Fermilab LHC Physics Center Machine Learning Hands-On Advanced Tutorial Session Datasets

The dataset jet_raw.tar.gz contains a sample of 2011 CMS Open Simulation in numpy arrays. The columns correspond to ['run', 'lumi', 'event', 'met', 'sumet', 'rho', 'pthat', 'mcweight', 'njet_ak7', 'jet_pt_ak7', 'jet_eta_ak7', 'jet_phi_ak7', 'jet_E_ak7', 'jet_msd_ak7', 'jet_area_ak7', 'jet_jes_ak7', 'jet_tau21_ak7', 'jet_isW_ak7', 'jet_ncand_ak7', 'ak7pfcand_ijet'] Each row is a separate anti-kT R=0.7 (AK7) jet. The code to produce the numpy arrays is located at https://doi.org/10.5281/zenodo.3901871 The dataset jet_images.h5 contains preprocessed 2D jet images. The datasets ntuple_4mu_bkg.root, ntuple_4mu_gg.root, and ntuple_4mu_VV.root contain simulated LHC events with 4 muons for the background process, gluon fusion Higgs boson production, and vector boson fusion Higgs boson production.

Related Organizations

University of Florida
United States
University of California, San Diego
United States

Keywords

tutorial, machine learning, LHC, high energy physics

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