Title |
Identification of the w-boson associated higgs boson production events with the cms detector at 13tev proton collision energy / |
Translation of Title |
Higso ir W bozonų vienalaikio susidarymo įvykių išskyrimas CMS detektoriumi esant 13TeV protonų susidūrimo energijai. |
Authors |
Venčkauskaitė, Monika |
Full Text |
|
Pages |
63 |
Keywords [eng] |
Higso bozonas, Higgs boson, daugiadimensinė analizė, multivariate analysis, mašininis mokymasis, machine learning, sprendimų medžiai, boosted decision trees |
Abstract [eng] |
Determining the Higgs boson properties is of high importance in particle physics today. For this analysis we selected the Higgs boson decay channel h → τ+ τ− with τ leptons decaying each into a muon and neutrinos and h → μ+ μ− channel. The selected Higgs boson production mechanism is Higgs boson production in association with the W boson. Therefore, the most complicated background process to discriminate is the Z boson production with the W boson where the signature is very similar: Z → τ+ τ− with τ leptons decaying each into a muon and neutrinos and Z → μ+ μ− . The W boson in all the mentioned processes decays into a muon and a neutrino. The goal of this analysis was to find discriminating variables for these two processes and use them to train the multivariate analysis method. We performed the analysis with the Monte Carlo simulations of the signal and the most important background processes. We found sixteen discriminating variables between the W h and W Z processes. These discriminants and the correlations between them were used to train multivariate analysis method - Boosted Decision Trees. The BDT were tested with independent test samples adjusted by the luminosity, respective cross-sections and branching fractions. These trained boosted decision trees will be used to analyze the data in proton-proton collisions at 13 TeV detected during the LHC Run II. |
Dissertation Institution |
Vilniaus universitetas. |
Type |
Master thesis |
Language |
English |
Publication date |
2016 |