Complementarity of Resonant Scalar, Vector-Like Quark and Superpartner Searches in Elucidating New Phenomena
Anke Biek\"otter, JoAnne L. Hewett, Jong Soo Kim, Michael Kr\"amer,, Thomas G. Rizzo, Krzysztof Rolbiecki, Jamie Tattersall, Torsten Weber

TL;DR
This paper explores how combined searches for scalar singlets, vector-like quarks, and superpartners can more effectively reveal new physics phenomena, using models motivated by the LHC diphoton excess.
Contribution
It demonstrates the complementary roles of different search strategies in constraining models with scalar singlets and vector-like quarks, highlighting the importance of multi-pronged approaches.
Findings
Missing energy searches outperform dedicated quark searches in sensitivity.
Combined search strategies provide stronger constraints on new physics models.
The study is motivated by the LHC diphoton excess.
Abstract
The elucidation of the nature of new phenomena requires a multi-pronged approach to understand the essential physics that underlies it. As an example, we study the simplified model containing a new scalar singlet accompanied by vector-like quarks, as motivated by the recent diphoton excess at the LHC. To be specific, we investigate three models with -doublet, vector-like quarks with Yukawa couplings to a new scalar singlet and which also couple off-diagonally to corresponding Standard Model fermions of the first or third generation through the usual Higgs boson. We demonstrate that three classes of searches can play important and complementary roles in constraining this model. In particular, we find that missing energy searches designed for superparticle production, supply superior sensitivity for vector-like quarks than the dedicated new quark searches themselves.
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.
