Growing Hierarchy Calculator Best — Fast

Here’s a concept for a Fast-Growing Hierarchy (FGH) Calculator, designed for both education and experimentation with large numbers and ordinals.


The Core Challenge

Building an FGH calculator is not like building a standard arithmetic calculator. You cannot simply store numbers as 64-bit integers. The output for ( f_\omega+1(10) ) is so astronomically large that even representing its logarithm would overflow memory. Therefore, a real FGH calculator must operate in one of three modes: fast growing hierarchy calculator

  1. Symbolic Mode: Keeps the expression in a simplified FGH form (e.g., f_ω^2+ω(4)).
  2. Approximation Mode: Uses Knuth’s up-arrow notation or Conway’s chained arrows to give a coarse magnitude.
  3. Hardcoded Limits: Only computes values for very small ( n ) (e.g., ( n \leq 5 )) and small ordinals (e.g., ( \alpha < \omega^2 )).

2. Step-by-Step Reduction

For a given f_α(n):

Fast-Growing Hierarchy Calculator — Report

3. Recursive Evaluation Engine

The evaluator must handle deep recursion. For example, computing ( f_\omega+2(3) ): Here’s a concept for a Fast-Growing Hierarchy (FGH)

[ \beginaligned f_\omega+2(3) &= f_\omega+1^3(3) \ &= f_\omega+1(f_\omega+1(f_\omega+1(3))) \ f_\omega+1(3) &= f_\omega^3(3) \ f_\omega(3) &= f_3(3) \quad (\textsince \omega[3]=3) \ f_3(3) &= f_2^3(3) \dots \endaligned ] The Core Challenge Building an FGH calculator is

Even for ( n=3 ), the recursion tree is enormous. A naive implementation will crash due to stack overflow or infinite loops. Thus, memoization and tail recursion are mandatory.

Part 8: The Future of FGH Calculators

Modern development is pushing FGH calculators into new domains:


Key Features