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ZENODO
Preprint . 2026
License: CC BY NC
Data sources: ZENODO
ZENODO
Preprint . 2026
License: CC BY NC
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY NC
Data sources: Datacite
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Temporal Dynamics of Distinguishability Collapse: On the Breakdown of the Schwartau Inequality under Generative AI

Authors: ROUXEL, Franck;

Temporal Dynamics of Distinguishability Collapse: On the Breakdown of the Schwartau Inequality under Generative AI

Abstract

This paper establishes the Temporal Information Collapse Theorem (Theorem 4.X), the dynamic counterpart of the Distinguishability Collapse Theorem [Rouxel 2026]. Under compression of adversary adaptation tempo below the structural floor of defender observation tempo, mutual information between the sampled trajectory and adversary intent, conditional on the confusable class, is bounded by the bilateral density ratio of the Dual-Use Trajectory Realizability Hypothesis. In the strong-collapse regime the bound vanishes; in the prior-dominated regime it reduces to the Axelsson base-rate bound. By the Data Processing Inequality, this impossibility is architecture-invariant: no sample-based detector — reconstructive or otherwise — recovers intent information from a collapsed channel. Two sampling-theoretic mechanisms realize the collapse: aliasing (Nyquist-Shannon violation) and sub-resolution (Slepian-Pollak-Landau dimensionality). A complementary Wienerian statistical floor (Theorem 5.0) bounds observation tempo from below, closing the viable observation window under sustained genAI compression. Schwartau's P_t > D_t + R_t inequality is shown to be a special case of the detectability condition, structurally unsatisfiable in the collapse regime. Paper 2 of the Distinguishability Collapse Theorem series.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average