Quantum Astronomical Fusion

Author: Dharun Ramesh
License: Creative Commons Attribution 4.0 International (CC BY 4.0)

This repository contains the full implementation of our Quantum-Enhanced Fusion Model, which combines classical MLP and LSTM-based time series models with quantum circuit fusion layers. The model is applied to the PLAsTiCC Astronomical Classification dataset for celestial object classification.

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🚀 Features

✔️ Hybrid Model Fusion: MLP for metadata + LSTM for time-series + Quantum circuits for feature enhancement
✔️ Benchmarking Against Baselines: Compared against classical MLP and LSTM-only models
✔️ Astronomical Dataset Application: Uses PLAsTiCC dataset to classify celestial objects
✔️ Fully Open Source & Reproducible

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📊 Results & Ablation Study

Accuracy Comparison

Inference Time vs. Accuracy

📌 Key Takeaway: The fused model achieves superior accuracy with a minimal inference-time tradeoff.

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📌 Citation

If you use this work, please cite it as follows:

@software{ramesh2025quantumfusion,
  author = {Dharun Ramesh},
  title = {Quantum Astronomical Fusion},
  year = {2025},
  version = {1.0.0},
  url = {https://github.com/dr1810/Quantum_Astronomical_Fusion},
  license = {CC-BY-4.0}
}