Historical Computational Progression

Historical Computational Progression is the recursive-exponential trajectory the book fits to the growth of computational capacity: a steady doubling law multiplied by amplification from each architectural breakthrough. The book holds that progress in computation has not been random. By treating information density, system architecture and processing frequency as measurable quantities, its Computational Evolution framework describes how substrate innovation compounds on itself, each breakthrough amplifying the base trajectory. The amplification is the Recursive Amplification Factor R(t) = ∏ᵢ₌₁ⁿ (1 + αᵢ × exp((t − tᵢ)/τᵢ)), with α₁ = 10.2 ± 1.5 for GUI emergence and α₂ = 98 ± 15 for network recursion. Read alongside the Wavelength Scaling Law λ_n = λ₀ × (n + 1)²/n and Information Conservation, the book says the trajectory toward quantum threshold achievement would follow from established recursive dynamics. The model is the Bit Density Evolution ρ▣(t) = ρ₀ × 2^((t − t₀)/T⇈) × R(t), where ρ▣(t) is the bit density, ρ₀ the initial bit density (10³ bits·cm⁻², circa 1971), t₀ the reference time, T⇈ the doubling period (1.8 ± 0.3 years) and R(t) the recursive amplification factor. Dimensions: ρ▣(t) and ρ₀ [𝕃⁻²], t, t₀, T⇈ [𝕋], R(t) [∅]; the book's check is valid and verified. It connects to Bit Density Evolution, the Recursive Amplification Factor, Computational Evolution, Historical Bit Curve and Wavelength Scaling Law.