Simultaneous Unbinned Differential Cross-Section Measurement of Twenty-Four <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>Z</mml:mi> <mml:mo>+</mml:mo> <mml:mtext>jets</mml:mtext> </mml:mrow> </mml:math> Kinematic Observables with the ATLAS Detector

Abstract

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 omnifold is used to produce a simultaneous measurement of twenty-four Z+jets observables using 139 fb^{-1} of proton-proton collisions at sqrt[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.