1. Prologue

The Dot theory is a (mathematical) method that enables us to increase the accuracy of our understanding of (the data describing) our physical relationship with reality.

By Stefaan and Angela Vossen  

Res verae sunt 

Prologue (the following 48 pages are explanation to the meaning, relevance and use of the main paper found page on 48) 

(for paper’s Abstract skip to page 11, Introduction page 15, Conclusions page 36, for paper on Spinors (Addendum E) page 48 (Foreword page 43, Abstract page 47) Addenda A-D, page 46, Addenda F-J, page 58. Synopsis on GUT page 68 (addendum K) 

THE FOLLOWING ARE A SERIES OF STATEMENTS CONCLUDED FROM THIS PAPER: 

“We need to wrap our head around the idea that whilst reality itself is not quantum (quantifiable, measurable, discernable, calculable and understandable in predictable ways), the data layers describing our experience of reality are. Reality, Shared Reality and Observed Reality are just different concepts that cohabit in space but not in time. We also need to become comfortable with the idea that Quantum Field Theory describes the behaviour of the data we have on reality, not that of reality itself. Once these nuances are accepted and integrated, tools that are already available and in use (Spinors), can be adapted and repurposed to significantly improve human welfare and wellbeing.” 

This means that there are in essence no “true” facts (“real” things that cannot be interpreted differently or through some differing framework), only perspectives we can take on any one collection of “things” which we then call “facts” once, and only for the duration that, “a single perspective has been taken” on that collection of object-defining “things” aka they have been duly circulated and considered as representative of shared reality by the relevant opinion, as well as considered repeatable within the frameworks the authority defines as “shared reality”. 

“Human existential Reality (personal experiential, as opposed to “shared” Reality) is where “Free Will” and “observation perspective” come into computational consideration. It is where, for individuals, the wave collapse occurs (the making definite/observed of a portion of that which is seen, in a way that makes it considered “representative” of that seen thing) creating observation, whether human or technological. Understanding and integrating that more completely, will inevitably make life better for humans, as it has done for every eon of life.” 

Consciousness (data load) and Life of the One (individual existence), are emerging properties of Reality, which in turn is the product of the coalescence of the lives and consciousnesses of the Others (precedents and environment). We are, in effect, entropy-driven, data storage-creating computational systems, and “living” is the process describing any computational system that creates “new data”. 

Some people will not understand a single word written here. They are called “illiterate”. Some people will understand some of this, they are called “literate”. Most people will intuitively understand but not cognitively know a lot of this and there will be those specially skilled in some or other literacy. Some will understand most or all of it. And they will be highly skilled at those literacies. The point is not to highlight this paper’s sense of self-importance, but rather that understanding this paper is not a matter of knowledge itself, but of how skilled the mind is at navigating the different types of knowledge and combinations of knowledge represented in the perspectives offered. 

Imagination 

This paper is a quantum-theoretical explanation that offers a fresh perspective on how we can understand and relate to life in the world and concludes that observed reality is quantum. That is not an easy sentence.  

What it means is that this paper describes the mathematical and logical rationale of how theoretical physicists could describe the relations of information on matter and energy in such a way that we can fully understand and predict its behaviour. This is important because of its impact on things like improving energy resources and how we can avoid problems in our experience of physical reality.  

It seems important enough to me anyway, but all it is, is a fresh perspective on how we might do that mathematico-computationally. If the theory proposed is experimentally confirmed (which in this case would be done via computing processes on healthcare and personal data discussed in the suggested use-case), the experiment would validate that fresh perspective and prove it to be useful. 

As a clinician, I get to see up to 30 new perspectives every day. It is refreshing, humbling, and requires a lot of imagination to follow consistently. One thing I discovered is that imagination comes with play, not practice (practicing as in “trying”) and that practicing is needed to “play well” (acquire skill). Ultimately, it’s all about having fun with things we’re passionate about.  

