I often talk about the exponential value of data retrieval tools. We know that certain numbers like 2 Pi, (Pi / 3), 2 / 1.62231147 or sqrt 60 and (1 / sqrt 60) can have remarkable value at connecting and expressing whole series of important numbers, and this is because of their value at higher powers, such as their squares (second power), cubes (third power), and etc.
We have seen time and again how often these numbers seem to appear in ancient architecture, with good reason. One of the things that this does is to often turn each structure into something of a lesson in itself, as well as simply providing us with plenty of data, although data storage is more or less the name of the game when it comes to “writing” important numbers into the measures and proportions of ancient architecture. That, of course, is data storage and retrieval.
In the event a given structure were the first structure to be analyzed in such a manner, we would be much more likely to see how the math operates on a first outing, rather than having to glean the very basics by examining one site after another and perhaps missing the patterns in evidence.
Yet if we do adopt an careful overview of the architectural data, the same patterns emerge. It’s difficult to find Mayan architecture that doesn’t seem to have one of the top few data retrieval tools trying to leap out at us.
The concern of conserving, where possible, exponential value can and should shape our efforts at interpretation, including that it’s relatively rare for nice round numbers to show much exponential value, with the obvious exception of simple multiples and fractions of the number 360, but even the there are limits. The usefulness of even whole numbers like these often peaks by the fifth or sixth power at best.
At any rate, rather that limit the discussion to random mentions of the exponential values of certain numbers or populate the page with extended recitations of examples, I though for once I would attempt a display for readers, and I apologize for being remiss in providing one earlier.
This shows some of our most important numbers and their exponential value, ranging all the way from about the first power for (Pi / 2) all the way up to a recently discovered record for square root 60 peaking at the 33rd power ((sqrt 60^33)) in certain equations relating to existing circular architecture (see: “At the Altar of Heaven“).
We can probably see a few interesting things here. Notice the cluster of powerful and useful constants peaking at about only the 4th to 6th power. The vast ancient popularity of some of these numbers along with their exponential properties tells us it may have often been adequate for the purposes of the ancients to build in only a few extra pieces of data into a particular equation through the selection of numbers with exponential value.
It might also help to show why the very highest premium may have been placed on about the four most powerful data retrieval keys, starting with the quintessential 2 Pi, and why Munck’s Squared Megalithic Yard is so important.
We can see why, even when raw data shows us figures like 1.627-something, we may still often actually be looking at 1.622311470. There are many similar numbers, which we may actually sometimes see, but most often
We can see why, even when raw data shows us figures like 1.627-something, we may still often actually be looking at 1.622311470. There are many similar numbers, which we may actually sometimes see, but most often by far we may see 1.622311470.
We can see why, even when raw data shows us figures like 1.627-something, we may still often actually be looking at 1.622311470. There are many similar numbers, which we may actually sometimes see, but most often the properties of 1.622311470 may make it so desirable that it is what we will most often see.
The very same is true for my standard working value for the Harris-Stockdale Megalithic Foot (HSMF), which is Munck’s “Alternate Pi” 1.177245771.
In essence, the chart makes predictions about the frequency with which we will see certain numbers in ancient architecture, predictions which the data already seems to generally have lived up.
–Luke Piwalker
Luke Piwalker 