activity
20162026
most citedSearch for production of four top quarks in final states with same-sign or multiple leptons in proton-proton collisions at 13 TeV

112 citations · 1.1k across the 45 of their papers we have counts for

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37 papers · 1 filter

hep-ex2026

Measurement of the -channel single top quark cross section in proton-proton collisions at = 5.02 TeV

CMS Collaboration

The single top quark -channel production cross section is measured in proton-proton collisions at the CERN LHC at = 5.02 TeV, using data recorded with the CMS detecto…

hep-ex2026

Search for a narrow resonance with a mass between 10 and 70 GeV decaying to a pair of photons in proton-proton collisions at = 13 TeV

CMS Collaboration

The existence of a new spin-zero particle with a mass below the electroweak scale is predicted by several theoretical models. Searches for resonant production of photon pairs at th…

hep-ex2025★ 1 cited

Search for resonances decaying to an anomalous jet and a Higgs boson in proton-proton collisions at = 13 TeV

CMS Collaboration

This paper presents a search for new physics through the process where a new massive particle, X, decays into a Higgs boson and a second particle, Y. The Higgs boson subsequently d…

hep-ex2025★ 22 cited

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…

hep-ex2025★ 1 cited

Search for an exotic decay of the 125 GeV Higgs boson to a pair of light pseudoscalars in the final state of two muons and two c-quarks in proton-proton collisions at with CMS Open Data

Danyer Perez Adan

A search is performed for pairs of light pseudoscalar bosons (a) produced from decays of the 125 GeV Higgs boson (). The analysis is based on publicly available dat…

hep-ex2025★ 1 cited

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…