Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/9640
Title: Dijet Resonance Search with Weak Supervision Using root S=13 TeV pp Collisions in the ATLAS Detector
Authors: Aad, G.
Abbott, B.
Abbott, D. C.
Abud, A. Abed
Abeling, K.
Abhayasinghe, D. K.
Adamczyk, L.
Keywords: Mass
Distributions
Association
Photon
Jet
Issue Date: 2020
Publisher: Amer Physical Soc
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 m(A) similar to O(TeV), m(B), m(C) similar to 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 root 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 m(A), m(B), and m(C). For example, when m(A) = 3 TeV and m(B) greater than or similar to 200 GeV, a production cross section between 1 and 5 fb is excluded at 95% confidence level, depending on m(C). 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.
URI: https://doi.org/10.1103/PhysRevLett.125.131801
https://hdl.handle.net/20.500.11851/9640
ISSN: 0031-9007
1079-7114
Appears in Collections:PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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