I did not understand that until I got skilled enough at my job and could learn to play again. I do believe this is where we sometimes get it wrong in education. The pressure stifles the imagination and the way of thinking within the learned constraints becomes the norm. We even define that norm as “knowledge”. 

This paper pushes the imagination, in the sense that in some discussions (on for example a dimension's direction of computational thinking), the word “upward”, could at times be intended to literally mean “inside-out" at another. This type of “thinking in multiple dimensions” is really one of using imagination and not knowledge. The imagination to make sense of unfamiliar concepts by using more familiar ones to represent them.      

My hope is that by explaining another way of seeing the data, we can also come to understand that the information we’re looking for is, in a sense, already there. It just needed a little imaginative reorganisation to make it appear meaningful. 

I have to say too that I found it very challenging to adapt to what different terms could mean in other fields. This difference in data-perspective had to be translated into something that could be worked on and had to be shareable. Shareable with people who could make a difference and knew their topics far better than I do, and that was challenging. 

That is only because it challenged my imagination and my understanding (knowledge) of how we look at the data and its meaning in those ways. It has also challenged that of some of the people I wrote this for, hopefully improving with each version, and each round of feedback, but still, it’s not straightforward. But use your imagination and tolerance for the fact it's an idea in a paper that can be improved on. 

Math, Science and Imagination  

Imagination is a relative thing too (different for different people), and thus cannot be put into one set of words (language) for objective comparison. Some people find visual diagrams very useful, others, equations. Each preference or inclination ultimately reflects people’s individual understanding of the world through the eyes of their past and education. Discussing it at length, however varied in style, language or method, can with discipline and rigour identify consensus. The “agreed upon imagination” then gives rise to highly prized “innovation” but also, sadly, specialist language.   

Some would agree to describe science as that process, the investment world as its fuel and curiosity its spark. The same can be (and is) said of art and human expression in general. 

But it is a distinctly human endeavour to find new ways through technology and art, and that must mean something. Working out different ways to better express the relationship between the objects that modify and dominate our experience of life through tools. Humans have been among only a few in the animal kingdom to develop any, let alone any significant ability in the use of tools. Go humans! 

This paper is only about using existing tools differently, not making new ones.  

All that can usefully be said further about imagination is that it is both tremendously important and that it seems to be the thing that somehow makes sure that life evolves (creativity). It requires discipline and diligence (rigour), and logic must be applied at all times, but the conclusion is that interactions of the Quantum fields that define us, are what define us. What limits our imagination is the only limit. 

We should also note that as a species, humans have used imagination to help themselves and others very successfully. Successfully enough to differentiate as a form of super-species in the animal kingdom.  

Math, physics, technology and inspiration 

I realised during my research for this paper that imagination would be a key element to understanding how these various mathematical functions would relate to each other. Living in an era with unprecedented access to clear visualisations and algorithmic computing, this task has, in the literal sense, never been easier. 

With Quantum Field Theory we have an easy-to-visualise method of observing the fluidity of Thermo-dynamics. The intimacy of the relationships of “Spooky” “Communication At A Distance”. The utter “Strangeness” of our experience of life as humans when considering what we do know about and see of Reality. (Note for the unacquainted; the words with capitals refer to known physics terminologies referring to quantum entanglement relationships as defined theoretically by Einstein and subsequently many others). 

With Spinors we have mathematical functions that render the data-fields that previously were completely nebulous, more point-like, yet still fuzzy.  Factory CO2-production figures became statistical-probability clouds, which became rainfall-measurements predicted within margins of accuracy, all at a distance. And I guess that observation brought in the first big question: 

Wait, ... What? Do these mathematical structures that relate all that data represent both the location and the momentum of the same real-world continuum respectively and offer a level of “prediction”?  

