2014/12/02 by Jiří Franc, J. Franc, Petr Bouř +8
Mathematics · Physics and Astronomy · #Data Analysis #FOS: Physical sciences #Fermilab #Gaussian #High Energy Physics - Experiment (hep-ex) #High-Energy Particle Collisions Research #Homogeneity (statistics) #Large Hadron Collider #Mathematics #Muon #Nuclear physics #Pair production #Particle physics #Particle physics theoretical and experimental studies #Physics #Quantum mechanics #Quark #Statistical Methods and Inference #Statistics #Statistics and Probability (physics.data-an) #Tevatron #Top quark #hep-ex #physics.data-an
paper · pdf · doi:10.48550/arxiv.1412.1076
Top 2014 Conference proceeding
openalex publication_date 2014/12/02 · arxiv created 2014/12/12 · arxiv updated 2014/12/15 · openalex created_date 2022/09/13 · openalex updated_date 2026/08/05
We present several different types of multivariate statistical techniques used in the measurement of the inclusive top pair production cross section in p p-collisions at √(s) = 1.96 TeV employing the full RunII data (9.7\textrm fb-1) collected with the D0 detector at the Fermilab Tevatron Collider. We consider the final state of the top quark pair decays containing one electron or muon and at least two jets. We proceed various statistical homogeneity tests such as Anderson - Darling, Kolmogorov - Smirnov, and φ-divergences tests to determine, which variables have good data-MC agreement, as well as a good separation power. We adjusted all tests for using weighted empirical distribution functions. Further we separate tt signal from the background by the application of Generalized Linear Models, Gaussian Mixture Models, Neural Networks with Switching Units and confront them with familiar methods from ROOT TMVA package such as Boosted Decision Trees, and Multi-layer Perceptron. We compare results by area under receiver operating characteristic curve and verify the quality of the discrimination from all methods.