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Type: Journal article
Title: Improved Limits on Millicharged Particles Using the ArgoNeuT Experiment at Fermilab
Other Titles: Dijet resonance search with weak supervision using root S=13 TeV pp collisions in the ATLAS detector
Author: Acciarri, R.
Adams, C.
Asaadi, J.
Baller, B.
Bolton, T.
Bromberg, C.
Cavanna, F.
Edmunds, D.
Fitzpatrick, R.S.
Fleming, B.
Harnik, R.
James, C.
Lepetic, I.
Littlejohn, B.R.
Liu, Z.
Luo, X.
Palamara, O.
Scanavini, G.
Soderberg, M.
Spitz, J.
et al.
Citation: Physical Review Letters, 2020; 124(13):1-6
Publisher: American Physical Society (APS)
Issue Date: 2020
ISSN: 0031-9007
Statement of
G. Aad, B. Abbott, D. C. Abbott, A. Abed Abud, K. Abeling, D. K. Abhayasinghe ... et al.
Abstract: This Letter describes a search for resonant new physics using a machine-learning anomaly detection procedure that does not rely on a signal model hypothesis. 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 $A\rightarrow BC$, for $m_A\sim\mathcal{O}(\text{TeV})$, $m_B,m_C\sim\mathcal{O}(100\text{ GeV})$ 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 $\sqrt{s}=13$ TeV $pp$ collision data set 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 $m_B\gtrsim 200$ 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.
Keywords: ATLAS Collaboration
Rights: © 2020 CERN, for the ATLAS Collaboration. 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.
DOI: 10.1103/physrevlett.124.131801
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