A simultaneous unbinned differential cross section measurement of twenty-four $Z$+jets 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 re-use in a variety of contexts and for new observables to be constructed from the twenty-four measured observables.

41 pages in total, author list starting on page 24, 8 figures, 0 tables, published in PRL. All figures including auxiliary figures are available at http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2020-17. Version 2 includes an updated link to the public Gitlab repository

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• A Practical Guide to Unbinned Unfolding
• How to Unfold Top Decays
• TOP2024: an overview of experimental results
• Tools for Unbinned Unfolding
• Machine learning in top quark physics at ATLAS and CMS