570 citations · 5.6k across the 81 of their papers we have counts for
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Likelihood Analysis of the Minimal AMSB Model
E. Bagnaschi, M. Borsato, K. Sakurai +17
We perform a likelihood analysis of the minimal Anomaly-Mediated Supersymmetry Breaking (mAMSB) model using constraints from cosmology and accelerator experiments. We find that a w…
Parton Shower Uncertainties in Jet Substructure Analyses with Deep Neural Networks
James Barnard, Edmund Noel Dawe, Matthew J. Dolan +1
Machine learning methods incorporating deep neural networks have been the subject of recent proposals for new hadronic resonance taggers. These methods require training on a datase…
Likelihood Analysis of Supersymmetric SU(5) GUTs
E. Bagnaschi, J. C. Costa, K. Sakurai +17
We perform a likelihood analysis of the constraints from accelerator experiments and astrophysical observations on supersymmetric (SUSY) models with SU(5) boundary conditions on so…
Determining the Quantum Numbers of Simplified Models in production at the LHC
Matthew J. Dolan, Michael Spannowsky, Qi Wang +1
Simplified models provide an avenue for characterising and exploring New Physics for large classes of UV theories. In this article we study the ability of the LHC to probe the spin…
Dissecting Jets and Missing Energy Searches Using -body Extended Simplified Models
Timothy Cohen, Matthew J. Dolan, Sonia El Hedri +3
Simplified Models are a useful way to characterize new physics scenarios for the LHC. Particle decays are often represented using non-renormalizable operators that involve the mini…
Recommendations on presenting LHC searches for missing transverse energy signals using simplified -channel models of dark matter
Antonio Boveia, Oliver Buchmueller, Giorgio Busoni +30
This document summarises the proposal of the LHC Dark Matter Working Group on how to present LHC results on -channel simplified dark matter models and to compare them to direct…