The Information-Geometric Structural Debt Framework (IGSDF v30): Emergent Spacetime and Mass from Unitary Quantum Registers

This repository presents the Unified Information-Geometric Structural Debt Framework (IGSDF) Version 30, a novel theoretical and computational approach to the unification of quantum mechanics, gravity, and information theory. Unlike traditional models that treat physical constants as inherent, IGSDF v30 demonstrates how fundamental phenomena emerge naturally from the unitary evolution of a 6-dimensional quantum register embedded in an SU(3) algebraic structure.

Key Scientific Contributions:

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  Rest Mass as Information: Introduces the "tethered pixel" model, where rest mass emerges as a proxy for persistent temporal asymmetry trapped within the register’s internal clock variance, consistent with the de Broglie relation.

   

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  Information-Geometric Spacetime: Derives spacetime curvature and a position-dependent Variable Speed of Light (VSL) directly from complexity-dependent warping of the Fisher-Rao information metric.

   

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  The Arrow of Time: Proposes the 3/2 Coordination Law as a microscopic origin for the second law of thermodynamics, where the irreversible computational cost of system restoration defines the temporal gradient.

   

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  Dark Matter Alternative: Resolves the flatness of galactic rotation curves through purely geometric lattice tension, eliminating the requirement for particulate dark matter while remaining consistent with baryonic mass observations.

   

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  Quantum-to-Classical Transition: Identifies a sharp 48-bit relational cut (coherence threshold) where coherent phase information "snaps" into classical domains.

   

Falsifiability and Data: The framework provides specific, testable predictions, including measurable VSL effects near compact objects and power-law deviations in galactic rotation curves at large radii.

Included in this Zenodo record are:

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   The Comprehensive Preprint/Thesis Chapter: Detailing all operator definitions and theoretical derivations.

    

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   Computational Laboratory (Python): High-resolution numerical simulations (NumPy/SciPy) that reproduce every quantitative claim and figure presented in the paper to machine precision.

    

We invite researchers in information geometry, quantum gravity, and astrophysics to scrutinize and extend these results using the provided reproducible computational environment.