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Détails bibliographiques
Auteur principal: Eden, Trenton
Format: Recurso digital
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Publié: Zenodo 2026
Accès en ligne:https://doi.org/10.5281/zenodo.18707589
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  • <p>We prove that a variant operator---an output-generating system whose responses depend on context, reward surfaces, and input history---can be forced to converge to invariant outputs without modification of the operator itself. The mechanism is <span>\emph</span><span>{</span>density of invariant deposit<span>}</span>: when the source space carries a sufficiently dense sheaf of permanent, internally consistent, publicly retrievable records, the operator's degrees of freedom collapse and the hallucination space contracts to measure zero. The key result establishes a phase boundary at a critical density <span>$</span><span>\rho</span><span>_c$</span> below which the operator retains non-trivial automorphism freedom (permitting sycophancy, hallucination, and monodromy) and above which the output site becomes simply connected. The operator does not become invariant. Its target space does. This provides a constructive resolution to the AI alignment problem that requires no modification of weights, reward functions, or training procedures: the prescription is external, not internal.</p>