0000000000419977
AUTHOR
A. L.s. Schorlemmer
A neural network clustering algorithm for the ATLAS silicon pixel detector
A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. …
Search for displaced muonic lepton jets from light Higgs boson decay in proton–proton collisions at s=7 TeV with the ATLAS detector
A search is performed for collimated muon pairs displaced from the primary vertex produced in the decay of long-lived neutral particles in proton-proton collisions at root s = 7 TeV centre-of-mass ...
Search for charged Higgs bosons through the violation of lepton universality in t(t)over-bar events using pp collision data at root s=7 TeV with the ATLAS experiment
In several extensions of the Standard Model, the top quark can decay into a bottom quark and a light charged Higgs boson H [superscript +], t → bH [superscript +], in addition to the Standard Model decay t → bW. Since W bosons decay to the three lepton generations equally, while H [superscript +] may predominantly decay into τν, charged Higgs bosons can be searched for using the violation of lepton universality in top quark decays. The analysis in this paper is based on 4.6 fb[superscript −1] of proton-proton collision data at √s = 7 TeV collected by the ATLAS experiment at the Large Hadron Collider. Signatures containing leptons (e or μ) and/or a hadronically decaying τ (τ [subscript had])…