System 4. The Peet Tent, MCQPS & QSF
The Peet Tent was principally inspired in 2012 by Dr Amanda Peet’s lecture String Theory for the Scientifically Curious in which she presents a string version of a Feynman Diagram and explains how this effect makes string theory very economical. If I could translate that into economics in S-World it would surely be significant. At the time I added a section to the 3rd American Butterfly book ‘The Network of a String,’ but I did not fully appreciate its significance.
It took three years for me to come up with a suitable simulation within the network design. The point that Dr Amanda Peet is making is elaborated in her more recent lecture String Theory Legos for Black Holes, as the vibrating loops of strings did not have specific points, they could accept any variety of result. This is in fact how string theory unifies general relative and quantum mechanics. Peet describes the jittery results of quantum mechanics unifying with the smooth results of general relativity by sting theory creating a big tent for them to sit under. This effect is also discussed in lectures from Professors Susskind, Greene & Witten.
It’s a tricky one to simulate, and it took a great deal of work on the micro-economics, and it required the creation of the GGW String. Albeit to be precise, the idea of the GGW-String was a result of the Peet Tent. The answer in the end was very simple, one just changes the shape of the GGW-String to emit enough capital to boost any company result that was not sufficient. Given that there is enough money in the network, all businesses we safe, permanently, which amount other things would have a great effect on investment into companies in the first place.
Added to the Peet Tent was the MCQPS (Monti Carlo Effect Probability Software) and what I have labelled QSF (Quantum Safe Forecasting). QSF adapts the Heisenberg uncertainty principle to tell us that one can increase the probability of achieving a set gross profit at a point in the future, simply by lowering the estimate, and that we should consider doubling the uncertainty when we double time (one year to two, or two to four). The MCQPS tells us that for each expected reaction, we should always pick the lowest probability, as we now do to all TFBMS forecasts (1, 2). Collectively when used to create financial forecasts QSF & MCQPS help to make sure that a company will not get into to trouble in the first place.