On new physics searches with multidimensional differential shapes
arXiv:1702.05106 · doi:10.1016/j.physletb.2018.01.008
Abstract
In the context of upcoming new physics searches at the LHC, we investigate the impact of multidimensional differential rates in typical LHC analyses. We discuss the properties of shape information, and argue that multidimensional rates bring limited information in the scope of a discovery, but can have a large impact on model discrimination. We also point out subtleties about systematic uncertainties cancellations and the Cauchy-Schwarz bound on interference terms.
8 pages, 5 figures
References in corpus (7)
- PYTHIA 6.4 Physics and Manual
- The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations
- Bayes in the sky: Bayesian inference and model selection in cosmology
- MadAnalysis 5, a user-friendly framework for collider phenomenology
- Complete Higgs Sector Constraints on Dimension-6 Operators
- Better Higgs Measurements Through Information Geometry
- The Effective Standard Model after LHC Run I
Cited by in corpus (6)
- Searching for axion-like particles with proton tagging at the LHC
- Standard Model EFT and Extended Scalar Sectors
- Exploring SMEFT in VH with Machine Learning
- Approaching robust EFT limits for CP-violation in the Higgs sector
- Phenomenology of vector-like leptons with Deep Learning at the Large Hadron Collider
- Using Machine Learning to disentangle LHC signatures of Dark Matter candidates