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Title: Enhancing Long-Lived Particles Searches at the LHC with Precision Timing Information

Journal Article · · Physical Review Letters
 [1];  [2];  [1]
  1. Univ. of Chicago, Chicago, IL (United States)
  2. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Univ. of Maryland, College Park, MD (United States)

We explore the physics potential of using precision timing information at the LHC in searches for long-lived particles (LLPs). In comparison with the light standard model particles, the decay products of massive LLPs arrive at detectors with time delays around the nanosecond scale. We propose new strategies to take advantage of this time delay feature by using initial state radiation to time stamp the collision event and require at least one LLP to decay within the detector. This search strategy is effective for a broad range of models. In addition to outlining this general approach, we demonstrate its effectiveness with the projected reach for two benchmark scenarios: a Higgs boson decaying into a pair of LLPs, and pair production of long-lived neutralinos in the gauge mediated supersymmetry breaking models. Our strategy increases the sensitivity to the lifetime of the LLP by two orders of magnitude or more and particularly exhibits a better behavior with a linear dependence on the lifetime in the large lifetime region compared to traditional LLP searches. Furthermore the timing information significantly reduces the standard model background and provides a powerful new dimension for LLP searches.

Research Organization:
Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP)
Grant/Contract Number:
AC02-07CH11359
OSTI ID:
1457538
Report Number(s):
arXiv:1805.05957; FERMILAB-PUB-18-173-T; EFI-18-7; PRLTAO; 1673386
Journal Information:
Physical Review Letters, Vol. 122, Issue 13; ISSN 0031-9007
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 55 works
Citation information provided by
Web of Science

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Study of energy deposition patterns in hadron calorimeter for prompt and displaced jets using convolutional neural network text January 2019
Dark Mesons at the LHC text January 2018
Stopping Quirks at the LHC text January 2018
Discovering the Twin Higgs Boson with Displaced Decays text January 2018
Seeking for sterile neutrinos with displaced leptons at the LHC text January 2019
Study of energy deposition patterns in hadron calorimeter for prompt and displaced jets using convolutional neural network text January 2019
Hypercharged Naturalness text January 2019
A sceptical analysis of Quantized Inertia text January 2019

Figures / Tables (4)