
A deep learning approach based on symmetry-preserving attention networks (SPA-NET) can significantly improve the reconstruction of unstable heavy particles, such as top quarks and Higgs bosons, compared to traditional permutation-based methods.


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improving-reconstruction-of-unstable-heavy-particles-using-deep-symmetry-preserving-attention-networks


Improving Reconstruction of Unstable Heavy Particles Using Deep Symmetry-Preserving Attention Networks
