PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 18, 2026The European Physical Journal C0 citationsOpen Access

Deciphering compressed electroweakino excesses with

JAJack Y. ArazBFBenjamin FuksMGMark D. Goodsell

Key Points

  • The aim is to improve the statistical handling and analysis of soft lepton signatures in electroweakino research.
  • Enhanced software package version 1.11 improves efficiency table handling and observable computation.
  • Integration with third-party software for better analysis accuracy.
  • Validation of analyses for Run 2 LHC targeting soft leptons and missing energy.
  • Significant improvements in statistical capabilities demonstrated by validated analyses.
  • Successful investigation of excesses in soft lepton and missing transverse energy channels.
  • Operational utility of software extensions shown through effective analysis of the Next-to-Minimal Supersymmetric Standard Model.

Abstract

Abstract We present version 1.11 of "Image missing" , which extends the software package in several major ways to improve the handling of efficiency tables, the computation of observables in different reference frames and the calculation of statistical limits and/or significance. We detail how these improvements, whose development was motivated by the desire to implement two Run 2 LHC analyses targeting signatures with soft leptons and missing energy and exhibiting mild excesses (ATLAS-SUSY-2018-16 and ATLAS-SUSY-2019-09), have been implemented by both direct extensions of the code and integrations with third-party software. We then document the implementation and validation of these analyses, demonstrating their utility along with the improved statistics capabilities of "Image missing" through an investigation of the Next-to-Minimal Supersymmetric Standard Model in the context of a larger set of overlapping excesses in channels with soft leptons/jets and missing transverse energy.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Araz et al. (2026) studied this question.

synapsesocial.com/papers/6a0aaccf5ba8ef6d83b703e5https://doi.org/10.1140/epjc/s10052-026-15710-3
Ask AI
Helpful
Bookmark
Share
View Full Paper