442 citations · 2.9k across the 95 of their papers we have counts for
6 papers · 1 filter
Sparse Data Generation for Particle-Based Simulation of Hadronic Jets in the LHC
Breno Orzari, Thiago Tomei, Maurizio Pierini +5
We develop a generative neural network for the generation of sparse data in particle physics using a permutation-invariant and physics-informed loss function. The input dataset use…
Particle Cloud Generation with Message Passing Generative Adversarial Networks
Raghav Kansal, Javier Duarte, Hao Su +6
In high energy physics (HEP), jets are collections of correlated particles produced ubiquitously in particle collisions such as those at the CERN Large Hadron Collider (LHC). Machi…
Constraints on the initial state of PbPb collisions via measurements of Z boson yields and azimuthal anisotropy at 5.02 TeV
CMS Collaboration
The CMS experiment at the LHC has measured the differential cross sections of Z bosons decaying to pairs of leptons, as functions of transverse momentum and rapidity, in lead-lead…
Measurements of production cross sections of the Higgs boson in the four-lepton final state in proton-proton collisions at 13 TeV
CMS Collaboration
Production cross sections of the Higgs boson are measured in the H ZZ ( e, ) decay channel. A data sample of proton-proton collisions at a center-o…
Measurement of the W production cross section in proton-proton collisions at 13 TeV and constraints on effective field theory coefficients
CMS Collaboration
A fiducial cross section for W production in proton-proton collisions is measured at a center-of-mass energy of 13 TeV in 137 fb of data collected using the CMS detector…
Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics
Raghav Kansal, Javier Duarte, Breno Orzari +5
We develop a graph generative adversarial network to generate sparse data sets like those produced at the CERN Large Hadron Collider (LHC). We demonstrate this approach by training…