Jet substructure probe to unfold singlet-doublet dark matter in the presence of non-standard cosmology
Prasanta Kumar Das, Partha Konar, Saumyen Kundu, and Sudipta Show

TL;DR
This paper proposes a novel collider search strategy using fat jet substructure variables to detect singlet-doublet dark matter in non-standard cosmological scenarios, enhancing discovery prospects at the HL-LHC.
Contribution
It introduces a new method employing fat jet substructure and multivariate analysis to probe non-thermal dark matter models affected by non-standard cosmology.
Findings
Fat jet substructure variables help distinguish signal from QCD background.
The proposed method extends the parameter space accessible at the HL-LHC.
Non-standard cosmology significantly impacts dark matter production and detection strategies.
Abstract
We examine the singlet-doublet fermionic dark matter model, where the non-thermal production of the dark matter in light of a non-standard cosmology demands a significantly large interaction rate than the typical radiation-dominated Universe. Despite being a model of freeze-in light dark matter and heavy mediator, the characteristic long-lived particle searches at the collider experiment and the displaced vertex signature do not help in probing such a dark sector since this non-standard interaction mandates nearly prompt decay. We make a counterproposal to probe such signal with di-fat-jets generated from the boosted decays of massive vector bosons and Standard Model Higgs, along with the substantial missing transverse momentum to probe the dark matter at LHC. Interestingly, substructure variables associated with these fat jets have an additional handle to tackle the extensive QCD…
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.
Taxonomy
TopicsParticle physics theoretical and experimental studies · Dark Matter and Cosmic Phenomena · Computational Physics and Python Applications
