Bumblebee: Foundation Model for Particle Physics Discovery
Wildridge, Andrew J., Rodgers, Jack P., Colbert, Ethan M., yao, Yao, Jung, Andreas W., Liu, Miaoyuan
–arXiv.org Artificial Intelligence
Bumblebee is a foundation model for particle physics discovery, inspired by BERT. By removing positional encodings and embedding particle 4-vectors, Bumblebee captures both generator- and reconstruction-level information while ensuring sequence-order invariance. Pre-trained on a masked task, it improves dileptonic top quark reconstruction resolution by 10-20% and excels in downstream tasks, including toponium discrimination (AUROC 0.877) and initial state classification (AUROC 0.625). The flexibility of Bumblebee makes it suitable for a wide range of particle physics applications, especially the discovery of new particles.
arXiv.org Artificial Intelligence
Dec-10-2024
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