Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Simultaneous Unbinned Differential Cross-Section Measurement of Twenty-Four Z+jets Kinematic Observables with the ATLAS Detector
AU - The ATLAS collaboration
AU - Ali, Hanadi
AU - Alsolami, Zainab
AU - Barton, A.E.
AU - Borissov, G.
AU - Bouhova-Thacker, E.V.
AU - Ferguson, Ruby
AU - Ferrando, James
AU - Fox, H.
AU - Hagan, Alina
AU - Henderson, R.C.W.
AU - Jones, R.W.L.
AU - Kartvelishvili, V.
AU - Love, P.A.
AU - Marshall, E.J.
AU - Meng, L.
AU - Muenstermann, D.
AU - Ribaric, N.
AU - Sampson, Elliot
AU - Smizanska, M.
AU - Spinali, S.
AU - Wharton, A.M.
PY - 2024/12/30
Y1 - 2024/12/30
N2 - Z boson events at the Large Hadron Collider can be selected with high purity and are sensitive to a diverse range of QCD phenomena. As a result, these events are often used to probe the nature of the strong force, improve Monte Carlo event generators, and search for deviations from standard model predictions. All previous measurements of Z boson production characterize the event properties using a small number of observables and present the results as differential cross sections in predetermined bins. In this analysis, a machine learning method called is used to produce a simultaneous measurement of twenty-four Z+jets observables using 139 fb−1 of proton-proton collisions at s=13 TeV collected with the ATLAS detector. Unlike any previous fiducial differential cross-section measurement, this result is presented unbinned as a dataset of particle-level events, allowing for flexible reuse in a variety of contexts and for new observables to be constructed from the twenty-four measured observables. © 2024 CERN, for the ATLAS Collaboration 2024 CERN
AB - Z boson events at the Large Hadron Collider can be selected with high purity and are sensitive to a diverse range of QCD phenomena. As a result, these events are often used to probe the nature of the strong force, improve Monte Carlo event generators, and search for deviations from standard model predictions. All previous measurements of Z boson production characterize the event properties using a small number of observables and present the results as differential cross sections in predetermined bins. In this analysis, a machine learning method called is used to produce a simultaneous measurement of twenty-four Z+jets observables using 139 fb−1 of proton-proton collisions at s=13 TeV collected with the ATLAS detector. Unlike any previous fiducial differential cross-section measurement, this result is presented unbinned as a dataset of particle-level events, allowing for flexible reuse in a variety of contexts and for new observables to be constructed from the twenty-four measured observables. © 2024 CERN, for the ATLAS Collaboration 2024 CERN
U2 - 10.1103/physrevlett.133.261803
DO - 10.1103/physrevlett.133.261803
M3 - Journal article
VL - 133
JO - Physical review letters
JF - Physical review letters
SN - 1079-7114
IS - 26
M1 - 261803
ER -