Theoretical framework establishes limits on structural recovery in latent systems, indicating critical foundational insights.
Structural Information Capacity of Latent Systems (SICLS) is a theoretical framework that establishes fundamental limits on the distinguishability of latent structures under constrained probing and intervention. The framework introduces Structural Information Capacity as a quantitative bound on the number of latent structural states that can be uniquely inferred through a given epistemic channel. SICLS shows that when latent structural complexity exceeds this capacity, unique structural recovery becomes information-theoretically impossible regardless of data volume, computational power, or estimator class. The theory extends classical information-theoretic and probe-constrained inference limits by introducing structural distinguishability as a capacity-limited epistemic resource and predicts phase-transition behavior in structural identifiability as probe and intervention diversity increases. Related resourcesAdditional preprints, theoretical frameworks, and ongoing work by the author are available at:https://murad-ahmadov.github.io/
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Murad Ahmadov (2026) studied this question.
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