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gift-framework/README.md

Geometric Information Field Theory

A theoretical physics framework that derives Standard Model constants from the topology of an E8xE8 compactification on a G2-holonomy 7-manifold.

33 dimensionless predictions from fixed topological structure. No free parameters.


Repositories

Repository Description
core Lean 4 formalization - 146 files, 455+ certified relations, 0 incomplete proofs. Also hosts giftpy (PyPI).
GIFT Publications, documentation, and statistical validation code for the framework (v3.3).

Follow

giftheory.substack.com Essays on topology, physics, and the research process
@GIFTheory Automated facts from the framework, twice a week

Published Papers

Key Results

The framework proposes that the 19+ free parameters of the Standard Model may be derivable from topological invariants of a compact 7-manifold K7 with G2 holonomy (b2 = 21, b3 = 77) and gauge group E8xE8 (dim = 496).

  • 33 dimensionless observables derived from topology, 0.24% mean deviation from experiment (PDG 2024 / NuFIT 6.0)
  • Exhaustive search over 3,070,396 topological configurations confirms statistical significance
  • 169-parameter analytical G2 metric on the full TCS manifold, certified via Newton-Kantorovich (h = 6.65e-8)
  • Lean 4 formalization with modular certificate: Foundations (26), Predictions (48), Spectral (27) conjuncts

Citations

  • Heyes, Hirst, Sa Earp, Silva -- Neural G2 metrics (arXiv: 2602.12438), Imperial College London / UNICAMP
  • Mamun -- The Void Paradox: Towards a Universal Coordinate System for Information Reality (2026), University of Oxford

Resources


GIFT FROM BIT


Pinned Loading

  1. GIFT GIFT Public

    Geometric Information Field Theory. 33 SM predictions from pure topology. 0.24% mean deviation. Zero free parameters. open source, Lean 4 verified, falsifiable.

    Jupyter Notebook 2

  2. core core Public

    GIFT Core: Certified mathematical identities from E8×E8 gauge theory on G2 manifolds. Verified in Lean 4

    Lean 2

  3. PhysLean PhysLean Public

    Forked from leanprover-community/physlib

    A project to digitalise results from physics into Lean.

    Lean