Structural Differentiation Information (SDI) v1.1: A Minimal and Falsifiable Theory of Information as Irreversible Structural Stabilization

This work presents Structural Differentiation Information (SDI) v1.1, a minimal and falsifiable framework that redefines information as stabilized structural difference under irreversible observation. In SDI, information is not treated as stored data, symbolic representation, or passive correlation. Instead, information is defined as what persists through structural fixation. Observation is formulated as a physical process of irreversible stabilization, not limited to conscious systems. The framework is constructed as a closed progression: (1) structural difference emerges,(2) observation fixes difference,(3) information persists,(4) irreversibility defines existence,(5) learning and memory follow the same principle,(6) a minimal persistence criterion determines information, neutrality, or loss. A central result of SDI is that information formation corresponds to local structural ordering under global irreversibility, expressed as:ΔS_local < 0, ΔS_total ≥ 0. Furthermore, information is shown to be inherently nonlocal:I(x) = ∫ K(x,x') D_obs(x') dx',indicating that information arises from extended structural relations rather than pointwise values. The framework naturally connects physical systems, artificial intelligence, and biological memory, unifying them under a single structural principle of persistence. A key contribution is the introduction of a single decisive and directly testable criterion based on the sign of the fixation rate:dI_struct/ds > 0 (information), = 0 (reversible), < 0 (loss). SDI v1.1 provides a unified, minimal, and directly testable foundation for understanding information across physical, computational, and biological domains.