
ip + in (np) – in / np equals 0 – Incomplete
n + (np-2n) FFT rewrite – Incomplete Determination
(( n + np (in) – in) / np ) *2) * 2in + ( -2n + np )) * 1/3 needs compressor Alteration
* 1/3
0.85174
Turning 7 into 6: 2in + ( -2n + np )) and /np Balancing
(( n + np (in) – in) / np ) * 2in + ( -2n + np )) * (1 1/3) – 2) / 6
(((( n + np (in) – in) / np ) * 2in + ( -2n + np )) /np + ( -n + np ))) *2) * 3 * 2 * 10
(( n + np (in) – in) / np ) * 2in + ( -2n + np ))
(( -in + ( n + np (in) – in) / np * 2)) / (( n + np (in) – in) / np ) * 2in + ( -2n + np )* (n(np)) broken
(( n + np (in) – in) / np ) * 2in + ( -2n + np )) / ((-in + ( n + np (in) – in) / np * 2in – n)) broken
-in + ( n + np (in) – in) / np * 2in – n ( n + np (in) – in) / np ) * 2in + ( -2n + np )) broken

 

Examples of currently working point combinations:

 

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