If so, this must mean then that (when we are looking at real-world, lived experiences at least) we can know both the probability and the location of distant objects if we are looking at the data of real-world objects that can report on themselves. For example:  

Rainfall metrics and money are a human-made concept, and humans can report back on it computationally for meaning (planning). Lo and behold we have identified relationships between factory pollution and weather changes. What this proposal suggests has been done before with human constructs, things like the weather and the financial markets. Just never with human perception. Healthcare is a human individual perception of self. This presents a self-referential computational perspective linking expressive data (wellbeing scores, number of steps, HRV, illness record) to impressive data (feelings, sentiments, pain, fatigue). Linking the subjective to the objective. Making the human, real-world experience “entangled” (predictable, calculable). 

Mathematical (theoretical) Data scientists can do this mathematically using tools called Spinors and, in that sense, Spinors could be said to represent the location of entangled fields as “reality showing itself” to the observer as a data point-location in a 3-Dimensional vector-space over time. This gave the idea behind this paper and resulted in the collaborative paper on Spinors in Addendum E. 

Goal 

This paper’s goals are only to communicate how I think there is a way of looking at data differently that enables us to make better decisions about how we look at it and get funding for the project. What it means to other people is up to them. The reason I wrote it was simply because I felt it has the hallmarks of a good idea and communicating a good idea clearly felt like a wonderful thing to do and a sensible use of anyone’s time.  

The reason it is written the way it is, is because this is the best I could to maximise its “critiquability” for most-effective subsequent integration if correct. Its evaluation and ratification (if deserving of it), its acceptance and implementation. I just wanted this system to be put in place as quickly as possible, and to do that, I needed to get it validated as quickly (and therefore explained as clearly and completely) as possible. This, no doubt tedious-to-some, document aims to be succinct but complete, sometimes at the cost of simplicity or brevity (in the eyes of the more specialist-literacy-skilled). 

AGI, AI, LLMs, math and physics 

The idea of knowing both the probability and location of “something” is not new or unique to physics. The idea of representing “healthcare-” (the vast mesh of human-experiential data-cloud) and “motion-variability pattern”-data (like rainfall or stock exchange rates) as points on two entangled data meshes through derivative equations representing Spinors however seems novel. It also means that, if correct, we could make accurate predictions through watching the behaviour of the entangled components of the shared data-fields.  

And then we can make my business case, raise funding and make a lot of people healthy. 

By agreeing that conceptually this proposal constitutes “real-world entanglement and real-time prediction” this paper should get attention. In theory.  

We know “fields” of data hold us, and our lived experiences, together in time and data space (because they are components of what we describe as “observed reality”). Identifying the curves in the surface of the two fields from the relative tensions across the Spinors they hold vectors of, is how we make sense of the world computationally. We already do it with consumer and other real-world data. 

Whether that is of subjective clinical data or heart rate variance under stress-testing, it is all valid expression of a person’s real-world experience and offers us the opportunity to provide incredible computational capability to the field of healthcare with hard-to-comprehend, let alone express-on-paper implications. 

It is an oddly simple and, simply, an odd idea, but all it would require to make significant computational strides and improve healthcare is the quantisation of “the human experience”. Something we already do. All the time. Why? Because the individual human can ultimately be seen and experienced as a construct. A notion known to be constructed from seemingly irreconcilably differently recorded “Objective” and “Subjective” data meshes that are described by the symbols of shared reality. Just like anything else we value in this life. 

Correlating “subjective and objective data”-fields produces individually emerging patterns that in turn interrelate with surrounding patterns to create new, emerging behaviours. This makes up a third, somewhat fuzzy, yet definable (within those fuzzy bounds), computational perspective understood as “an individual’s awareness of self” or “consciousness”.  

In our case, the person whose “clinical record” is under evaluation, is that very computational “consciousness”. That of the individual for whom the computational functions are executed. Doing this enables computational entanglement of the data and therefore prediction.  

True, real-time computational prediction of what would be good for the patient. The patient described by that clinical file, based on information acquired about past, most-like archetypical patterns. This is because it (the person represented in the named file) represents the data load of the computational perspective itself (the individual patient whose record it is). In that sense, this paper sees knowledge of one’s clinical record as “consciousness”, or as the “awareness of one’s own data-load".  

