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Dorothee Schaile

Researcher at Ludwig Maximilian University of Munich

Publications -  1142
Citations -  88294

Dorothee Schaile is an academic researcher from Ludwig Maximilian University of Munich. The author has contributed to research in topics: Large Hadron Collider & Higgs boson. The author has an hindex of 128, co-authored 1031 publications receiving 81031 citations. Previous affiliations of Dorothee Schaile include Politehnica University of Bucharest & West University of Timișoara.

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Search for squarks and gluinos with the ATLAS detector in final states with jets and missing transverse momentum using 4.7 fb − 1 of s = 7 TeV proton-proton collision data

Georges Aad, +2916 more
- 22 Jan 2013 - 
TL;DR: In this paper, a search for squarks and gluinos in final states containing jets, missing transverse momentum and no high-p(T) electrons or muons is presented.
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Searches for Higgs boson pair production in the hh →bbττ, γγWW∗, γγbb, bbbb channels with the ATLAS detector

Georges Aad, +2911 more
- 05 Nov 2015 - 
TL;DR: In this article, both resonant and nonresonant Higgs boson pair production were performed in the hh -> bb tau tau, gamma gamma WW* final states using 20.3 fb(-1) of collision data at a center-of-m...
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Search for new phenomena in dijet mass and angular distributions from pp collisions at √s= 13 TeV with the ATLAS detector

Georges Aad, +2817 more
- 10 Mar 2016 - 
TL;DR: In this article, the authors describe a model-agnostic search for pairs of jets (dijets) produced by resonant and non-resonant phenomena beyond the Standard Model.
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Measurement of Bs0 Mixing Parameters from the Flavor-Tagged Decay Bs0→J/ψ

V. M. Abazov, +541 more
TL;DR: In this paper, the authors obtained the width difference between the B-s(0) light and heavy mass eigenstates, Delta Gamma(s)=0.19 +/- 0.07(stat), and the CP-violating phase, phi(s)=-0.57(-0.30)(+0.24) ps(-1), and -1.20
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Search for the Standard Model Higgs boson produced in association with top quarks and decaying into bb¯ in pp collisions at √s = 8 TeV with the ATLAS detector

Georges Aad, +2816 more
TL;DR: In this paper, a neural network is used to discriminate between signal and background events, the latter being dominated by +jets production, and an observed (expected) limit of 3.4 (2.2) times the Standard Model cross section is obtained at 95 % confidence level.