FCD-CORE-1: Frame Constraints and the Limits of Totalization

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Authors: Geoffrey Marcellin
Cited by: 0

Abstract

This paper introduces a structural framework for analyzing the limits of observation, control, and prediction in systems operating under finite constraints. Rather than proposing a new domain-specific theory, it formalizes a minimal operational setting (“frame”) defined by finite informational access, local interaction, constrained feedback, and non-isomorphic scale representations. Within this setting, the paper identifies a structural invariant: complete observability, complete controllability, complete predictability across scales, and finite resource usage cannot be simultaneously achieved. From this invariant, a weak but falsifiable theorem is derived. It shows that attempts at global stabilization or total unification under finite resources necessarily induce loss of fine-scale accessibility, cross-scale instability, or long-range correlations. Local success may be achieved, but joint multi-scale closure cannot, in general, be maintained. The paper further introduces a set of effective (non-fundamental) laws describing how these constraints manifest dynamically, including scale-invariant temporal structure, heavy-tailed fluctuations, regime transitions under saturation, and weak universality of form across non-isomorphic systems. The framework is tested on controlled model systems and a blind real-world time series using an identical, a priori analysis pipeline. The results support the claim that these structural signatures arise from frame constraints rather than from system-specific dynamics. This work does not introduce new physical constants or forces. It provides a structural explanation for recurring limits observed across physics, computation, control, and complex systems, and reframes them as expected consequences of finite operational access. Part of the Frame-Constrained Dynamics (FCD-CORE) framework.

Fields of Study & Subjects

Complex Systems and Dynamics Complex Systems and Time Series Analysis Advanced Thermodynamics and Statistical Mechanics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 April 2026
Language
EN