RS3L: A jet tagging dataset for self-supervised learning based on re-simulation

<p>Jet tagging dataset used for "Re-Simulation-based Self-Supervised Learning" (RS3L, <a href="https://arxiv.org/abs/2403.07066">arXiv:2403.07066</a>). Simulated partons are re-showered with various parton shower configurations and reconstructed with the Delphes3 detector software.&nbsp;<br><br>The <code>singletons</code> array contains information about the jet and has dimensions <code>N_examples x N_augmentations x N_singletons</code>. The augmenations are ordered by: <br><br>1. nominal scenario: jet showered with Pythia8<br>2. changing the numerical seed in Pythia8<br>3. changing the scale controlling the probability for final state radiation by 1/sqrt(2)<br>4. changing the scale controlling the probability for final state radiation by sqrt(2)<br>5. using Herwig7 as parton shower</p> <p>The variables stored in the <code>singletons</code> array are:</p> <p><code>singletons = ['jettype','parton1_pt','parton1_eta','parton1_phi','parton1_e','parton2_pt','parton2_eta','parton2_phi','parton2_e', 'jet_pt','jet_eta','jet_phi','jet_e','jet_msd','jet_n2']</code><br><br></p> <p>For gluon-initiated jets,&nbsp;<code>parton1</code> and <code>parton2</code> are the two gluon daughters (see below). For any other jet type, parton1 is the main particle (W, H, Z, or single quark), and parton2 is filled with 0s.</p> <p>The <code>jet_pflow_cands</code> contains the particles clustered into the jet. The array has a shape <code>N_examples x N_augmentations x N_features x N_particles</code>.<br><br>The features per particle are:</p> <p><code>features = ['pt','relpt','eta','phi','dr','e','rele','charge','pdgid','d0','dz']</code><br><br>The <code>jettype</code> gives the parton at the origin of the jet:&nbsp;<br><br><code>jettype: <br>1: q<br>2: c<br>3: b<br>4: H-&gt;bb<br>5: g-&gt;qq<br>6: g-&gt;cc<br>7: g-&gt;bb<br>8: g-&gt;gg<br>9: W-&gt;two quarks<br>10: Z-&gt;qq<br>11: Z-&gt;bb</code></p> <p>&nbsp;</p>