43 citations · 92 across the 24 of their papers we have counts for
7 papers · 1 filter
Identification of tau leptons using a convolutional neural network with domain adaptation
CMS Collaboration
A tau lepton identification algorithm, DeepTau, based on convolutional neural network techniques, has been developed in the CMS experiment to discriminate reconstructed hadronic de…
Search for a new neutral gauge boson produced in association with one or two b jets and decaying into a pair of muons in proton-proton collisions at = 13 TeV
CMS Collaboration
A search for a new neutral gauge boson, Z', produced in association with one or two jets, including at least one b jet, and decaying into a pair of muons is presented. The analysis…
Search for a Higgs boson produced in association with a charm quark and decaying to a W boson pair in proton-proton collisions at = 13 TeV
CMS Collaboration
This paper presents a search for a Higgs boson produced in association with a charm quark (cH) which allows to probe the Higgs-charm Yukawa coupling strength modifier $κ_\mathrm{c}…
Determination of the spin and parity of all-charm tetraquarks
CMS Collaboration
The traditional quark model accounts for the existence of baryons, such as protons and neutrons, which consist of three quarks, as well as mesons, composed of a quark-antiquark pai…
Search for charged-lepton flavour violation in top quark interactions with an up-type quark, a muon, and a lepton in proton-proton collisions at = 13 TeV
CMS Collaboration
A search for charged-lepton flavour violation (CLFV) in top quark (t) production and decay is presented. The search uses proton-proton collision data corresponding to 138 fb…
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…