Replication Protocol for Testing the Information-Causal Unified Framework (ICUF):
Year: 2025
Type: article
Abstract: This paper provides a detailed protocol for AI systems to replicate simulations testingthe Information-Causal Unified Framework (ICUF), a quantum-gravitational model inte-grating the Unified Data Framework (UDF v5.2) and Entangled Causal Network Theory(ECNT). ICUF posits a quantum information network as reality’s foundation, with a totalprobability functional Ω[Λ] and scale-dependent actions. We outline a maximal-capacity sim-ulation—pushing event counts, grid resolution, and signal bins to computational limits—toevaluate ICUF’s predictions (e.g., power-law spectra, gravitational wave dispersion), robust-ness, and simulation-detection capabilities. Parameters, algorithms, and failure points arespecified for replication by other AI, with developer notifications for scaling beyond currentlimits.
Author: Sambey, Stanley Everett
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893257898
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