Reconstruction and identification of boosted di-τ systems in a search for Higgs boson pairs using 13 TeV proton-proton collision data in ATLAS
In this paper, a new technique for reconstructing and identifying hadronically decaying τ+τ− pairs with a large Lorentz boost, referred to as the di-τ tagger, is developed and used for the first time in the ATLAS experiment at the Large Hadron Collider. A benchmark di-τ tagging selection is employed...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Corporate Author: | |
| Format: | Article (Journal) |
| Language: | English |
| Published: |
30 November 2020
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| In: |
Journal of high energy physics
Year: 2020, Issue: 11, Pages: 1-47 |
| ISSN: | 1029-8479 |
| DOI: | 10.1007/JHEP11(2020)163 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1007/JHEP11(2020)163
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| Author Notes: | the ATLAS collaboration |
| Summary: | In this paper, a new technique for reconstructing and identifying hadronically decaying τ+τ− pairs with a large Lorentz boost, referred to as the di-τ tagger, is developed and used for the first time in the ATLAS experiment at the Large Hadron Collider. A benchmark di-τ tagging selection is employed in the search for resonant Higgs boson pair production, where one Higgs boson decays into a boosted $$ b\overline{b} $$pair and the other into a boosted τ+τ− pair, with two hadronically decaying τ-leptons in the final state. Using 139 fb−1 of proton-proton collision data recorded at a centre-of-mass energy of 13 TeV, the efficiency of the di-τ tagger is determined and the background with quark- or gluon-initiated jets misidentified as di-τ objects is estimated. The search for a heavy, narrow, scalar resonance produced via gluon-gluon fusion and decaying into two Higgs bosons is carried out in the mass range 1-3 TeV using the same dataset. No deviations from the Standard Model predictions are observed, and 95% confidence-level exclusion limits are set on this model. |
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| Item Description: | The ATLAS collaboration: G. Aad, G.V. Andrei, F. Bartels, M. Dunford, S. Franchino, J. Jongmanns, M. Klassen, A. Krishnan, T. Mkrtchyan, F. Napolitano, P. Ott, A. Schoening, H-C. Schultz-Coulon, T.M. Spieker, R. Stamen, P. Starovoitov, S. Suchek, L. Vigani, S.M. Weber, M. Wessels, X. Yue [und viele weitere] Gesehen am 10.01.2022 |
| Physical Description: | Online Resource |
| ISSN: | 1029-8479 |
| DOI: | 10.1007/JHEP11(2020)163 |