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https://github.com/agora-lab-ai/stellarnet

An AI system probing the possibility that stars may possess primitive forms of information processing. By analyzing complex patterns in stellar emissions using deep learning, we search for signatures of self-organization and structured behavior that transcend random processes.
https://github.com/agora-lab-ai/stellarnet

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An AI system probing the possibility that stars may possess primitive forms of information processing. By analyzing complex patterns in stellar emissions using deep learning, we search for signatures of self-organization and structured behavior that transcend random processes.

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README 

        

# StellarNet 🌟



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[![PyTorch](https://img.shields.io/badge/PyTorch-2.0+-orange.svg)](https://pytorch.org/)

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[![arXiv](https://img.shields.io/badge/arXiv-2024.xxxxx-b31b1b.svg)](https://arxiv.org/)



StellarNet: An AI system probing the possibility that stars may possess primitive forms of information processing. By analyzing complex patterns in stellar emissions using deep learning, we search for signatures of self-organization and structured behavior that transcend random processes.



## Overview



This project implements a comprehensive analysis pipeline for investigating potential "consciousness-like" patterns in stellar data using PyTorch and astronomical data from TESS and Kepler missions.



## Features



- 🔬 Real-time analysis of stellar light curves from TESS/Kepler missions

- 🧠 LSTM-based pattern detection for stellar behavior prediction

- 📊 Comprehensive entropy and frequency analysis

- 🔍 Anomaly detection in stellar emissions

- 📈 Advanced visualization of stellar patterns



## Installation



```bash

# Clone the repository

git clone https://github.com/Agora-Lab-AI/StellarNet.git

cd StellarNet



# Create and activate a virtual environment (optional but recommended)

python -m venv venv

source venv/bin/activate  # On Windows, use `venv\Scripts\activate`



# Install dependencies

pip install -r requirements.txt

```



## Quick Start



```bash

python main.py

```



By default, the script analyzes a set of pre-selected variable stars. To analyze specific stars:



```bash

python main.py --star_id "TIC 260128333" --mission "TESS"

```



## Requirements



- Python 3.10+

- PyTorch

- lightkurve

- astropy

- numpy

- pandas

- scipy

- scikit-learn

- matplotlib



See `requirements.txt` for complete list.



## Methodology



Our analysis pipeline consists of several key components:



1. **Data Collection**: Automated fetching of stellar light curves from TESS/Kepler missions

2. **Preprocessing**: Cleaning and normalization of time-series data

3. **Pattern Analysis**:

   - Shannon entropy calculation

   - Fourier analysis

   - LSTM-based pattern prediction

   - Anomaly detection

4. **Visualization**: Comprehensive plotting of results



## Results



Analysis results are saved in the `results/` directory with the following structure:

- `{star_id}_analysis.npz`: Numerical results and statistics

- `{star_id}_plots.png`: Visualization plots

- `models/{star_id}_model.pt`: Trained LSTM model



## Contributing



We welcome contributions! Please see our [Contributing Guidelines](CONTRIBUTING.md) for details.



1. Fork the repository

2. Create a feature branch

3. Commit your changes

4. Push to the branch

5. Open a Pull Request



## Citation



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



```bibtex

@article{stellarnet2024,

  title={StellarNet: Investigating Information Processing Patterns in Stellar Emissions},

  author={Agora Lab AI, Kye Gomez},

  journal={arXiv preprint arXiv:2024.xxxxx},

  year={2024}

}

```



## License



This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.



## Acknowledgments



- NASA's TESS and Kepler missions for providing stellar data

- The lightkurve team for their excellent data access tools

- The astropy community for their comprehensive astronomy tools



## Contact



- **Website**: [https://agoralab.ai](https://agoralab.ai)

- **Issues**: [GitHub Issues](https://github.com/Agora-Lab-AI/StellarNet/issues)

- Twitter: [@kyegomez](https://twitter.com/kyegomez)

- Email: [email protected]



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## Want Real-Time Assistance?



[Book a call with here for real-time assistance:](https://cal.com/swarms/swarms-onboarding-session)



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