Téléchargez le livre : Measurement of the Inclusive Electron Cross-Section from Heavy-Flavour Decays and Search for Compressed Supersymmetric Scenarios with the ATLAS Experiment

Measurement of the Inclusive Electron Cross-Section from Heavy-Flavour Decays and Search for Compressed Supersymmetric Scenarios with the ATLAS Experiment



de

Éditeur :

Springer


Collection :

Springer Theses

Paru le : 2014-06-11



eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
52,74 €
Téléchargement immédiat
Dès validation de votre commande
Ajouter à ma liste d'envies
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

badge apple Application Louise Reader
badge Android Application Louise Reader
Description
The first part of this thesis presents the measurement of the inclusive cross-section for electron production from heavy-flavour decays in the electron transverse momentum range 7 GeV < pT < 26 GeV using 1.3 pb-1 of 7 TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider in 2010. The measured value of the cross-section within the fiducial range of the analysis is s_e^HF = 0.946 ± 0.020(stat.) ± 0.146(syst.) ± 0.032(lumi.) µb. Theoretical predictions are in good agreement with the measurement. The second part of this thesis is a search for compressed supersymmetric scenarios in events with missing transverse energy, jets and one isolated low-pT lepton in the final state using 4.7 fb-1 of ATLAS data collected at 7 TeV center-of-mass energy in 2011. No significant excess of events over the Standard Model expectation is observed and exclusion limits are derived for a number of supersymmetric models.
Pages
256 pages
Collection
Springer Theses
Parution
2014-06-11
Marque
Springer
EAN papier
9783319071350
EAN EPUB
9783319071367
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
8765 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
52,74 €

Suggestions personnalisées