Structural Differentiation Information (SDI) v1.0: A Minimal and Falsifiable Structural Theory of Information

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Autore principale: Okino, Koji
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Pubblicazione: Zenodo 2026
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author Okino, Koji
author_facet Okino, Koji
contents <p>Structural Differentiation Information (SDI) v1.0 proposes a minimal and falsifiable redefinition of information based on structural differentiation.</p> <p>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.</p> <p>The core idea is summarized as follows:</p> <ul> <li>Distinguishable variation emerges within a system</li> <li>Observation stabilizes this variation</li> <li>Persistent information is the subset of variation that survives fluctuation</li> <li>Positive fixation defines informational persistence</li> </ul> <p>The central mathematical relation is given by:</p> <p><span><span><span>Istruct=−log⁡(1−ηD)I_{\mathrm{struct}} = -\log(1 - \eta D)</span><span><span><span><span>I</span><span><span><span><span><span><span><span>struct</span></span></span></span><span></span></span></span></span></span><span>=</span></span><span><span>−</span><span>log</span><span>(</span><span>1</span><span>−</span></span><span><span>ηD</span><span>)</span></span></span></span></span></p> <p>where <span><span>DD</span><span><span><span>D</span></span></span></span> is structural difference and <span><span>η\eta</span><span><span><span>η</span></span></span></span> is a scaling parameter.</p> <p>This mapping captures the irreversible stabilization of difference into persistent informational structure. As <span><span>D→1D \to 1</span><span><span><span>D</span><span>→</span></span><span><span>1</span></span></span></span>, the divergence reflects the saturation of distinguishability and asymptotic fixation of information.</p> <p>A key conceptual shift introduced by SDI is:</p> <blockquote> <p>Information is not stored.<br>It is stabilized structural difference that survives observation.</p> </blockquote> <p>The framework establishes a closed structure consisting of:</p> <ol> <li>Definition (difference)</li> <li>Observation / fixation (mapping)</li> <li>Distinction from noise (persistence under fluctuation)</li> <li>Persistence condition (<span><span>dIstruct/ds>0dI_{\mathrm{struct}}/ds > 0</span><span><span><span>d</span><span><span>I</span><span><span><span><span><span><span><span>struct</span></span></span></span><span></span></span></span></span></span><span>/</span><span>d</span><span>s</span><span>></span></span><span><span>0</span></span></span></span>)</li> <li>Conceptual closure</li> </ol> <p>SDI is intentionally minimal and does not modify existing mathematical frameworks such as Shannon information theory. Instead, it provides a structural reinterpretation that is:</p> <ul> <li>conceptually minimal</li> <li>internally consistent</li> <li>structurally closed</li> <li>directly testable in principle</li> </ul> <p>This work provides a unified perspective in which information is understood as a persistent structural phenomenon rather than a stored quantity.</p>
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spellingShingle Structural Differentiation Information (SDI) v1.0: A Minimal and Falsifiable Structural Theory of Information
Okino, Koji
information theory structural differentiation information emergence structural information irreversibility observation persistence noise vs information minimal theory falsifiable framework complex systems nonlocal structure SDI
<p>Structural Differentiation Information (SDI) v1.0 proposes a minimal and falsifiable redefinition of information based on structural differentiation.</p> <p>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.</p> <p>The core idea is summarized as follows:</p> <ul> <li>Distinguishable variation emerges within a system</li> <li>Observation stabilizes this variation</li> <li>Persistent information is the subset of variation that survives fluctuation</li> <li>Positive fixation defines informational persistence</li> </ul> <p>The central mathematical relation is given by:</p> <p><span><span><span>Istruct=−log⁡(1−ηD)I_{\mathrm{struct}} = -\log(1 - \eta D)</span><span><span><span><span>I</span><span><span><span><span><span><span><span>struct</span></span></span></span><span></span></span></span></span></span><span>=</span></span><span><span>−</span><span>log</span><span>(</span><span>1</span><span>−</span></span><span><span>ηD</span><span>)</span></span></span></span></span></p> <p>where <span><span>DD</span><span><span><span>D</span></span></span></span> is structural difference and <span><span>η\eta</span><span><span><span>η</span></span></span></span> is a scaling parameter.</p> <p>This mapping captures the irreversible stabilization of difference into persistent informational structure. As <span><span>D→1D \to 1</span><span><span><span>D</span><span>→</span></span><span><span>1</span></span></span></span>, the divergence reflects the saturation of distinguishability and asymptotic fixation of information.</p> <p>A key conceptual shift introduced by SDI is:</p> <blockquote> <p>Information is not stored.<br>It is stabilized structural difference that survives observation.</p> </blockquote> <p>The framework establishes a closed structure consisting of:</p> <ol> <li>Definition (difference)</li> <li>Observation / fixation (mapping)</li> <li>Distinction from noise (persistence under fluctuation)</li> <li>Persistence condition (<span><span>dIstruct/ds>0dI_{\mathrm{struct}}/ds > 0</span><span><span><span>d</span><span><span>I</span><span><span><span><span><span><span><span>struct</span></span></span></span><span></span></span></span></span></span><span>/</span><span>d</span><span>s</span><span>></span></span><span><span>0</span></span></span></span>)</li> <li>Conceptual closure</li> </ol> <p>SDI is intentionally minimal and does not modify existing mathematical frameworks such as Shannon information theory. Instead, it provides a structural reinterpretation that is:</p> <ul> <li>conceptually minimal</li> <li>internally consistent</li> <li>structurally closed</li> <li>directly testable in principle</li> </ul> <p>This work provides a unified perspective in which information is understood as a persistent structural phenomenon rather than a stored quantity.</p>
title Structural Differentiation Information (SDI) v1.0: A Minimal and Falsifiable Structural Theory of Information
topic information theory structural differentiation information emergence structural information irreversibility observation persistence noise vs information minimal theory falsifiable framework complex systems nonlocal structure SDI
url https://doi.org/10.5281/zenodo.19402293