SearcharxivSearch

arXiv subjects

Dongsub Lee

Publications and source records attributed to Dongsub Lee.

2 recordsLinked to original sources

Boosting Invisible Higgs Searches by Tagging a Gluon Jet for Gluon Fusion Process

We propose a novel method in that quark-gluon tagging of the jets emitted as initial state radiation (ISR) can boost searches of invisible Higgs from gluon fusion processes against irreducible electroweak vector boson productions. While quark ISR typically takes up a dominant portion than gluon in the background processes mainly by frequent quark-gluon initiated hard scatterings at the LHC, gluon ISR portion in the gluon fusion can be significantly larger in the central region of detector. Focusing on invisible Higgs searches using jet substructure variables capturing the new features, we demonstrate that Higgs from gluon fusion constrains invisible Higgs decays the most, over vector boson fusion traditionally known as the most constraining, and the limit on the branching ratio is significantly improved. We summarize with emphasizing that our method has wider implications in search for new resonances from gluon fusion processes.

hep-ph

Beyond $M_{t\bar{t}}$: learning to search for a broad $t\bar t$ resonance at the LHC

A resonance peak in the invariant mass spectrum has been the main feature of a particle at collider experiments. However, broad resonances not exhibiting such a sharp peak are generically predicted in new physics models beyond the Standard Model. Without a peak, how do we discover a broad resonance at colliders? We use machine learning technique to explore answers beyond common knowledge. We learn that, by applying deep neural network to the case of a $t\bar{t}$ resonance, the invariant mass $M_{t\bar{t}}$ is still useful, but additional information from off-resonance region, angular correlations, $p_T$, and top jet mass are also significantly important. As a result, the improved LHC sensitivities do not depend strongly on the width. The results may also imply that the additional information can be used to improve narrow-resonance searches too. Further, we also detail how we assess machine-learned information.

hep-ph