Relational Becoming as a Minimal Generative Model of Memory-Driven Dynamical Regimes

A minimal relational architecture composed of phase duality, trace memory, and feedback can generate emergent laws, reproducible predictions, and multiple classifiable dynamical regimes. From this architecture we derive two experimentally independent laws (trace-gradient birth and relational coherence), reduce them to a minimal generative core, test their robustness across topology, size, and material definition, benchmark them against standard reference models (Kuramoto oscillators, Reservoir Computing) in which the phenomenon is not observed, generate a prediction (a sign-reversal phenomenon) that is reproduced on independent data, subject it to a four-attempt falsification program, and map its first regime (phase) diagram. All results are explicitly bounded by the specific computational implementation tested and are not generalized beyond it without independent verification.