Using displaced tracks to search for sterile neutrinos in the ATLAS detector

The Standard Model of particle physics is a powerful theory of nature, yet it does not account for all physical observations. Notably, the nonzero masses of the three neutrino flavours and their transformations into one another suggest the need for an extension of the Standard Model. One such extension postulates the existence of Heavy Neutral Leptons (HNLs, ) — right-handed neutrino states that do not interact with other particles except through mixing with Standard Model neutrinos. HNLs may generate light neutrino masses through the so-called “seesaw mechanism.” This dissertation presents a direct search for long-lived HNLs using 139 fb⁻¹ of √s=13 TeV pp collision data collected by the ATLAS detector at the Large Hadron Collider. In this search, the is produced via W → μ or W → e and decays into a neutrino and two charged leptons, which form a displaced vertex in the inner detector. No signal is observed, and limits are set on the squared mixing angles of the with the Standard Model neutrinos in the mass range 3 GeV < m < 15 GeV. For the first time in a collider search, results are presented in the context of realistic HNL mixing models consistent with neutrino oscillation data. Such a displaced vertex search relies heavily upon nonstandard reconstruction algorithms. An additional pass of the track reconstruction algorithm with relaxed collision vertex pointing requirements is executed on a subset of the recorded data to improve sensitivity to long-lived particles in the inner detector. This Large-Radius Tracking (LRT) configuration is effective yet computationally expensive due to the reconstruction of many “fake” tracks not formed from individual charged particles. This algorithm was optimized in preparation for the Run 3 data-taking period, which began in July 2022. Fake LRT tracks are reduced by 95%, drastically improving the purity and reducing the computational load such that LRT is now run in the default reconstruction pipeline. This optimization is expected to substantially improve the sensitivity and reduce the complexity of long-lived particle analyses in ATLAS, including future HNL searches.Science, Faculty ofPhysics and Astronomy, Department ofGraduat