Persistent Excitations in Adaptive Field-Topology Networks

This work investigates emergent persistent regimes in a large-scale constitutive network model where a scalar field co-evolves with an adaptive connectivity structure. Rather than assuming a fixed background geometry, the model is defined relationally through time-dependent weighted connections and local update rules. Using long-duration GPU simulations, the study identifies reproducible nontrivial dynamical organization and develops an initial framework for analyzing its statistical and structural features. The results are presented as a methodological and empirical contribution toward the study of persistent objects in constitutive network dynamics.