Measurements Of Differential Z Gamma Jet X Cross Sections With The D0 Detector

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Measurements of Differential Z/gamma*+jet+X Cross Sections with the D0 Detector

We present measurements of differential cross sections in inclusive Z/[gamma]* plus jet production in a data sample of 1 fb−1 collected with the D0 detector in proton antiproton collisions at √s = 1.96 TeV. Measured variables include the Z/[gamma]* transverse momentum (p{sub T}{sup Z}) and rapidity (y{sup Z}), the leading jet transverse momentum (p{sub T}{sup jet}) and rapidity (y{sup jet}), as well as various angles of the Z+jet system. We compare the results to different Monte Carlo event generators and next-to-leading order perturbative QCD (NLO pQCD) predictions, with non-perturbative corrections applied.
Elementary Particle Physics

Author: Andrew J. Larkoski
language: en
Publisher: Cambridge University Press
Release Date: 2019-05-23
Introduces the fundamentals of particle physics with a focus on modern developments and an intuitive physical interpretation of results.
Measurements of Differential Cross Sections of Z/gamma*+jets+X Events in Proton Anti-proton Collisions at S**ư

We present cross section measurements for Z/?* + jets + X production, differential in the transverse momenta of the three leading jets. The data sample was collected with the D0 detector at the Fermilab Tevatron p{bar p} collider at a center-of-mass energy of 1.96 TeV and corresponds to an integrated luminosity of 1 fb−1. Leading and next-to-leading order perturbative QCD predictions are compared with the measurements, and agreement is found within the theoretical and experimental uncertainties. We also make comparisons with the predictions of four event generators. Two parton-shower-based generators show significant shape and normalization differences with respect to the data. In contrast, two generators combining tree-level matrix elements with a parton shower give a reasonable description of the shapes observed in data, but the predicted normalizations show significant differences with respect to the data, reflecting large scale uncertainties. For specific choices of scales, the normalizations for either generator can be made to agree with the measurements.