LHC signals of triplet scalars as dark matter portal: cut-based approach and improvement with gradient boosting and neural networks

Journal of High Energy Physics

Biswarup Mukhopadhyaya¹  Atri Dey²  Jayita Lahiri² 

[1] Department of physical sciences, Indian Institute of Science Education and Research Kolkata, 741 246, Mohanpur, India;Regional Centre for Accelerator-based Particle Physics, Harish-Chandra Research Institute, HBNI, Chhatnag Road, Jhunsi, 211 019, Allahabad, India;

关键词: Beyond Standard Model;    Dark matter;    Higgs physics;    Hadron-Hadron scat- tering (experiments);   

DOI  :  10.1007/JHEP06(2020)126

来源: Springer

【 摘 要 】

We consider a scenario where an SU(2) triplet scalar acts as the portal for a scalar dark matter particle. We identify regions of the parameter space, where such a triplet coexists with the usual Higgs doublet consistently with all theoretical as well as neutrino, accelerator and dark matter constraints, and the triplet-dominated neutral state has substantial invisible branching fraction. LHC signals are investigated for such regions, in the final state same-sign dilepton + ≥ 2 jets +. While straightforward detectability at the high-luminosity run is predicted for some benchmark points in a cut-based analysis, there are other benchmarks where one has to resort to gradient boosting/neural network techniques in order to achieve appreciable signal significance.

【 授权许可】

Unknown