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Andrey Popov

Researcher at Université libre de Bruxelles

Publications -  1328
Citations -  68160

Andrey Popov is an academic researcher from Université libre de Bruxelles. The author has contributed to research in topics: Large Hadron Collider & Lepton. The author has an hindex of 113, co-authored 1184 publications receiving 60015 citations. Previous affiliations of Andrey Popov include University of Siena & University of Trento.

Papers
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Measurement of prompt J/ψ pair production in pp collisions at √s = 7 Tev

Vardan Khachatryan, +2196 more
- 17 Sep 2014 - 
TL;DR: In this article, the high transverse-momentum region of J/psi meson pair production is measured in a phase space defined by the individual J/Psi transverse momentum and rapidity.
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Measurement of the Splitting Function in pp and Pb-Pb Collisions at sNN =5.02 TeV

Albert M. Sirunyan, +2235 more
- 03 Apr 2018 - 
TL;DR: The momentum ratio of the two leading partons, resolved as subjets, provides information about the parton shower evolution and indicates a more unbalanced momentum ratio in central PbPb and pp collisions.
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Model-independent measurement of t-channel single top quark production in pp¯ collisions at s=1.96 TeV

V. M. Abazov, +428 more
- 17 Nov 2011 - 
TL;DR: In this article, a model-independent measurement of the electroweak production of single top quarks in collisions at the Fermilab Tevatron was presented, where the probability of the background to fluctuate and produce a signal as large as the one observed is $1.6\times10^{-8}, corresponding to a significance of 5.5 standard deviations.
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Search for resonant and nonresonant new phenomena in high-mass dilepton final states at √s = 13 TeV

Albert M. Sirunyan, +2407 more
- 27 Jul 2021 - 
TL;DR: In this paper, a data set of proton-proton collisions collected by the CMS experiment at the LHC at s = 13 TeV from 2016 to 2018 corresponding to a total integrated luminosity of up to 140 fb−1 is analyzed.
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Identification of Heavy, Energetic, Hadronically Decaying Particles Using Machine-Learning Techniques

Albert M. Sirunyan, +2305 more
- 03 Jun 2020 - 
TL;DR: In this article, machine learning techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks.