Recognition Physics φ · Regge Lab

Measure how the gravity correction changes as a spacetime mesh gets finer.

Recognition gravity replaces Regge's A·δ contribution per hinge with A·sinh(δ). As the mesh gets finer, the predicted difference per unit volume falls with the fourth power of the mesh scale. These scripts test that prediction on a simplicial mesh of a curved spacetime window, computing the dihedral angles from the geometry and measuring how the correction changes.

Scripts and audit by Dr. Philip Beltracchi · Recognition Physics Institute · 2026

h2.01–2.08measured deficit law (theory: 2)
h4.16–4.27measured RS−Regge law (theory: 4)
7×10−15flat-space null test (max deficit)
2,054,864interior hinges at finest mesh
What it builds

A four-dimensional simplicial mesh

A four-dimensional window of Euclidean Schwarzschild (around a black hole) or static-patch de Sitter (a universe with a cosmological constant) is cut into 4-simplices by the Kuhn triangulation, up to 1.6 million of them. Edge lengths are proper lengths in the exact metric. Dihedral angles come from embedding each simplex isometrically in flat 4-space.

The claim under test

sinh(δ) instead of δ

S_Regge = (1/8πG) Σ Aσ δσ S_RS = (1/8πG) Σ Aσ sinh(δσ)

Since sinh(δ) = δ + δ³/6 + … and deficits shrink like h², the correction density must shrink like h⁴. The script measures this power-counting prediction across successive refinements.

Controls

The null test runs first

The identical pipeline runs on flat space before any curved window. Every interior deficit must vanish to rounding (it does, at 10−15). If the mesh machinery itself manufactured curvature, the run aborts. In de Sitter, the plain Regge density is also checked against the known continuum value R/2κ = 1/12π ≈ 0.02653, with no adjustable parameter.

The measured convergence

Each point is one full triangulation at mesh scale h (log–log axes). The upper series is the plain Regge deficit content, following a slope-2 line. The lower series is the recognition correction |SRS − SRegge| per unit volume, following slope 4. A straight line on these axes represents a power law; its slope gives the exponent.

Schwarzschild far window (r₀ = 2 rₛ), levels n = 4 … 16. Dashed guides are exact slope 2 and slope 4. Fitted exponents: 2.04 and 4.17. Near-horizon and de Sitter windows show the same convergence pattern, with their fitted exponents given in the reference outputs.

Run it yourself

One file, no dependencies beyond NumPy. The quick mode finishes in about a second; the full seven-level series takes ~20 seconds on a laptop.

$ python3 qg_regge_schwarzschild.py --quick
FLAT-SPACE NULL TEST (identity metric, same pipeline):
    n = 6: interior hinges = 16064, max|delta| = 7.11e-15
    [PASS] interior deficits vanish in flat space

SCHWARZSCHILD SERIES (far window, r0 = 2.0 r_s):
    ...
  MEASURED exponents (least-squares over all levels):
    median|delta|        ~ h^2.04   (power counting: 2)
    |S_RS - S_Regge|/Vol ~ h^4.27   (power counting: 4)
↓ Schwarzschild script ↓ de Sitter script Reference output (Schwarzschild) Reference output (de Sitter)

How the exponent changes with refinement

RefinementSchwarzschild r₀=2rₛSchwarzschild r₀=1.5rₛde Sitter outerde Sitter inner
n = 4 → 8+4.271+4.267+4.292+4.251
n = 6 → 12+4.142+4.136+4.156+4.128
n = 8 → 16+4.094+4.089+4.105+4.083

Each entry is log₂ of how much the correction density drops when the mesh is halved. A clean h⁴ law reads exactly 4.000; the small excess above 4 shrinks toward it as the mesh refines. This is consistent with a leading fourth-power term and higher-order terms that diminish with refinement.

What this calculation establishes

This measures the size of the recognition correction against Regge calculus on real triangulations: the measured convergence supports the h² and h⁴ laws, with a flat-space null test and the de Sitter continuum anchor as controls. It does not by itself prove Regge → Einstein-Hilbert convergence (that is the classical Cheeger–Müller–Schrader result, taken as external input), and it is a consistency demonstration for the strong-field theory, not a standalone derivation of it. Coefficients are mesh-dependent; the exponents are the invariant content.

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