2 citations · 5 across the 7 of their papers we have counts for
7 papers
Search for single production of a vector-like T quark decaying to a top quark and a neutral scalar boson in the lepton+jets final state in proton-proton collisions at = 13 TeV
CMS Collaboration
A search for single production of a vector-like T quark with charge 2/3, decaying to a top quark and a neutral scalar boson is presented. The boson can be a standard model Higgs…
Measurement of the dineutrino system kinematic variables in dileptonic top quark pair production in proton-proton collisions at = 13 TeV
CMS Collaboration
Differential top quark pair production cross sections are measured in the dilepton final states ee, , and e, as a function of kinematic variables of the…
A method for correcting the substructure of multiprong jets using the Lund jet plane
CMS Collaboration
Many analyses at the CERN LHC exploit the substructure of jets to identify heavy resonances produced with high momenta that decay into multiple quarks and/or gluons. This paper pre…
Search for top squarks in final states with many light-flavor jets and 0, 1, or 2 charged leptons in proton-proton collisions at = 13 TeV
CMS Collaboration
Several new physics models including versions of supersymmetry (SUSY) characterized by -parity violation (RPV) or with additional hidden sectors predict the production of events…
Combined effective field theory interpretation of Higgs boson, electroweak vector boson, top quark, and multi-jet measurements
CMS Collaboration
Constraints on Wilson coefficients (WCs) corresponding to dimension-six operators of the standard model effective field theory (SMEFT) are determined from a simultaneous fit to sev…
Measurements of the inclusive W and Z boson production cross sections and their ratios in proton-proton collisions at = 13.6 TeV
CMS Collaboration
Measurements are presented of the W and Z boson production cross sections in proton-proton collisions at a center-of-mass energy of 13.6 TeV. Data collected in 2022 and correspondi…
Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC
CMS Collaboration
We propose a neural network training method capable of accounting for the effects of systematic variations of the data model in the training process and describe its extension towa…