Testing the seesaw mechanisms via displaced right-handed neutrinos from a light scalar at the HL-LHC
Wei Liu, Jiale Li, Jing Li, Hao Sun

TL;DR
This paper explores the detection of long-lived right-handed neutrinos produced from a light scalar in a B-L extended model at the HL-LHC, highlighting potential signatures like displaced vertices and time-delayed leptons.
Contribution
It introduces a novel search strategy for right-handed neutrinos via displaced signatures at the HL-LHC, focusing on a light scalar in the B-L model and assessing experimental sensitivities.
Findings
Displaced vertex searches can probe active-sterile mixing down to 10^{-5}.
Time-delayed lepton searches can reach sensitivities an order of magnitude lower.
The study demonstrates the potential to test type-I seesaw mechanisms at the HL-LHC.
Abstract
We investigate the pair production of right-handed neutrinos from the decay of a light scalar in the model. The scalar mixes to the SM Higgs, and the physical scalar is required to be lighter than the observed Higgs. The produced right-handed neutrinos are predicted to be long-lived according to the type-I seesaw mechanism, and yield potentially distinct signatures such as displaced vertex and time-delayed leptons at the CMS/ATLAS/LHCb, as well as signatures at the far detectors including the CODEX-b, FACET, FASER, MoEDAL-MAPP and MATHUSLA. We analyze the sensitivity reach at the HL-LHC for the right-handed neutrinos with masses of 2.5 30 GeV, showing that the active-sterile mixing to muons can be probed to at the CMS/ATLAS/LHCb using the displaced vertex searches, and one magnitude lower at the MATHUSLA/CMS using time-delayed…
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.
Taxonomy
TopicsParticle physics theoretical and experimental studies · Dark Matter and Cosmic Phenomena · Computational Physics and Python Applications
