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| Verfasst von: | Aad, Georges [VerfasserIn]  |
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| | Andrei, George Victor [VerfasserIn] |
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| | Bartels, Falk [VerfasserIn] |
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| | Bolz, Arthur [VerfasserIn] |
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| | Czurylo, Marta [VerfasserIn] |
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| | Dunford, Monica [VerfasserIn] |
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| | Ferreira de Lima, Danilo Enoque [VerfasserIn] |
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| | Franchino, Silvia [VerfasserIn] |
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| | Jongmanns, Jan [VerfasserIn] |
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| | Klassen, Martin [VerfasserIn] |
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| | Krishnan, Anjali [VerfasserIn] |
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| | Mkrtchyan, Tigran [VerfasserIn] |
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| | Napolitano, Fabrizio [VerfasserIn] |
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| | Ott, Philipp [VerfasserIn] |
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| | Schöning, André [VerfasserIn] |
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| | Schultz-Coulon, Hans-Christian [VerfasserIn] |
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| | Spieker, Thomas [VerfasserIn] |
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| | Stamen, Rainer [VerfasserIn] |
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| | Starovoitov, Pavel [VerfasserIn] |
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| | Vigani, Luigi [VerfasserIn] |
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| | Weber, Sebastian [VerfasserIn] |
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| | Wessels, Martin [VerfasserIn] |
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| | Yue, Xiaoguang [VerfasserIn] |
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| Titel: | Dijet resonance search with weak supervision using √s=13TeV pp Collisionsin the ATLAS Detector |
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| Körperschaft: | ATLAS Collaboration [VerfasserIn] |
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| Verf.angabe: | the ATLAS Collaboration |
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| E-Jahr: | 2020 |
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| Jahr: | 21 September 2020 |
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| Fussnoten: | The ATLAS Collaboration: G. Aad, V. Andrei, F. Bartels, A.E. Bolz, M. Czurylo, M. Dunford, D.E. Ferreira de Lima, S. Franchino, J. Jongmanns, M. Klassen, A. Krihnan, T. Mkrtchyan, F. Napolitano, P.S. Ott, A. Schöning, H.-C. Schultz-Coulon, T.M. Spieker, R. Stamen, P. Starovoitov, L. Vigani, S. Weber, M. Wessels, X. Yue [und 2898 weitere] ; Im Titel steht der Buchstabe s unter dem Wurzelsymbol ; Gesehen am 02.11.2020 |
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| Titel Quelle: | Enthalten in: Physical review letters |
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| Ort Quelle: | College Park, Md. : APS, 1958 |
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| Jahr Quelle: | 2020 |
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| Band/Heft Quelle: | 125(2020,13) Artikel-Nummer 131801, 23 Seiten |
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| ISSN Quelle: | 1079-7114 |
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| Abstract: | This Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on signal simulations for developing the analysis selection. Weakly supervised learning is used to train classifiers directly on data to enhance potential signals. The targeted topology is dijet events and the features used for machine learning are the masses of the two jets. The resulting analysis is essentially a three-dimensional search A→BC, for mA∼O(TeV), mB,mC∼O(100 GeV) and B, C are reconstructed as large-radius jets, without paying a penalty associated with a large trials factor in the scan of the masses of the two jets. The full run 2 √s=13 TeV pp collision dataset of 139 fb−1 recorded by the ATLAS detector at the Large Hadron Collider is used for the search. There is no significant evidence of a localized excess in the dijet invariant mass spectrum between 1.8 and 8.2 TeV. Cross-section limits for narrow-width A, B, and C particles vary with mA, mB, and mC. For example, when mA=3 TeV and mB≳200 GeV, a production cross section between 1 and 5 fb is excluded at 95% confidence level, depending on mC. For certain masses, these limits are up to 10 times more sensitive than those obtained by the inclusive dijet search. These results are complementary to the dedicated searches for the case that B and C are standard model bosons. |
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| DOI: | doi:10.1103/PhysRevLett.125.131801 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext ; Verlag: https://doi.org/10.1103/PhysRevLett.125.131801 |
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| | Volltext: https://link.aps.org/doi/10.1103/PhysRevLett.125.131801 |
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| | DOI: https://doi.org/10.1103/PhysRevLett.125.131801 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| K10plus-PPN: | 1737531380 |
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| Verknüpfungen: | → Zeitschrift |
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Dijet resonance search with weak supervision using √s=13TeV pp Collisionsin the ATLAS Detector / Aad, Georges [VerfasserIn]; 21 September 2020 (Online-Ressource)
