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Monica Dunford

Researcher at Heidelberg University

Publications -  1024
Citations -  85184

Monica Dunford is an academic researcher from Heidelberg University. The author has contributed to research in topics: Large Hadron Collider & Higgs boson. The author has an hindex of 129, co-authored 906 publications receiving 77571 citations. Previous affiliations of Monica Dunford include Polish Academy of Sciences & Politehnica University of Bucharest.

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Measurement of the top-quark mass using a leptonic invariant mass in pp collisions at $$ \sqrt{s} $$ = 13 TeV with the ATLAS detector

Georges Aad, +2835 more
TL;DR: In this article , a measurement of the top-quark mass in the $t\bar{t}\rightarrow~\textrm{lepton}+\textm{jets}$ channel is presented, with an experimental technique which exploits semileptonic decays of $b$-hadrons produced in the topquark decay chain.
Journal ArticleDOI

Measurement of electroweak $$ Z\left(\nu \overline{\nu}\right)\gamma jj $$ production and limits on anomalous quartic gauge couplings in pp collisions at $$ \sqrt{s} $$ = 13 TeV with the ATLAS detector

Georges Aad, +2812 more
TL;DR: In this article , the electroweak production at the Large Hadron Collider (LHC) was studied in a regime with a photon of high transverse momentum above 150 GeV using proton-proton collisions at a centre-of-mass energy of 13 TeV at the LHC.

Search for diphoton events with large missing transverse momentum in 1 fb[superscript -1] of 7 TeV proton–proton collision data with the ATLAS detector

Georges Aad, +2989 more
TL;DR: A Aad et al. as mentioned in this paper search for diphoton events with large missing transverse momentum in 1 fb[superscript -1] of 7 TeV Proton-proton Collision Data with the ATLAS Detector.

Operation and performance of the ATLAS semiconductor tracker in LHC Run 2

Georges Aad, +2891 more
TL;DR: The semiconductor tracker (SCT) is one of the tracking systems for charged particles in the ATLAS detector as discussed by the authors , and it consists of 4088 silicon strip sensor modules, which achieved a data-quality efficiency of 99.85%.