Skip to content
This repository was archived by the owner on Jul 7, 2026. It is now read-only.

README_OLD.md

Latest commit

 

History

History
225 lines (173 loc) · 6.61 KB

README_OLD.md

File metadata and controls

225 lines (173 loc) · 6.61 KB
Raw

SSZ Schumann Experiment

Segmented Spacetime (SSZ) Analysis of Schumann Resonances

Tests Python License

A Python package for testing the Segmented Spacetime (SSZ) theory using Earth-based Schumann resonance measurements.

Documentation

Overview

This project applies the SSZ framework to Schumann resonances - electromagnetic resonances in the Earth-ionosphere cavity. The key SSZ prediction is that spacetime segmentation introduces a uniform relative frequency shift across all resonance modes, distinct from classical dispersive effects.

Physical Background

Classical Schumann Resonances:

f_n = η × c / (2πR) × √(n(n+1))

where:

  • n = mode number (1, 2, 3, ...)
  • η ≈ 0.74 = effective slowdown factor (due to finite conductivity)
  • c = speed of light
  • R = Earth radius

SSZ Modification:

f_n_SSZ = f_n_classical / D_SSZ
D_SSZ = 1 + δ_seg(t)

The SSZ signature is that δ_seg(t) produces the same relative shift for all modes:

Δf_n / f_n ≈ -δ_seg(t)  for all n

This is testable: if the relative frequency shifts are consistent across modes and correlate with ionospheric conditions, it supports the SSZ hypothesis.

Installation

# Clone the repository
git clone https://github.com/error-wtf/ssz-schuhman-experiment.git
cd ssz-schuhman-experiment

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # Linux/Mac
# or: .venv\Scripts\activate  # Windows

# Install dependencies
pip install -r requirements.txt

# Install package in development mode
pip install -e .

Quick Start

1. Run with Synthetic Data

python scripts/run_schumann_ssz_analysis.py --synthetic

This creates synthetic Schumann data with a known SSZ signature and demonstrates that the analysis pipeline can recover it.

2. Fetch Real Data

python scripts/fetch_data.py --all

This creates info files with instructions for downloading:

  • Schumann data from Zenodo (Sierra Nevada ELF station)
  • F10.7 solar flux from NOAA
  • Kp/Ap indices from GFZ Potsdam

3. Run Analysis on Real Data

python scripts/run_schumann_ssz_analysis.py \
    --schumann-path data/schumann/2016/data.csv \
    --f107-path data/space_weather/f107_noaa.csv \
    --kp-path data/space_weather/kp_ap.csv

Project Structure

ssz-schuhman-experiment/
├── ssz_schumann/              # Main package
│   ├── config.py              # Configuration and constants
│   ├── data_io/               # Data loading modules
│   │   ├── schumann_sierra_nevada.py
│   │   ├── schumann_real.py
│   │   ├── space_weather_noaa.py
│   │   ├── lightning_wwlln.py
│   │   └── merge.py
│   ├── models/                # Physical models
│   │   ├── classical_schumann.py
│   │   ├── ssz_correction.py
│   │   ├── layered_ssz.py
│   │   ├── maxwell_schumann.py
│   │   ├── physical_ssz.py
│   │   └── fit_wrappers.py
│   └── analysis/              # Analysis pipeline
│       ├── compute_deltas.py
│       ├── correlation_plots.py
│       ├── regression_models.py
│       ├── spectral_coherence.py
│       ├── model_comparison.py
│       └── model_fits.py
├── tests/                     # Unit tests (94 tests)
├── scripts/                   # CLI scripts
│   ├── run_complete_analysis.py
│   ├── run_full_validation.py
│   ├── run_sensitivity_scan.py
│   └── fetch_zenodo_schumann.py
├── docs/                      # Documentation
└── output/                    # Analysis output

Data Sources

Schumann Resonance Data

  • Source: Sierra Nevada ELF Station (Salinas et al., 2022)
  • DOI: 10.5281/zenodo.6348930
  • Period: March 2013 - February 2017
  • Resolution: 10-minute intervals
  • Parameters: f1, f2, f3 (frequencies), widths, amplitudes

Space Weather Data

  • F10.7 Solar Flux: NOAA SWPC
  • Kp/Ap Index: GFZ Potsdam

Key Results

The analysis produces:

  1. Mode Consistency Score: Measures how well δ_seg is consistent across modes

    • Score > 0.7: Strong SSZ signature
    • Score < 0.3: No SSZ signature detected

  2. Model Comparison: Classical vs. SSZ model

    • ΔR²: Improvement in explained variance
    • ΔAIC/BIC: Information criteria comparison

  3. Correlation Analysis: δ_seg vs. ionospheric proxies

    • F10.7 (solar activity)
    • Kp (geomagnetic activity)

Running Tests

# Run all tests (94 tests)
pytest tests/ -v

# Run full validation suite
python scripts/run_full_validation.py

# Run complete analysis with synthetic data
python scripts/run_complete_analysis.py --synthetic --delta-seg-amp 0.03

# Run sensitivity scan
python scripts/run_sensitivity_scan.py --amplitudes 0.0 0.01 0.02 0.05 --plot

Validation Results

Phase Status
Unit Tests 94 passed
Synthetic Validation PASS
Model Comparison PASS
Physical Model PASS
Sensitivity Analysis PASS

Model Comparison (Synthetic Data with 2% SSZ Signal)

Metric Classical SSZ
RMSE 1.05 Hz 0.44 Hz
R² 0.96 0.99
AIC 20298 7103
BIC 20305 7129

Delta BIC: +13176 -> Very strong evidence for SSZ model

References

SSZ Theory

Schumann Resonances

  • Schumann, W.O. (1952). Über die strahlungslosen Eigenschwingungen einer leitenden Kugel, die von einer Luftschicht und einer Ionosphärenhülle umgeben ist. Z. Naturforsch., 7a, 149-154.
  • Salinas, A. et al. (2022). Schumann resonance data processing programs and four-year measurements from Sierra Nevada ELF station. Computers & Geosciences, 165, 105148.

License

Anti-Capitalist Software License v1.4

© 2025 Carmen Wrede & Lino Casu