Abstract
The prevalence of null results in searches for new physics at the LHC motivates the effort to make these searches as model-independent as possible. We describe procedures for adapting the Matrix Element Method for situations where the signal hypothesis is not known a priori. We also present general and intuitive approaches for performing analyses and presenting results, which involve the flattening of background distributions using likelihood information. The first flattening method involves ranking events by background matrix element, the second involves quantile binning with respect to likelihood (and other) variables, and the third method involves reweighting histograms by the inverse of the background distribution.
Highlights
The CERN Large Hadron Collider (LHC) will soon resume operation, probing energies never before accessed with colliders
The lack of convincing evidence for new physics at the LHC to date suggests that we may be looking in the wrong places
The Matrix Element Method (MEM) [3] and similar multivariate analyses [4] have been used with success in LHC experiments
Summary
Matchev1 1Physics Department, University of Florida, Gainesville, FL 32611, USA (Dated: May 22, 2014). The prevalence of null results in searches for new physics at the LHC motivates the effort to make these searches as model-independent as possible. We describe procedures for adapting the Matrix Element Method for situations where the signal hypothesis is not known a priori. We present general and intuitive approaches for performing analyses and presenting results, which involve the flattening of background distributions using likelihood information. The first flattening method involves ranking events by background matrix element, the second involves quantile binning with respect to likelihood (and other) variables, and the third method involves reweighting histograms by the inverse of the background distribution. PACS numbers: 12.60.-i, 29.85.Fj, 07.05.Rm, 02.50.Sk arXiv:1405.5879v1 [hep-ph] 22 May 2014
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