Search for new physics using effective field theory in 13 TeV pp collision events that contain a top quark pair and a boosted Z or Higgs boson
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URI: https://hdl.handle.net/10902/32092ISSN: 1550-7998
ISSN: 1550-2368
ISSN: 2470-0010
ISSN: 2470-0029
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Tumasyan, A.; Brochero Cifuentes, Javier Andrés













Fecha
2023-08Derechos
Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3
Publicado en
Physical Review D, 2023, 108(3), 032008
Editorial
American Physical Society
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Resumen/Abstract
A data sample containing top quark pairs (tt¯) produced in association with a Lorentz-boosted Z or Higgs boson is used to search for signs of new physics using effective field theory. The data correspond to an integrated luminosity of 138 fb-1 of proton-proton collisions produced at a center-of-mass energy of 13 TeV at the LHC and collected by the CMS experiment. Selected events contain a single lepton and hadronic jets, including two identified with the decay of bottom quarks, plus an additional large-radius jet with high transverse momentum identified as a Z or Higgs boson decaying to a bottom quark pair. Machine learning techniques are employed to discriminate between t¯tZ or t¯tH events and events from background processes, which are dominated by t¯t+jets production. No indications of new physics are observed. The signal strengths of boosted
t¯tZ and t¯tH production are measured, and upper limits are placed on the t¯t Z and t¯tH differential cross sections as functions of the Z or Higgs boson transverse momentum. The effects of new physics are probed using a framework in which the standard model is considered to be the low-energy effective field theory of a higher energy scale theory. Eight possible dimension-six operators are added to the standard model Lagrangian, and their corresponding coefficients are constrained via fits to the data.
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