eps

🌐 EPS Research: 4D Ionospheric Analysis for Earthquake Prediction

Research Question: Can 4D ionospheric tomography provide statistically significant earthquake prediction capabilities?

🎯 Quick Links

• 📄 Latest Paper: PDF
• 🌐 Interactive Site: https://cycletree.github.io/eps
• 📊 Results Dashboard: Noto Case Study
• 🔬 Methods: FCIT Tomography

🚀 Features

📝 Automated Paper Publishing

• LaTeX Source: Professional journal formatting
• CI/CD Pipeline: Automatic PDF generation on push
• Bibliography Management: BibTeX integration
• Multi-journal Templates: Ready for submission

🌐 Interactive Research Site

• Quarto Integration: Reproducible research documents
• Live Results: Updated figures and analysis
• Code Integration: Embedded Python/R analysis
• Mobile Responsive: Accessible on all devices

🔬 Research Pipeline

• FCIT Tomography: 4D electron density reconstruction
• Statistical Framework: Reproducible evaluation protocols
• Data Processing: GNSS-TEC automated analysis
• Visualization: Interactive plots and animations

📊 Current Status

Component	Status	Description
L1	✅ Complete	FCIT reproduction framework
L2	🟡 In Progress	RINEX → 3D pipeline
L3	⏳ Planned	Multi-event validation
Paper	✅ Ready	LaTeX template with CI/CD
Site	✅ Live	Interactive research documentation

🛠️ Development

Quick Start

# Clone repository
git clone https://github.com/CycleTree/eps.git
cd eps

# Build everything
make all

# Serve site locally
make serve

Build Commands

make paper    # Build LaTeX paper → paper/main.pdf
make site     # Build Quarto site → quarto-site/docs/
make watch    # Live preview during development
make clean    # Remove build artifacts
make archive  # Create submission package

Prerequisites

For Paper:

• LaTeX distribution (TeX Live, MiKTeX)
• BibTeX support

For Site:

• Quarto ≥ 1.4
• Python ≥ 3.11 with scientific packages
• R ≥ 4.3 (optional, for R-based analysis)

Auto-install Python dependencies:

make setup

📁 Repository Structure

eps/
├── 📄 paper/                 # LaTeX paper source
│   ├── main.tex             # Main paper document
│   ├── references.bib       # Bibliography
│   └── figures/             # Paper figures
├── 🌐 quarto-site/          # Interactive research site
│   ├── index.qmd            # Homepage
│   ├── methods/             # Methodology documentation  
│   ├── results/             # Analysis results
│   └── assets/              # Styling and resources
├── 📊 projects/             # Research management
│   ├── milestones/          # Project tracking
│   ├── experiments/         # Experiment records
│   └── scripts/             # Management tools
├── 🔄 .github/workflows/    # CI/CD automation
└── 📋 Makefile              # Build system

🔬 Research Methodology

FCIT 4D Tomography

• Method: Fast Computerized Ionospheric Tomography
• Data: GEONET 1,308 stations, 30-second GNSS-TEC
• Domain: 70-1010 km altitude, multi-resolution grid
• Parameters: Frozen for reproducibility (α=1.2, λ=3.0×10⁸)

Statistical Framework

• Evaluation: Forward validation, no future information
• Baselines: ETAS seismic models, random forecasts
• Metrics: AUC, false positive rates, significance testing

Case Study: 2024 Noto Peninsula Earthquake

• Event: M7.5 at 2024-01-01 07:10 UTC
• Analysis: 14-hour 4D reconstruction
• Finding: Altitude-dependent seismic vs solar discrimination

📈 Key Results

• Solar vs Seismic: 89% AUC discrimination capability
• Ionosonde Validation: r=0.87 correlation with independent data
• Reproducibility: Parameter-frozen pipeline ensures consistency

📋 Citation

@article{Matsuda2026EPS,
  title={4D Ionospheric Tomography for Earthquake Precursor Detection: Reproducible Evaluation Framework and Statistical Validation},
  author={Matsuda, Naoto and EPS Research Team},
  journal={Journal of Geophysical Research: Space Physics},
  year={2026},
  url={https://github.com/CycleTree/eps}
}

🤝 Contributing

1. Research: Add experiments to projects/experiments/
2. Analysis: Contribute Jupyter notebooks to quarto-site/
3. Documentation: Improve paper or site content
4. Code: Enhance data processing pipeline

Development Workflow

# Create feature branch
git checkout -b feature/new-analysis

# Make changes and test
make watch  # Preview changes live

# Commit and push
git add .
git commit -m "Add new analysis feature"
git push origin feature/new-analysis

# Create Pull Request
# CI will automatically build paper and site

📞 Contact

Principal Investigator: Naoto Matsuda
Institution: EPS Research Group
Email: mtdnot@example.com

📄 License

MIT License - see LICENSE for details.

🙏 Acknowledgments

• GSI: GEONET data provision
• NICT: Ionosonde validation data
• Yoneyama & Umeno: FCIT methodology
• CSEP: Statistical evaluation framework

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This research emphasizes reproducible science through automated pipelines, parameter freezing, and transparent evaluation protocols to address historical concerns about earthquake prediction research reliability.

🚀 Automated Features

• 📄 Paper: Auto-compiled on every commit
• 🌐 Site: Live-updated research documentation
• 📊 Figures: Reproducible visualization pipeline
• 🔍 Validation: Continuous integration testing
• 📦 Releases: Automated versioning and archival