Grid Analyses — Three Falsifiable Predictions

Methodology

This research package contains three complete analysis pipelines for the strongest testable predictions of the sub-quantum grid model. Each pipeline is executable against existing public data — no new experiment needs to be set up.

All scripts run on Python 3.8+ with numpy, matplotlib, and scipy.

Prediction #17 — Helix Stability Threshold in Pair Production

Layer 1+3 #pair-production#qed#cern-open-data#directly-testable

Core hypothesis

Pair production (γ → e⁺e⁻) shows resonance peaks at harmonics of 2 m_e c² = 1.022 MeV. The peaks have a Breit-Wigner profile and decay as 1/n² with harmonic number n.

Why this is the sharpest test

QED predicts the pair-production cross-section to 8+ decimal places of accuracy. Any deviation, however small, would be a fundamental discovery. Moreover: the resonance peaks at harmonics are a unique prediction of the grid model — no other framework predicts peaks at exactly these energies.

Required data

• Pair-production cross-section measurements near threshold (1–10 MeV)
• CERN Open Data: LEP / OPAL / DELPHI datasets
• HEPData: published cross-section tables
• Ideally: high-resolution energy scans (ΔE < 0.05 MeV)

Required statistics

Generated plot

Prediction #15 — Planck-Scale Anisotropy

Layer 1+3 #fermi-lat#lorentz-invariance#grid-geometry#directly-testable

Core hypothesis

The grid is a discrete lattice. Photons at different energies propagate at slightly different speeds: v(E) = c × [1 ± η × (E/E_Planck)^n]. Over cosmological distances this leads to measurable arrival-time differences in gamma-ray bursts.

Current constraints (critical context)

Fermi-LAT has already partially tested this hypothesis. Result (Abdo et al. 2009, Nature 462, 331, GRB 090510):

E_QG > 1.2 × E_Planck for linear LIV (n=1)

This rules out cubic grid geometry (η ~ 1). But hexagonal (η ~ 0.3), FCC (η ~ 0.1), and amorphous (η ~ 0.01) geometries survive.

What this means for the grid model

The grid is not cubic. The most likely scenarios:

• Hexagonal (η ≈ 0.3): energetically most stable 2D lattice; explains the prevalence of hexagons in nature
• FCC (η ≈ 0.1): most stable 3D structure (gold, aluminum)
• Amorphous (η → 0): no preferred direction, near-isotropic

Key GRBs

Generated plot

Prediction #18 — Non-Linear Shapiro Delay

Layer 1+3 #nanograv#pulsar-timing#shapiro-delay#future-test

Core hypothesis

Mass locally densifies the grid → c decreases locally → extra delay above standard general-relativistic Shapiro delay. The correction is non-linear:

Δt_grid = Δt_GR × [1 + β × (GM/Rc²)^α]   with α > 1

Current status

At present timing precision (~5% on Shapiro delay), the signal is not detectable at β = 0.01, α = 2. The grid correction at the Double Pulsar (compactness 0.18) is only ~0.03% — well below current measurement error.

When detectable?

Strongest test objects

PSR J0737−3039A (Double Pulsar): compactness 0.18, most precise Shapiro measurement. Hulse-Taylor (B1913+16): compactness 0.20, but harder to measure (low inclination).

Generated plot

Timeline summary

2026 (NOW):
  ├── #17: Re-analyse CERN data for resonance peaks
  │       → Download HEPData cross-sections
  │       → Run prediction17_pair_production.py with real data
  │       → Result within weeks
  │
  └── #15: Re-analyse Fermi-LAT GRB data
          → Download 2GBM catalog
          → Fit hexagonal grid model (η=0.3)
          → Result within months

2028–2032 (SKA):
  └── #18: Wait for SKA Phase 1 / Full
          → Monitor Double Pulsar
          → Test non-linear Shapiro correction
          → Result ~2032

Conclusion: #17 is currently the most readily falsifiable. #15 constrains grid geometry from existing data. #18 is a future test that validates the grid-density model for gravity.

Source code

All five Python scripts are published openly:

• prediction17_pair_production.py — Breit-Wigner peak detection in cross-section residuals
• prediction17_real_data.py — same pipeline, against real HEPData input
• prediction17_real_data_v2.py — refined v2
• prediction15_fermi_lat.py — Fermi-LAT GRB photon arrival-time analysis
• prediction18_pulsar_timing.py — non-linear Shapiro delay forecast

Dependencies: numpy, matplotlib, scipy — install with pip install numpy matplotlib scipy.

Citation

Bes, M. (2026). Sub-quantum Grid Model — Testable Predictions. The Spectrum of Everything. https://spectrumofeverything.com/research/grid-analyses/

A note to working researchers

If you have access to CERN HEPData cross-section tables, the Fermi-LAT 2GBM catalog, or SKA pulsar-timing data and want to run any of these pipelines against real data, please reach out: marald@gmail.com. The scripts are designed to be replaced at the data-loading stage; the analysis pipeline downstream is unchanged.

Last updated: May 4, 2026