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Paolo Mastrandrea

Researcher at University of Pisa

Publications -  335
Citations -  37367

Paolo Mastrandrea is an academic researcher from University of Pisa. The author has contributed to research in topics: Large Hadron Collider & Lepton. The author has an hindex of 83, co-authored 335 publications receiving 32774 citations. Previous affiliations of Paolo Mastrandrea include Stony Brook University & University of Grenoble.

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Muon reconstruction performance of the ATLAS detector in proton–proton collision data at √ s =13 TeV

Georges Aad, +2831 more
- 23 May 2016 - 
TL;DR: In this article, the performance of the ATLAS muon identification and reconstruction using the first LHC dataset recorded at s√ = 13 TeV in 2015 was evaluated using the Monte Carlo simulations.
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Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1

Georges Aad, +2891 more
- 24 Jul 2017 - 
TL;DR: Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS and is exploited to apply a local energy calibration and corrections depending on the nature of the cluster.
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Performance of the ATLAS Trigger System in 2010

Georges Aad, +5595 more
- 03 Jan 2012 - 
TL;DR: The ATLAS trigger system as discussed by the authors selects events by rapidly identifying signatures of muon, electron, photon, tau lepton, jet, and B meson candidates, as well as using global event signatures, such as missing transverse energy.
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Search for high-mass dilepton resonances in pp collisions at s =8 TeV with the ATLAS detector

Georges Aad, +2921 more
- 19 Sep 2014 - 
TL;DR: In this paper, the ATLAS detector at the Large Hadron Collider is used to search for high-mass resonances decaying to dielectron or dimuon final states.
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Performance of $b$-Jet Identification in the ATLAS Experiment

Georges Aad, +2815 more
- 04 Apr 2016 - 
TL;DR: In this paper, an independent b-tagging algorithm based on the reconstruction of muons inside jets as well as the b tagging algorithm used in the online trigger are also presented.