Probing Compressed Mass Spectrum Supersymmetry at the LHC with the Vector Boson Fusion Topology

TL;DR

This study explores the detection of supersymmetric particles with compressed mass spectra at the LHC using vector boson fusion topology, employing a novel machine learning approach to improve sensitivity in challenging scenarios.

Contribution

It introduces a new machine learning method for better signal-background discrimination in supersymmetry searches with compressed spectra at the LHC.

Findings

Projected bounds up to 1.1 TeV chargino mass in challenging scenarios.

Significant improvement in signal sensitivity over traditional methods.

Method applicable to current and future LHC data sets.

Abstract

We present a phenomenology study probing pair production of supersymmetric charginos and neutralinos ("electroweakinos") with the vector boson fusion (VBF) topology in proton-proton collisions at CERN's Large Hadron Collider (LHC). In particular, we examine the compressed-mass spectrum phase space that has been traditionally challenging due to experimental constraints. The final states considered have two jets, large missing transverse momentum, and one, two, or three light leptons. Different model scenarios are considered for the production and decays of the electroweakinos. A novel high-performance and interpretable sequential attention-based machine learning algorithm is employed for signal-background discrimination and is observed to significantly improve signal sensitivity over traditional methods. We report expected signal significances for integrated luminosities of $137$, $300$, and $3000$ $\textrm{fb}^{-1}$ corresponding to the current data acquired at the LHC, expectation for the end of Run 3, and the expectation for the high-luminosity LHC. Our methodology results in projected 95\% confidence level bounds that cover chargino masses up to 1.1 TeV in compressed-mass spectrum scenarios within the R-parity conserving minimal supersymmetric standard model. This parameter space, currently beyond the reach of ATLAS and CMS searches at the LHC, is traditionally challenging to explore due to significant Standard Model backgrounds and low signal cross-sections.