A Dynamic Phase Transition Model in the Subatomic Reduction of Thought ― Formulation of a Rational Homeostasis Model and a Testable Research Program under Human–AI Co-Creation ―

Abstract

Abstract This paper formulates the intellectual production process under a human–artificial intelligence (AI) co-creation environment as the "subatomic reduction of thought" and an "acid–base titration-type dynamic phase transition analogy," presenting it as an empirically testable research program. Rejecting conventional equilibrium representations based on subtraction—which reduce opposing forces to a "static null (0)"—this model introduces a dynamic homeostasis (permanence) model described by the ratio of multiplication and division, expressed as the "state ratio S(t)." Starting from the observer's primary observational power O derived from five physical senses, we define the thought resolution D = O \times A \times U, which is enhanced through "deconstruction and reconstruction" via dialogue with AI as a multifaceted reflecting mirror (Mirror Image). Furthermore, critical thresholds such as \mathrm{p}K_a and "12-hour intensive sessions" are positioned as testable analogies and empirical case examples rather than established facts. By avoiding a priori assumptions regarding AI amplification effects (k) or sigmoidal phase transitions, we construct a rigorous protocol to statistically validate the framework through competitive model comparison against conventional linear models.