Structural Differentiation Information (SDI) v1. 0 proposes a minimal and falsifiable redefinition of information based on structural differentiation. In this framework, information is not treated as stored data, symbolic representation, or passive correlation. Instead, information is defined as stabilized structural difference that persists under observation. The core idea is summarized as follows: Distinguishable variation emerges within a system Observation stabilizes this variation Persistent information is the subset of variation that survives fluctuation Positive fixation defines informational persistence The central mathematical relation is given by: Istruct=−log (1−ηD) Iₒₓₑₔ₂ₓ = - (1 - D) Istruct=−log (1−ηD) where DDD is structural difference and ηη is a scaling parameter. This mapping captures the irreversible stabilization of difference into persistent informational structure. As D→1D 1D→1, the divergence reflects the saturation of distinguishability and asymptotic fixation of information. A key conceptual shift introduced by SDI is: Information is not stored. It is stabilized structural difference that survives observation. The framework establishes a closed structure consisting of: Definition (difference) Observation / fixation (mapping) Distinction from noise (persistence under fluctuation) Persistence condition (dIstruct/ds>0dIₒₓₑₔ₂ₓ/ds > 0dIstruct/ds>0) Conceptual closure SDI is intentionally minimal and does not modify existing mathematical frameworks such as Shannon information theory. Instead, it provides a structural reinterpretation that is: conceptually minimal internally consistent structurally closed directly testable in principle This work provides a unified perspective in which information is understood as a persistent structural phenomenon rather than a stored quantity.
Koji Okino (Fri,) studied this question.
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