Search for vector-like leptons coupling to first- and second-generation Standard Model leptons in $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

TL;DR

This paper reports a search for vector-like leptons in proton-proton collisions at 13 TeV using the ATLAS detector, setting mass limits and no evidence of new particles was found.

Contribution

It introduces a novel search strategy using deep neural networks and categorization based on lepton flavor and multiplicity to improve sensitivity.

Findings

No significant excess observed above Standard Model background

Mass lower limits set at 1220 GeV for vector-like electrons in doublet scenario

Mass lower limits set at 400 GeV for vector-like muons in singlet scenario

Abstract

A search for pair production of vector-like leptons coupling to first- and second-generation Standard Model leptons is presented. The search is based on a dataset of proton-proton collisions at $\sqrt{s}=13$ TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 140 fb$^{-1}$. Events are categorised depending on the flavour and multiplicity of leptons (electrons or muons), as well as on the scores of a deep neural network targeting particular signal topologies according to the decay modes of the vector-like leptons. In each of the signal regions, the scalar sum of the transverse momentum of the leptons and the missing transverse momentum is analysed. The main background processes are estimated using dedicated control regions in a simultaneous fit with the signal regions to data. No significant excess above the Standard Model background expectation is observed and limits are set at 95% confidence level on the production cross-sections of vector-like electrons and muons as a function of the vector-like lepton mass, separately for SU(2) doublet and singlet scenarios. The resulting mass lower limits are 1220 GeV (1270 GeV) and 320 GeV (400 GeV) for vector-like electrons (muons) in the doublet and singlet scenarios, respectively.