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v0.1.0 - Initial Release

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@imediacorp imediacorp released this 30 Dec 17:16
v0.1.0
37836a6

Release v0.1.0 - Initial Release

Release Date: January 2025

Overview

This is the initial release of the FaCC (Fibonacci Cosmology) repository, introducing a scientifically defensible framework for testing φ-modulation as an empirical pattern in cosmic structure.

Key Features

Core Analysis Framework

  • PhiModulationModel Class: A comprehensive Python class implementing φ-modulated power spectrum analysis within the ΛCDM framework
    • CAMB integration for generating physically accurate ΛCDM power spectra
    • Log-periodic modulation: P(k) = P_ΛCDM(k) × [1 + A_φ × cos(2π × log(k/k_pivot) / ln(φ) + φ_0)]
    • BAO signature computation with φ-modulation
    • DESI Year 5 sensitivity forecasts using Fisher matrix analysis

Analysis Tools

  • DESI Forecast Notebook (notebooks/01_desi_forecasts.ipynb): Comprehensive analysis notebook featuring:
    • Power spectrum ratio analysis
    • BAO signature comparison
    • DESI SNR vs amplitude forecasts
    • 4-panel publication-quality figures

Documentation

  • Complete README with usage examples
  • Independence statement (INDEPENDENCE.md) clarifying separation from other projects
  • Comprehensive code documentation
  • Release notes and changelog

Scientific Approach

This release implements a two-parameter extension to ΛCDM (amplitude A_φ and phase φ_0), representing a shift from hypothesis-proving to hypothesis-testing with proper statistical rigor.

Key Scientific Claims:

  • Tests whether the Golden Ratio (φ ≈ 1.618) appears in cosmic structure as an empirical pattern
  • Forecasts suggest DESI Year 5 can detect oscillations with amplitude A_φ ≳ 0.005 at 3σ confidence
  • Model is testable, falsifiable, and respects ΛCDM as the baseline

Installation

pip install -r requirements.txt

Key Dependencies:

  • CAMB (for ΛCDM power spectrum calculations)
  • NumPy, SciPy, Matplotlib, Pandas
  • Astropy
  • Optional: emcee, dynesty, corner (for Bayesian analysis)

Quick Start

from src.phi_modulation import PhiModulationModel

# Initialize model
model = PhiModulationModel()

# Generate power spectrum
k, z, Pk = model.get_base_power_spectrum(k_min=0.01, k_max=0.3)

# Apply φ-modulation
Pk_mod, mod_factor = model.apply_phi_modulation(k, Pk[0], A_phi=0.01)

# Forecast DESI sensitivity
forecast = model.forecast_desi_sensitivity(A_phi_true=0.01)
print(f"Forecast σ_Aφ = {forecast['sigma_Aphi']:.4f}, SNR = {forecast['SNR']:.2f}σ")

Repository

Citation

If you use this code in your research, please cite:

@misc{persaud_fibonacci_cosmology,
  author       = {Bryan David Persaud},
  title        = {Fibonacci Cosmology: Falsified Background, Testable Perturbations},
  year         = {2025},
  howpublished = {GitHub repository},
  url          = {https://github.com/imediacorp/FaCC}
}

Acknowledgments

This work represents independent cosmological research exploring whether the Golden Ratio manifests in cosmic structure formation. It originated as a thought experiment and hypothesis motivated by self-similarity patterns observed from plants to galaxies.

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