## 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 Navier-Stokes. 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

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:

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.

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

Old iterations:

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: