Topological Reactors and Emergent $1/f$ Noise in Minimal Spacetime Networks

This paper bridges the gap between foundational discrete spacetime theory and concrete computational experimentation by introducing a massively parallel GPU-accelerated spacetime simulation engine. Using an evolutionary tensor-processing framework, we isolate a non-trivial, highly asymmetric local update operator F that naturally generates anisotropic stress structures and topological phase knots without parameter tuning. By implementing controlled algorithmic cavitation and a perimeter transducer ring, we construct a working virtual "topological reactor" capable of trapping, stabilizing, and harvesting structural network stress. Furthermore, Fast Fourier Transform (FFT) Power Spectral Density (PSD) analysis reveals that the system spontaneously self-organizes to the edge of chaos, exhibiting emergent $1/f$ (pink) noise as a direct fingerprint of distributed network memory. The study concludes with practical engineering applications for real-time Causal-AI digital twins, passive topological metamaterials, and edge reservoir computing.