Title: Boosted Higgs, dark matter, and deep learning

Abstract: In this seminar, I will present several complementary searches for the Higgs boson and dark matter mediators with the CMS experiment at the LHC. One technique uses the CMS scouting data stream concept to record larger data rates than otherwise possible. Other searches use initial- or final- state radiation to overcome trigger thresholds and study boosted dijet resonances, whose decay products are merged into a single jet. Jet substructure and dedicated decorrelation techniques are used to identify a potential signal and avoid sculpting the jet mass distribution; the dominant background is then estimated from data. The searches are interpreted in the context of simplified models of dark matter with spin-1 or spin-0 mediators. This approach has also been employed to the search for boosted Higgs bosons decaying to bottom quark-antiquark pairs using a machine-learning-based tagger. Finally, I will discuss how deep learning methods may help us improve these searches, and possibly, the trigger and data acquisition systems at the LHC.