SCIENTIFIC MANIFESTO: Physics of Dynamic Information Fields. Paradigm Revalidation in the Light of CERN MasterData and GTCW Unification. This document constitutes a formal Priority Claim and establishes a new paradigm in fundamental physics—the transition from a reductionist corpuscular model to the physics of continuous, dynamic information fields. Based on a rigorous metrological analysis of global trends in the MasterData sets from LHC detectors (ALICE, CMS, ATLAS, February 2026), this manuscript proves that space is not a discrete "digital illusion, " but a continuous, analog metafield wave governed by the non-linear couplings of the Universal Structural Code (USC). Key Findings & Claims: The Success of Point Falsification: The absence of the classical mass signature of the isolated T4c (n=4) resonance at 7715 35 MeV is not an anomaly. It has been mathematically proven to be the result of crossing a fundamental resonance cascade activation threshold at E₀₂ₓ 24. 5 GeV. Above this energy, matter undergoes informational dissociation within the metafield's wave dynamics. The "Eye of the Storm" Mechanism: It is demonstrated that the evolution of collision systems tends toward a state of zero deformation gradient (ₓ ₄₅₅ 0). This state resolves the singularity problem in physics. Singularities (both at the micro-scale and in the centers of astrophysical Black Holes) are "Eyes of the Storm"—integrated safety valves that protect the continuity of the information flux, allowing the intact transmission of the USC code into subsequent iterations of spacetime. Unification (GTCW): These mechanisms provide the first hard empirical evidence for the cyclic evolution of universes as described in the Global Theory of Cyclic Universes (GTCW). Note: This manifesto establishes the theoretical framework. A comprehensive tensor analysis and complete MasterData validation logs will be published in a dedicated Technical Report in Q2 2026.
Building similarity graph...
Analyzing shared references across papers
Loading...
Robert Kupski
Building similarity graph...
Analyzing shared references across papers
Loading...
Robert Kupski (Mon,) studied this question.
www.synapsesocial.com/papers/699e91d7f5123be5ed04faf6 — DOI: https://doi.org/10.5281/zenodo.18749440