A Phenomenological Thermodynamic Architecture for Behavioral Topology: Variational Information-Biochemical Potential Flux Under Allostatic Constraints

This paper introduces a generative, macroscopic behavioral analogy that maps human personality dynamics as an open-system attractor manifold operating far from equilibrium over neuro-endocrinal and behavioral state spaces. By synthesizing variational free energy minimization (Active Inference) with catastrophe theory, we formulate a phenomenological scaling architecture capable of generating macroscopic behavioral taxonomies from underlying state pressures. Personality traits emerge as low-dimensional topological features of a non-linear dynamical system driven by continuous, digital telemetry. We evaluate this architecture using a differentiable reference implementation in JAX, providing an empirical bridge between statistical information physics and longitudinal psychological modeling while resolving core issues of dimensional homogeneity and numerical optimization stability.