Lorentz-Equivariant Quantum Graph Neural Network for High-Energy Physics
Published in IEEE Transactions on Artificial Intelligence, 2025
This paper presents a Lorentz-equivariant quantum graph neural network designed for high-energy physics applications. The framework combines Lorentz symmetry principles with quantum graph neural networks and parameterized quantum circuits for particle physics analysis.
Recommended citation: Jahin, Md Abrar and Masud, Md. Akmol and Suva, Md Wahiduzzaman and Mridha, M. F. and Dey, Nilanjan. (2025). "Lorentz-Equivariant Quantum Graph Neural Network for High-Energy Physics." IEEE Transactions on Artificial Intelligence. 1-11.
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