Classification of Stars Based on Stellar Spectra

This project focuses on classifying stars based on their stellar spectra and visualizing their placement on the Hertzsprung–Russell (HR) diagram.

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Project Overview

• Data is obtained from the Sloan Digital Sky Survey (SDSS).
• Unknown stars are sorted into spectral classes (O, B, A, F, G, K, M) using spectral features.
• A set of known stars is then taken for reference using a simple Python script.
• Finally, the stars are plotted on the HR diagram to show their relationship between luminosity and temperature.

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Workflow

1. Fetch data

   • Download stellar spectra data from SDSS.

2. Classify stars

   • Sort unknown stars into spectral classes.
   • Cross-check with known star data.

3. Analyze with Python

   • Use a Python script to select known stars.
   • Generate and visualize the HR diagram.

4. Document findings

   • Full explanation and analysis written in LaTeX.
   • Final compiled PDF report available in the repo.

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Example: HR Diagram

Features

• Stellar classification using spectral analysis
• Clean HR diagram visualization
• Full LaTeX report for academic use
• Reproducible workflow with Python + SDSS data

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Acknowledgements

• SDSS Collaboration – for stellar spectra data
• Python & Matplotlib – for data analysis and visualization
• LaTeX – for professional scientific documentation