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Oleksii Toldaiev

Researcher at Université libre de Bruxelles

Publications -  323
Citations -  16423

Oleksii Toldaiev is an academic researcher from Université libre de Bruxelles. The author has contributed to research in topics: Large Hadron Collider & Standard Model. The author has an hindex of 59, co-authored 323 publications receiving 13459 citations. Previous affiliations of Oleksii Toldaiev include Joint Institute for Nuclear Research.

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Particle-flow reconstruction and global event description with the CMS detector

Albert M. Sirunyan, +2215 more
TL;DR: A fully-fledged particle-flow reconstruction algorithm tuned to the CMS detector was developed and has been consistently used in physics analyses for the first time at a hadron collider as mentioned in this paper.
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Event generator tunes obtained from underlying event and multiparton scattering measurements

Vardan Khachatryan, +2286 more
TL;DR: Combined fits to CMS UE proton–proton data at 7TeV and to UEProton–antiproton data from the CDF experiment at lower s, are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton-proton collisions at 13.
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Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV

Khachatryan, +2288 more
TL;DR: In this paper, an improved jet energy scale corrections, based on a data sample corresponding to an integrated luminosity of 19.7 fb^(-1) collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 8 TeV, are presented.
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Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at s=13 TeV

Albert M. Sirunyan, +2358 more
TL;DR: In this paper, the performance of the modified system is studied using proton-proton collision data at center-of-mass energy √s=13 TeV, collected at the LHC in 2015 and 2016.
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Extraction and validation of a new set of CMS pythia8 tunes from underlying-event measurements

Albert M. Sirunyan, +2251 more
TL;DR: For the first time, predictions from pythia8 obtained with tunes based on NLO or NNLO PDFs are shown to reliably describe minimum-bias and underlying-event data with a similar level of agreement to predictions from tunes using LO PDF sets.