Measurement of the Higgs boson production rate in association with top quarks in final states with electrons, muons, and hadronically decaying tau leptons at $$\sqrt{s} = 13\,\text {TeV} $$

The European Physical Journal C · 2021 · 78 citations

• Physics
• Particle physics
• Nuclear physics

production rate to date.

Search for direct top squark pair production in events with one lepton, jets, and missing transverse momentum at 13 TeV with the CMS experiment

Journal of High Energy Physics · 2020 · 68 citations

• Physics
• Particle physics
• Nuclear physics

A bstract A search for direct top squark pair production is presented. The search is based on proton-proton collision data at a center-of-mass energy of 13 TeV recorded by the CMS experiment at the LHC during 2016, 2017, and 2018, corresponding to an integrated luminosity of 137 fb −1 . The search is carried out using events with a single isolated electron or muon, multiple jets, and large transverse momentum imbalance. The observed data are consistent with the expectations from standard model processes. Exclusions are set in the context of simplified top squark pair production models. Depending on the model, exclusion limits at 95% confidence level for top squark masses up to 1.2 TeV are set for a massless lightest supersymmetric particle, assumed to be the neutralino. For models with top squark masses of 1 TeV, neutralino masses up to 600 GeV are excluded.

A deep neural network to search for new long-lived particles decaying to jets

Machine Learning Science and Technology · 2020 · 54 citations

• Artificial Intelligence
• Computer Science
• Physics

A tagging algorithm to identify jets that are significantly displaced from the proton-proton (pp) collision region in the CMS detector at the LHC is presented. Displaced jets can arise from the decays of long-lived particles (LLPs), which are predicted by several theoretical extensions of the standard model. The tagger is a multiclass classifier based on a deep neural network, which is parameterised according to the proper decay length c 0 of the LLP. A novel scheme is defined to reliably label jets from LLP decays for supervised learning. Samples of pp collision data, recorded by the CMS detector at a centre-of-mass energy of 13 TeV, and simulated events are used to train the neural network. Domain adaptation by backward propagation is performed to improve the simulation modelling of the jet class probability distributions observed in pp collision data. The potential performance of the tagger is demonstrated with a search for long-lived gluinos, a manifestation of split supersymmetric models. The tagger provides a rejection factor of 10 000 for jets from standard model processes, while maintaining an LLP jet tagging efficiency of 30%-80% for gluinos with 1 mmc 0 10 m. The expected coverage of the parameter space for split supersymmetry is presented.

A measurement of the Higgs boson mass in the diphoton decay channel

Physics Letters B · 2020 · 165 citations

• Physics
• Particle physics
• Nuclear physics

A measurement of the mass of the Higgs boson in the diphoton decay channel is presented. This analysis is based on 35.9 fb -1 of proton-proton collision data collected during the 2016 LHC running period, with the CMS detector at a centre-of-mass energy of 13 TeV. A refined detector calibration and new analysis techniques have been used to improve the precision of this measurement. The Higgs boson mass is measured to be m H = 125.78 0.26 GeV. This is combined with a measurement of m H already performed in the H ZZ 4 decay channel using the same data set, giving m H = 125.46 0.16 GeV. This result, when further combined with an earlier measurement of m H using data collected in 2011 and 2012 with the CMS detector, gives a value for the Higgs boson mass of m H = 125.38 0.14 GeV. This is currently the most precise measurement of the mass of the Higgs boson.