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. / Aad, G; Berry, Tracey; Blanco, Jacobo; Boisvert, Veronique; Brooks, Timothy; Connelly, Ian; Cowan, Glen; Duguid, Liam; Faucci Giannelli, Michele; George, Simon; Gibson, Stephen; Kempster, Jacob; Panduro Vazquez, Jose G; Pastore, Francesca; Savage, Graham; Spano, Francesco; Teixeira-Dias, Pedro; Thomas-Wilsker, Joshuha; The ATLAS Collaboration .

In: European Physical Journal C: Particles and Fields, Vol. 75, 349, 29.07.2015, p. 1-50.

Research output: Contribution to journalArticlepeer-review




A search for the Standard Model Higgs boson produced in association with a top-quark pair, tt¯H, is presented. The analysis uses 20.3 fb−1 of pp collision data at s√=8TeV, collected with the ATLAS detector at the Large Hadron Collider during 2012. The search is designed for the H→bb¯ decay mode and uses events containing one or two electrons or muons. In order to improve the sensitivity of the search, events are categorised according to their jet and b-tagged jet multiplicities. A neural network is used to discriminate between signal and background events, the latter being dominated by tt¯+jets production. In the single-lepton channel, variables calculated using a matrix element method are included as inputs to the neural network to improve discrimination of the irreducible tt¯+bb¯ background. No significant excess of events above the background expectation is found and an observed (expected) limit of 3.4 (2.2) times the Standard Model cross section is obtained at 95 % confidence level. The ratio of the measured tt¯H signal cross section to the Standard Model expectation is found to be μ=1.5±1.1 assuming a Higgs boson mass of 125GeV.
Original languageEnglish
Article number349
Pages (from-to)1-50
Number of pages50
JournalEuropean Physical Journal C: Particles and Fields
Publication statusPublished - 29 Jul 2015
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 25746124