Journal Article

·2026 OPEN ACCESS

Search for nonresonant new physics signals in high-mass dilepton events produced in association with b-tagged jets in proton-proton collisions at $$\sqrt{s}=13$$ TeV

V. Chekhovsky , A. Hayrapetyan , V. Makarenko , A. Tumasyan , W. Adam , J. W. Andrejkovic , L. Benato , T. Bergauer , K. Damanakis , C. Favaro ,

Journal of High Energy Physics

Abstract

A bstract A search for nonresonant new physics phenomena in high-mass dilepton events produced in association with b-tagged jets is performed using proton-proton collision data collected in 2016–2018 by the CMS experiment at the CERN LHC, at a center-of-mass energy of 13 TeV corresponding to an integrated luminosity of 138 fb − 1 . The analysis considers two effective field theory models with dimension-six operators; involving four-fermion contact interactions between two leptons ( ℓℓ , electrons or muons) and b or s quarks (bb ℓℓ and bs ℓℓ ). Two lepton flavor combinations (ee and μμ ) are required and events are classified as having 0, 1, or ≥2 b-tagged jets in the final state. No significant excess is observed over the standard model backgrounds. Upper limits are set on the production cross section of the new physics signals. These translate into lower limits on the energy scale Λ of 6.9 to 9.0 TeV in the bb ℓℓ model, depending on model parameters, and on the ratio of energy scale and effective coupling, Λ/ g * , of 2.0 to 2.6 TeV in the bs ℓℓ model. Lepton flavor universality is also tested by comparing the dielectron (ee) and dimuon ( μμ ) mass spectra for different b-tagged jet multiplicities. No significant deviation from the standard model expectation of unity is observed.

Keywords

Lepton Physics beyond the Standard Model Large Hadron Collider Quark Standard Model (mathematical formulation) Luminosity Missing energy Pair production Universality (dynamical systems) Physics Particle physics Nuclear physics

Subject Areas

Particle physics theoretical and experimental studies ·Nuclear and High Energy Physics ·Physical Sciences
High-Energy Particle Collisions Research ·Nuclear and High Energy Physics ·Physical Sciences
Computational Physics and Python Applications ·Artificial Intelligence ·Physical Sciences

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