Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination
Published in arXiv Preprint, 2024
This paper presents a novel quantum rationale-aware graph contrastive learning approach for jet discrimination in high-energy physics. The method combines quantum computing principles with graph neural networks to improve the classification of particle jets, with enhanced interpretability and performance compared to classical approaches.
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Research Area: Quantum Machine Learning, Graph Neural Networks, High-Energy Physics, Particle Physics
Recommended citation: Jahin, M. A., Masud, M. A., Mridha, M. F., & Dey, N. (2024). Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination. arXiv preprint arXiv:2411.01642.
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