XPAI is an Artificial Intelligence project designed to analyze X-ray polarimetry data, inspired by NASA’s IXPE (Imaging X-ray Polarimetry Explorer) mission. Its goal is to make astrophysical research and visualization more accessible through open-source tools.
🌌 Scientific Context
NASA’s IXPE mission studies the high-energy universe through X-ray observations to explore extreme objects such as:
Black holes
Neutron stars
Pulsars
Supernova remnants
This project replicates some of IXPE’s fundamental concepts, applying Machine Learning to:
Analyze X-ray images
Detect polarization patterns
Simulate datasets and outcomes
🤖 What XPAI Does
Processes and classifies X-ray polarimetry data
Trains Deep Learning models for automated analysis
Generates interactive data visualizations
Runs entirely on Google Colab (no local setup required)
🚀 Tech Stack
Python (NumPy, Matplotlib, Pandas)
TensorFlow / PyTorch (neural network training)
Astropy (astronomy utilities)
Google Colab (cloud execution)
📂 Repository Structure
XPAI/ ├── notebooks/ # Analysis and training notebooks ├── data/ # Sample datasets ├── models/ # Pre-trained models ├── utils/ # Helper functions └── README.md # Documentation
🧠 Next Steps
Improve model accuracy using real IXPE datasets
Implement a simple graphical interface
Publish scientific findings derived from this tool