There is a newer version of the record available.

Published July 26, 2025 | Version 1.0

COSMIC Framework: An Information-Theoretic Approach to Grand Unification

Description

We propose the COSMIC (Computational Optimization of Spacetime through Mathematical Intelligence and Constants) Framework, a comprehensive theoretical approach that unifies all fundamental forces, quantum mechanics, and general relativity through information-theoretic principles. The framework is grounded in claimed empirical observations of mathematical constant evolution across WMAP frequency bands, where π exhibits systematic variation from -0.68σ to +0.21σ with correlation r=0.91 across the 23-94 GHz range. We present four interconnected theoretical components: Pattern-Emergent Gravity (PEG), Universal Information Processing, TransPlanck Dynamics, and Adaptive Quantization, with natural force unification through mathematical constant field optimization. If validated, this framework suggests the universe operates as a computational system optimizing mathematical efficiency, with all forces and quantization emerging from information processing rather than being fundamental. The theory makes specific experimental predictions for information-gravity coupling, mathematical constant physics, and force unification, potentially resolving major physics problems, including the hierarchy problem, fine-tuning, black hole information paradox, and consciousness-expansion connection. This work represents a complete Theory of Everything requiring extensive experimental validation and peer review.

Files

COSMIC Framework-An Information-Theoretic Approach to Grand Unification.pdf

Files (331.5 kB)

Additional details

Related works

Continues
Publication: 10.5281/zenodo.15845342 (DOI)
Publication: 10.5281/zenodo.16261539 (DOI)
Publication: 10.5281/ZENODO.16376120 (DOI)

Dates

Submitted
2025-07-26
Copyright © 2025 Michael Kevin Baines (ORCID: 0009-0001-8084-3870). This work is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). You are free to share and adapt this material for any purpose, including commercially, provided you give appropriate credit, provide a link to the license, and indicate if changes were made. License: https://creativecommons.org/licenses/by/4.0/