A simultaneous unbinned differential cross section measurement of twenty-four +jets kinematic observables with the ATLAS detector
arXiv:2405.20041 · doi:10.1103/PhysRevLett.133.261803
Abstract
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 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 +jets observables using fb of proton-proton collisions at 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.
arXiv comment41 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
References in corpus (55)
- The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations
- The anti-k_t jet clustering algorithm
- An Introduction to PYTHIA 8.2
- A Brief Introduction to PYTHIA 8.1
- FastJet user manual
- A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX
- Parton distributions for the LHC Run II
- Herwig++ Physics and Manual
- The ATLAS Simulation Infrastructure
- Parton distributions in the LHC era: MMHT 2014 PDFs
- Event Generation with Sherpa 2.2
- Identifying Boosted Objects with N-subjettiness
- Performance of the ATLAS Trigger System in 2015
- Merging meets matching in MC@NLO
- Electroweak gauge boson production at hadron colliders through O(alpha_s^2)
- SVD Approach to Data Unfolding
- Measurement of the boson transverse momentum distribution in collisions at = 7 TeV with the ATLAS detector
- Maximizing Boosted Top Identification by Minimizing N-subjettiness
- Muon reconstruction and identification efficiency in ATLAS using the full Run 2 collision data set at TeV
- Jet Substructure at the Large Hadron Collider: A Review of Recent Advances in Theory and Machine Learning
- Performance of the ATLAS muon triggers in Run 2
- Jet Substructure at the Large Hadron Collider: Experimental Review
- OmniFold: A Method to Simultaneously Unfold All Observables
- TUnfold: an algorithm for correcting migration effects in high energy physics
- Measurement of the production cross section of jets in association with a Z boson in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector
- Studies of jet mass in dijet and W/Z + jet events
- Invertible Networks or Partons to Detector and Back Again
- Unsafe but Calculable: Ratios of Angularities in Perturbative QCD
- How to GAN away Detector Effects
- Measurement of inclusive jet and dijet cross-sections in proton-proton collisions at TeV with the ATLAS detector
- Measurements of jet multiplicity and differential production cross sections of Z + jets events in proton-proton collisions at sqrt(s) = 7 TeV
- Measurements of the production cross section of a boson in association with jets in pp collisions at TeV with the ATLAS detector
- A Neural Resampler for Monte Carlo Reweighting with Preserved Uncertainties
- Measurements of the differential jet cross section as a function of the jet mass in dijet events from proton-proton collisions at 13 TeV
- Measurement of the Drell--Yan triple-differential cross section in collisions at TeV
- Presenting Unbinned Differential Cross Section Results
- Learning to Simulate High Energy Particle Collisions from Unlabeled Data
- Measurement of the triple-differential dijet cross section in proton-proton collisions at sqrt(s) = 8 TeV and constraints on parton distribution functions
- Differential cross-section measurements for the electroweak production of dijets in association with a boson in proton-proton collisions at ATLAS
- Measurement of Z/gamma*+jet+X angular distributions in ppbar collisions at sqrt{s}=1.96 TeV
- Electroweak production of two jets in association with a Z boson in proton-proton collisions at 13 TeV
- Study of quark and gluon jet substructure in Z+jet and dijet events from pp collisions
- Modelling and computational improvements to the simulation of single vector-boson plus jet processes for the ATLAS experiment
- Measurement of charged hadron production in -tagged jets in proton-proton collisions at TeV
- Disentangling Quarks and Gluons with CMS Open Data
- Measurements of differential production cross sections for a Z boson in association with jets in pp collisions at sqrt(s) = 8 TeV
- Measurement of differential production cross section for bosons in association with jets in collisions at TeV
- Improving Generative Model-based Unfolding with Schrödinger Bridges
- Multidifferential study of identified charged hadron distributions in -tagged jets in proton-proton collisions at 13 TeV
- Unbinned Deep Learning Jet Substructure Measurement in High ep collisions at HERA
- Unbinned Profiled Unfolding
- Measurement of the splitting scales in events in collisions at TeV with the ATLAS detector
- Cross-section measurements for the production of a boson in association with high-transverse-momentum jets in collisions at TeV with the ATLAS detector
- Measurement of differential cross sections for the production of a Z boson in association with jets in proton-proton collisions at = 13 TeV
- Azimuthal correlations in Z+jets events in proton-proton collisions at = 13 TeV
Cited by in corpus (9)
- An implementation of neural simulation-based inference for parameter estimation in ATLAS
- Describing Hadronization via Histories and Observables for Monte-Carlo Event Reweighting
- Generative Unfolding with Distribution Mapping
- Machine Learning-Assisted Unfolding for Neutrino Cross-section Measurements with the OmniFold Technique
- 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