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arXiv · 2411.11519

Transformer networks for Heavy flavor jet tagging

A. Hammad·Mihoko M Nojiri
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Abstract

In this article, we review recent machine learning methods used in challenging particle identification of heavy-boosted particles at high-energy colliders. Our primary focus is on attention-based Transformer networks. We report the performance of state-of-the-art deep learning networks and further improvement coming from the modification of networks based on physics insights. Additionally, we discuss interpretable methods to understand network decision-making, which are crucial when employing highly complex and deep networks.

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A. Hammad, Mihoko M Nojiri. 2024-11-18. Transformer networks for Heavy flavor jet tagging. https://arxiv.org/abs/2411.11519

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