Data-driven model-independent searches for long-lived particles at the LHC

Andrea Coccaro, David Curtin, H. J. Lubatti, Heather Russell, Jessie Shelton

Research output: Contribution to journalArticlepeer-review


Neutral long-lived particles (LLPs) are highly motivated by many beyond the Standard Model scenarios, such as theories of supersymmetry, baryogenesis, and neutral naturalness, and present both tremendous discovery opportunities and experimental challenges for the LHC. A major bottleneck for current LLP searches is the prediction of Standard Model backgrounds, which are often impossible to simulate accurately. In this paper, we propose a general strategy for obtaining differential, data-driven background estimates in LLP searches, thereby notably extending the range of LLP masses and lifetimes that can be discovered at the LHC. We focus on LLPs decaying in the ATLAS muon system, where triggers providing both signal and control samples are available at LHC run 2. While many existing searches require two displaced decays, a detailed knowledge of backgrounds will allow for very inclusive searches that require just one detected LLP decay. As we demonstrate for the h→XX signal model of LLP pair production in exotic Higgs decays, this results in dramatic sensitivity improvements for proper lifetimes 10 m. In theories of neutral naturalness, this extends reach to glueball masses far below the bb threshold. Our strategy readily generalizes to other signal models and other detector subsystems. This framework therefore lends itself to the development of a systematic, model-independent LLP search program, in analogy to the highly successful simplified-model framework of prompt searches.

Original languageEnglish (US)
Article number113003
JournalPhysical Review D
Issue number11
StatePublished - Dec 8 2016
Externally publishedYes

ASJC Scopus subject areas

  • Physics and Astronomy (miscellaneous)


Dive into the research topics of 'Data-driven model-independent searches for long-lived particles at the LHC'. Together they form a unique fingerprint.

Cite this