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DYTurbo: fast predictions for Drell–Yan processes

Articolo
Data di Pubblicazione:
2020
Citazione:
DYTurbo: fast predictions for Drell–Yan processes / S. Camarda, M. Boonekamp, G. Bozzi, S. Catani, L. Cieri, J. Cuth, G. Ferrera, D. de Florian, A. Glazov, M. Grazzini, M.G. Vincter, M. Schott. - In: THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS. - ISSN 1434-6044. - 80:3(2020), pp. 251.1-251.15. [10.1140/epjc/s10052-020-7757-5]
Abstract:
Drell–Yan lepton pair production processes are extremely important for standard model (SM) precision tests and for beyond the SM searches at hadron colliders. Fast and accurate predictions are essential to enable the best use of the precision measurements of these processes; they are used for parton density fits, for the extraction of fundamental parameters of the SM, and for the estimation of background processes in searches. This paper describes a new numerical program, DYTurbo, for the calculation of the QCD transverse-momentum resummation of Drell–Yan cross sections up to next-to-next-to-leading logarithmic accuracy combined with the fixed-order results at next-to-next-to-leading order (O(αS2)), including the full kinematical dependence of the decaying lepton pair with the corresponding spin correlations and the finite-width effects. The DYTurbo program is an improved reimplementation of the DYqT, DYRes and DYNNLO programs, which provides fast and numerically precise predictions through the factorisation of the cross section into production and decay variables, and the usage of quadrature rules based on interpolating functions for the integration over kinematic variables.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
transverse-momentum resummation; double exponential formula; vector boson production; one-loop corrections; W-boson; radiative-corrections; root-S=13 TEV; lepton pairs; higgs-boson; distributions
Elenco autori:
S. Camarda, M. Boonekamp, G. Bozzi, S. Catani, L. Cieri, J. Cuth, G. Ferrera, D. de Florian, A. Glazov, M. Grazzini, M.G. Vincter, M. Schott
Autori di Ateneo:
FERRERA GIANCARLO ( autore )
Link alla scheda completa:
https://air.unimi.it/handle/2434/792825
Link al Full Text:
https://air.unimi.it/retrieve/handle/2434/792825/1653616/Camarda2020_Article_DYTurboFastPredictionsForDrell.pdf
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