Daniel Reichelt daniel.reichelt@durham.ac.uk
Post Doctoral Research Associate
Daniel Reichelt daniel.reichelt@durham.ac.uk
Post Doctoral Research Associate
Simone Caletti
Oleh Fedkevych
Simone Marzani
Steffen Schumann
Gregory Soyez
We compute resummed and matched predictions for jet angularities in hadronic dijet and Z+jet events with and without grooming the candidate jets using the SoftDrop technique. Our theoretical predictions also account for non-perturbative corrections from the underlying event and hadronisation through parton-to-hadron level transfer matrices extracted from dedicated Monte Carlo simulations with Sherpa. Thanks to this approach we can account for non-perturbative migration effects in both the angularities and the jet transverse momentum. We compare our predictions against recent measurements from the CMS experiment. This allows us to test the description of quark- and gluon-jet enriched phase-space regions separately. We supplement our study with Sherpa results based on the matching of NLO QCD matrix elements with the parton shower. Both theoretical predictions offer a good description of the data, within the experimental and theoretical uncertainties. The latter are however sizeable, motivating higher-accuracy calculations.
Reichelt, D., Caletti, S., Fedkevych, O., Marzani, S., Schumann, S., & Soyez, G. (2022). Phenomenology of jet angularities at the LHC. Journal of High Energy Physics, 2022(3), Article 131. https://doi.org/10.1007/jhep03%282022%29131
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 1, 2022 |
Online Publication Date | Mar 21, 2022 |
Publication Date | 2022-03 |
Deposit Date | Jan 12, 2022 |
Publicly Available Date | May 5, 2022 |
Journal | Journal of High Energy Physics |
Print ISSN | 1126-6708 |
Electronic ISSN | 1029-8479 |
Publisher | Scuola Internazionale Superiore di Studi Avanzati (SISSA) |
Peer Reviewed | Peer Reviewed |
Volume | 2022 |
Issue | 3 |
Article Number | 131 |
DOI | https://doi.org/10.1007/jhep03%282022%29131 |
Public URL | https://durham-repository.worktribe.com/output/1220743 |
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This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited.
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