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arXiv · 2408.11616

RODEM Jet Datasets

Knut Zoch·John Andrew Raine·Debajyoti Sengupta·Tobias Golling
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Abstract

We present the RODEM Jet Datasets, a comprehensive collection of simulated large-radius jets designed to support the development and evaluation of machine-learning algorithms in particle physics. These datasets encompass a diverse range of jet sources, including quark/gluon jets, jets from the decay of W bosons, top quarks, and heavy new-physics particles. The datasets provide detailed substructure information, including jet kinematics, constituent kinematics, and track displacement details, enabling a wide range of applications in jet tagging, anomaly detection, and generative modelling.

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Knut Zoch, John Andrew Raine, Debajyoti Sengupta, Tobias Golling. 2024-08-21. RODEM Jet Datasets. https://arxiv.org/abs/2408.11616

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