Low Energy Leptons in High Energy Physics: A Search for Physics beyond the Standard Model with Compressed Mass-Spectra and New Algorithms for Triggering on Electrons at the High Luminosity LHC

A search for new physics beyond the Standard Model with compressed mass-spectra is performed, motivated by natural solutions to the hierarchy problem or the observed Dark Matter relic abundance. Compressed mass-spectra scenarios are particularly challenging to probe as they are characterized by final states with only low visible and missing energy. These signatures are hard to distinguish from the overwhelming background of Standard Model processes in the LHC environment, and therefore could have escaped experimental observation thus far. The analysis targets final states with multiple low-momentum prompt or displaced leptons and missing transverse energy, relying on 138 fb$^{-1}$ of proton-proton collision data at a center-of-mass energy of $\sqrt s$ = 13 TeV, collected by the CMS experiment during LHC Run 2. The results of the search are interpreted in terms of a simplified wino-bino model of R-parity conserving Supersymmetry. The search sets exclusion limits at 95% confidence level as function of the lifetime and masses of the new particle states. For promptly decaying winos, the signal exclusion extends to mass-splittings as low as 900 MeV for a wino mass of 100 GeV. This result hereby closes the sensitivity gap at mass-splittings between 0.9 and 2 GeV, implying that LHC searches now exceed the mass-bounds for compressed electroweakinos from LEP experiments over the full range of the mass-splitting. For long-lived scenarios the maximum exclusion is obtained for a $\chi_2^0$ lifetime of $c\tau$ = 100 mm, $m_{\chi_2^0}$ = 400 GeV and a mass-splitting $\Delta m(\chi_2^0, \chi_1^0)$ = 20 GeV. The search categories targeting final states with prompt leptons are furthermore included in the legacy Run 2 combination of searches for electroweak Supersymmetry, covering the production of charginos, neutralinos and sleptons. The combined search expands the excluded parameter space by as much as 125 GeV, depending on the model, with respect to the most sensitive component search and also covers some of the intermediate sensitivity gaps between mass-compressed and uncompressed signal scenarios. Finally, to ensure feasibility of future physics analyses even under the harsh data-taking conditions of the High Luminosity LHC era, a new electron reconstruction and identification algorithm for the Phase-2 upgrade of the CMS Level-1 Trigger is developed. The new approach increases the electron selection efficiency by up to 10% with respect to the baseline algorithm, making use of machine learning techniques, tracks reconstructed at the 40 MHz collision rate, high granularity Calorimeter information and state-of-the-art FPGAs. It furthermore paves the way for the implementation of identification algorithms for low-momentum electrons that could help expand even further the analysis sensitivity at the HL-LHC.