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Yuri Kulchitsky

Researcher at National Academy of Sciences of Belarus

Publications -  486
Citations -  47575

Yuri Kulchitsky is an academic researcher from National Academy of Sciences of Belarus. The author has contributed to research in topics: Large Hadron Collider & Higgs boson. The author has an hindex of 92, co-authored 369 publications receiving 43691 citations. Previous affiliations of Yuri Kulchitsky include Joint Institute for Nuclear Research & CERN.

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Measurement of the muon reconstruction performance of the ATLAS detector using 2011 and 2012 LHC proton–proton collision data

Georges Aad, +2873 more
TL;DR: In this paper, the performance of ATLAS muon reconstruction during the LHC run with pp collisions at root s = 7-8 TeV in 2011-2012, focusing mainly on data collected in 2012.
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Search for dark matter candidates and large extra dimensions in events with a jet and missing transverse momentum with the ATLAS detector

Georges Aad, +2934 more
- 12 Apr 2013 - 
TL;DR: In this paper, a search for new phenomena in events with a high-energy jet and large missing transverse momentum is performed using data from proton-proton collisions at root s = 7 TeV with the ATLAS experiment at the Large flatiron Collider.
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Search for an additional, heavy Higgs boson in the H → ZZ decay channel at √s = 8 TeV in pp collision data with the ATLAS detector

Georges Aad, +2841 more
- 25 Jan 2016 - 
TL;DR: In this article, a search for a high-mass Higgs boson in the,,, and decay modes using the ATLAS detector at the CERN Large Hadron Collider is presented.
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Combination of searches for invisible Higgs boson decays with the ATLAS experiment

Morad Aaboud, +2939 more
- 13 Jun 2019 - 
TL;DR: An exclusion limit on the H→invisible branching ratio of 0.26(0.17_{-0.05}^{+0.07}) at 95% confidence level is observed (expected) in combination with the results at sqrt[s]=7 and 8 TeV.
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Electron and photon performance measurements with the ATLAS detector using the 2015-2017 LHC proton-proton collision data

Georges Aad, +2965 more
- 10 Dec 2019 - 
TL;DR: In this article, an improved energy clustering algorithm is introduced, and its implications for the measurement and identification of prompt electrons and photons are discussed in detail, including corrections and calibrations that affect performance, including energy calibration, identification and isolation efficiencies.