Recursive Complexity Growth

Recursive Complexity Growth is the nonlinear accumulation of computational complexity, following P(n) = (n+1)², that BPT puts in place of the linear progression of classical harmonics and that produces Nonlinear Harmonic Spectra. In classical systems the nth harmonic of a fundamental f_0 is f_n = n × f_0, a linear additive series. BPT replaces this with Recursive Complexity Growth, reflecting the computational architecture of the binary substrate: harmonics emerge from Prime Pulse Bifurcation working through Recursive State Evolution, where each generation inherits and amplifies the computational load of those before. The load grows as L(n) = L_0 + n(n+1)/2, and that quadratic growth is what shows up in the frequency domain as harmonics scaling with (n+1)², linking computational load to pulse density and Temporal Drag. The current definition states the growth pattern as P(n) = (n+1)², where P(n) is the pulse density and n the recursion depth. It connects to Nonlinear Harmonic Spectra, Harmonic Complexity Scaling, Computational Load Accumulation, Recursive State Evolution, Prime Pulse Bifurcation and the Harmonic Origin Pulse.