Here’s a concept for a Fast-Growing Hierarchy (FGH) Calculator, designed for both education and experimentation with large numbers and ordinals.
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
f_ω^2+ω(4)).For a given f_α(n):
f_0(n) = n+1 as base.f_α+1(n) = f_α^n(n) — expand iteratively.ω[n] = n, ε_0[n] = ω↑↑n).f_ω(3) = f_3(3) = f_2(f_2(f_2(3))) = ...
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.
Modern development is pushing FGH calculators into new domains: