GRANDHOLD OF ABYSS

SECTION 1
ABSTRACT

Fractal complexity computation is both an excellent source of computational power and data storage. The rate which capacity for computational power and data storage increases faster than older methods.

SECTION 2
SUMMARY

Fractal complexity computation is a fundamental form of generating computational power. It is composed of recursive, interconnected, and self-sustaining Foundspace quantum constructs paired to an Ilgospace quantum processor known as a fractal unit. The increase in computational power as fractal units are added is by a squared exponential factor (x^{y^2} / x^y*y).

In simpler terms, fractal complexity computation generates computational power by creating clusters of stable (will not decompose when unpowered) quantum objects (in Foundspace) connected to one-another in a web-like pattern. These clusters are paired with a physical quantum processor which can read/write information from/to its cluster. Each added processor increases overall computational power by a squared exponential factor. Squared exponentiation is what exponentiation is to multiplication.

• Electrical/photonic processing power is determined by linear growth. (x*y)
  • Ex: 3*3 = 9
• Quantum processing power is determined by exponential growth. (x^y)
  • Ex: 3³ = 27
• Fractal processing power is determined by squared exponential growth. (x^y2)
  • Ex: 3³² = 19,683

Unlike electrical, photonic, and quantum computing, information can be stored indefinitely in a fractal processor without power, allowing for fractal processors to be used for raw computation and permanent data storage/memory (power is still needed to perform computation or access data). As such, fractal computation units may be used as either a computational processor core or data storage cell. Usually, fractal units are used for either computation or storage/memory; fractal memory-units have far higher raw information storage capability, but have less effective processing power. Fractal processor-units have higher per-unit processing power, but store overall less information. All fractal units lose potential processing power as units are used for long-term data storage; it is best to keep fratal processors and fractal memory separate.

SECTION 3
HISTORY

Fractal complexity computation was developed on date [26,218-8-27 GE] by the Quantize as a solution to stagnating improvement in quantum computation.

After the standard rampup period where a new technology is improved to the point that its cost-to-effectiveness ratio outweighed that of the most recent of quantum processing units, fractal complexity computation overtook quantum computation as the best form of generating computational power.

The unexpected property of fractal complexity computation to store information lead to the then-contemporary digital storage mediums being surpassed by fractal complexity computation as well.