Discovering the Dark Universe with Artificial Intelligence

• Shih-Chieh Hsu (University of Washington Seattle (US))

Compelling experimental evidence strongly supports searches for new particles predicted by theories Beyond the Standard Model (BSM). Such searches are connected to fundamental questions among the highest priorities of particle physics like dark matter baryogenesis and hierarchy problems. At the Large Hadron Collider (LHC) the ATLAS experiment is ideally suited for detecting heavy states like heavy Higgs and dark scalars that decay to particles with high transverse momentum (pT) to the beam. In this talk I will present the state-of-the-art heavy Higgs and dark scalar searches in ATLAS. Specifically I will highlight how Artificial Intelligence plays a role to advance and expand the LHC physics program. This includes the improvement of on-going analyses through novel algorithm developments and new opportunities for discovery with accelerated Machine Learning which can address big data challenges from the upcoming High-Luminosity LHC.