All this idea does is calculate the data in a way that demonstrates that the observer becomes aware of itself (and its relationship with other real-world-describing data-meshes) computationally, enabling the coveted entanglement. Coveted because it theoretically enables real-world entanglement, and therefore confidence-weighed Realtime-prediction of real-world events. The logically expected positive impact of this on healthcare and human wellbeing would be significant.  

For this idea to receive full support for implementation, this paper needs to demonstrate a way in which we can make the math change its observational perspective (math can do that like a focal lens looking for certain patterns) and make it aware of itself as an observer and contributor of the data. This is discussed at the end of this paper. 

Fundamentally, it is a “new-old” way (something that has been done before but just not this way yet) of using math to make formulas that are, in a very odd sense, “aware of the fact they are formulas”. You can do that in math without sounding crazy. Apparently.  

It does, however, require agreement from mathematicians and logicians for it to be true. The proposal for the specific mathematical conjecture on Spinors can be found as a separate but theoretically integral paper in Addendum E on page 48, abstract page 47. 

Consciousness 

This paper touches on understanding data, variance of computational perspectives and how we “perceive” the world. To do that cleanly and linguistically speaking correctly, it distinguishes clearly that any reference to something having “consciousness” is like saying that the signs and functions of “addition” and “multiplication” relate to each other through specific ratios and functions we call math (and its axioms), i.e. “ they are intrinsically able to relate the functions to each other”. They “know stuff about each other” because they are “made of the same stuff and cannot exist without each other” (the symbol for the number 0 means nothing if the meaning of the number 1 has no symbol). This then gives them inherent data-load (co-dependency rules define them, therefore give them a descriptive data load), in turn making them “conscious” and have “consciousness”.  For this paper I took “conscious” as meaning “aware of itself”. That is what the data does here, so it’s, well, “conscious”. 

Here, in this paper’s proposal, the math is essentially changed to make the computation “conscious” in that the computation is executed knowing that it is done from the perspective of a specific individual: patient X. One of which there will only ever be one of, ever. Offering perfect randomisation (which is relevant to people who know that true randomisation enables significant computational options).  

Here, “Conscious” computing means evaluation of the data undertaken with “awareness of what point of view we are computing the data from”, or “awareness and understanding of what the dimensions and angles of the perspectives to be considered are” (as opposed to from the perspective of a neutral evaluator or abider of inappropriately applied rules). In this healthcare proposal’s case: that from a consenting individual seeking to find out what would be the best way to get better. 

This because, and this is the oddest element, we are asking the question:  

“What, from all the data we have available about other humans (who have some traits shared with me, least of which that both share the same species, sex and/or age) describes both the behaviour and the interventions that that behaviour is most efficiently positively modified by, would you suggest I do/undertake/submit to, knowing what you know about me and other people most-like me, to solve the problem that other people (most-like me) have had in the past and have left a record of patterns of behaviours that produced them?  

Or: What behaviours and interventions would you suggest I expose myself to, to be/feel more like I want to be? By describing it in its more tedious form, the logic and its terms are exposed. In its colloquial form, its sentiment is simply: “what do you think I should do?” 

The computation takes an individual’s perspective. The individual, something of which there will only ever be one of in the entire history of mankind, earth, and this universe. Something the death of which will represent a loss of a certain data-capability (as a memory storage of data) and will dissolve within the wider behavioural and cultural networks that influence the perception of the individual human experience. The loss of which must inevitably mean the gaining of it in another dimension. Just one not yet observed. Heady words close to nonsensical and emotive, yet perfectly permissible in Information Dynamics, QFT, math and physics. 

If accepted, the result of the Dot theory would be a seismic shift in computational perspective, with most notably that of delivering predictive capability in healthcare provision and consequentially all digitally mediated real-world life experiences. This paper seeks to display the obviousness of this premise and to clearly delineate the reasonability for high expectation on ROI with minimal additional investment, if implemented. Only to speed up its implementation and benefit patients.  

