Enhancing Sensitivities to Long-lived Particles with High Granularity Calorimeters at the LHC
Jia Liu, Zhen Liu, Lian-Tao Wang, Xiao-Ping Wang

TL;DR
This paper proposes a novel search strategy for long-lived particles at the LHC using the high granularity of the upgraded CMS HGCAL to identify signals and suppress backgrounds, significantly improving sensitivity over previous methods.
Contribution
It introduces a new LLP search method leveraging HGCAL's shower track imaging, enhancing detection sensitivity for Higgs decays into LLP pairs across various lifetimes.
Findings
Projected sensitivity for Higgs decay BR$(h o XX)$ down to 10^{-4}–10^{-6}
HGCAL enables identification of shower tracks to suppress backgrounds
Enhanced coverage of LLP parameter space compared to previous searches
Abstract
The search for long-lived particles (LLP) is an exciting physics opportunity in the upcoming runs of the Large Hadron Collider. In this paper, we focus on a new search strategy of using the High Granularity Calorimeter (HGCAL), part of the upgrade of the CMS detector, in such searches. In particular, we demonstrate that the high granularity of the calorimeter with this upgrade, which allows us to see "shower tracks" in the calorimeter, can play a crucial role in identifying the signal and suppressing the background. We study the potential reach of the HGCAL using a signal model in which the Standard Model Higgs boson decays into a pair of LLPs, . After carefully estimating the Standard Model QCD and the misreconstructed fake-track backgrounds, we give the projected reach for both a more conservative vector boson fusion trigger and a novel displaced-track-based trigger. Our…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