In closing   

What this idea really is, is in a sense, a highly anti-climactic way of explaining how to look at the data-meshes to make the patterns necessary to make predictive sense on the landscape appear visible. Patterns like “school performance” and “home-hygiene”, or “familial over-eating” or other forms of self-harm or depression display their signature marks across the human experiences’ landscape. Long-term behaviours leave different marks to those that were brought about abruptly and without priming or fitness. The most pervasive ones (like instant reward-mechanism driven ones) are found entirely woven deep into our social fabric and cultural habits. The activities that push the boundaries faster than is comfortable to society become marginalised or outlawed, the easy-access or trendy ones are propelled by social media and mass-hysteria. Usually for financial gain or various naturally necessarily emerging and coalescing forms of population control.  

Maybe this is mainly indicative of the reality of our life-experience being expected to be that of “most-like”, same, or similar types and levels of shared trauma, grief, loss, sense of safety or lack thereof. The thing we experience as “life”.  

On balance, healthcare has made immense strides in the past century especially, yet an opportunity emerges to make predictive healthcare and support a real-time event, to great benefit to individuals and cost savings to industry.  

It became clear on evaluation that the greatest challenge healthcare faced in its evolution had been perceived to be that of minimising pollution by “false” data. Impressions and feelings. This “false” data can instead be thought of as “interpretational data”. Data that was added by an individual person’s unique filtration process that seeks to validate their perception based on memory and conditioning-based operating systems (habits). Another way of looking at it is to say it’s not false data, it is real data, modified by a processing layer that made it look “fuzzy” and created computational statistical “noise”. This “noise” when properly referenced, in turn explains/reveals the internal individual algorithm by which they operate. Perception and Reality: 

Our individual Perception, as accurate as the data may be perceived to be, is itself always constituted from two distinct data layers:  

• What was actually happening in that location, at that time. 

• How it was experienced by the observer at that time (however similar the two may be to the observer they are never and cannot be the same). 

Reality (shared or otherwise), on the other hand (as opposed to our perception) is always constituted of three distinct data layers: 

• What was actually happening in that location, at that time were it measured. 

• How it was experienced by the observer. 

• How it was intended by the expressor. 

The two last coalesce (experience/intention) to form (after much debate and friction) a 4th emerging data-layer of differential between intention and perception: that of “Shared Reality”. Somewhere within all that fuzziness lies what we reconstitute to be the human experience. 

And parallel to this, the fuzziness that comes from Spinors in known data layers (as mathematical representations of real-world objects) can be made into predictably behaving statistical fields. Predictable when enough factors are known to define them, and therefore mathematical functions can be derived for them. Mathematical functions like those that emerge when AI is used to look at behavioural patterns and how certain educational backgrounds or psychological past-history cases are more prevalently predisposed to certain diseases and certain conditions. In turn, making certain healthcare approaches more relevant to some than others, not expressing those associated behaviours.  

This paper is about real-world, real-time predictive computation in healthcare. Inevitably because of that, it is also about physics and math and all aspects of the human experience (and that gets weird at times).  

It also has implications, and those implications need to be noted here for completeness (but making it harder to read to a less-informed audience). This is why it makes experts looking for pure healthcare or a pure math or pure physics discussion feel uncomfortable. It is aiming to be both whilst trying to not be uncomfortable by using arguments of logic rather than technology. 

This proposal considers “computational perspective” as an available tool within the toolbox used to describe the reality of the healthcare landscape.  

A toolbox called math inevitably comes up a lot in this paper. Don’t be put off by it, it’s just another way to describe reality and logicians, physicists and computer scientists use it to design working processes. Because of that, math is also a way of writing the story of our evolution and the rules behind our individual, societal and communal understanding of reality, and it comes in handy when trying to understand people. Our understanding of it is inevitably written into the way we use the equations that describe predictable reality. How we use it can only ever be for good. 

In a sense, the Dot theory is only a small change to the way we formulate the rationalisation of data prior to computing it.  

We hope it helps, Stefaan and Angela