@misc{10481/64564,
year = {2020},
month = {9},
url = {http://hdl.handle.net/10481/64564},
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 ∼ OðTeVÞ, mB;mC ∼
Oð100 GeVÞ 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 ffisffiffi
p
¼ 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 ¼ 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},
organization = {ANPCyT},
organization = {YerPhI, Armenia},
organization = {Australian Research Council},
organization = {BMWFW, Austria},
organization = {Austrian Science Fund (FWF)},
organization = {Azerbaijan National Academy of Sciences (ANAS)},
organization = {SSTC, Belarus},
organization = {National Council for Scientific and Technological Development (CNPq)},
organization = {Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)},
organization = {Natural Sciences and Engineering Research Council of Canada},
organization = {NRC, Canada},
organization = {CERN},
organization = {Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT)},
organization = {Chinese Academy of Sciences},
organization = {Ministry of Science and Technology, China},
organization = {National Natural Science Foundation of China (NSFC)},
organization = {Departamento Administrativo de Ciencia, Tecnologia e Innovacion Colciencias},
organization = {Ministry of Education, Youth & Sports - Czech Republic

Czech Republic Government},
organization = {Czech Republic Government},
organization = {DNRF, Denmark},
organization = {Danish Natural Science Research Council},
organization = {Centre National de la Recherche Scientifique (CNRS)},
organization = {CEA-DRF/IRFU, France},
organization = {SRNSFG, Georgia},
organization = {Federal Ministry of Education & Research (BMBF)},
organization = {HGF, Germany},
organization = {Max Planck Society},
organization = {Greek Ministry of Development-GSRT},
organization = {RGC, China},
organization = {Hong Kong SAR, China},
organization = {Israel Science Foundation},
organization = {Benoziyo Center, Israel},
organization = {Istituto Nazionale di Fisica Nucleare (INFN)},
organization = {Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT)},
organization = {Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT)

Japan Society for the Promotion of Science},
organization = {CNRST, Morocco},
organization = {Netherlands Organization for Scientific Research (NWO)

Netherlands Government},
organization = {RCN, Norway},
organization = {Ministry of Science and Higher Education, Poland},
organization = {NCN, Poland},
organization = {Portuguese Foundation for Science and Technology},
organization = {MNE/IFA, Romania},
organization = {MES of Russia},
organization = {NBC KI, Russia Federation},
organization = {JINR},
organization = {MESTD, Serbia},
organization = {MSS R, Slovakia},
organization = {Slovenian Research Agency - Slovenia},
organization = {Slovenia},
organization = {DST/NRF, South Africa},
organization = {MINECO, Spain},
organization = {SRC, Sweden},
organization = {Wallenberg Foundation, Sweden},
organization = {SERI, Switzerland},
organization = {Swiss National Science Foundation (SNSF)},
organization = {Canton of Bern, Switzerland},
organization = {Canton of Geneva, Switzerland},
organization = {Ministry of Science and Technology, Taiwan},
organization = {Ministry of Science and Technology, Taiwan},
organization = {Science & Technology Facilities Council (STFC)},
organization = {United States Department of Energy (DOE)},
organization = {National Science Foundation (NSF)},
organization = {BCKDF, Canada},
organization = {CANARIE, Canada},
organization = {Compute Canada, Canada},
organization = {CRC, Canada},
organization = {European Union (EU)

European Research Council (ERC)},
organization = {European Union (EU)},
organization = {Horizon 2020, European Union},
organization = {French National Research Agency (ANR)},
organization = {German Research Foundation (DFG)},
organization = {Alexander von Humboldt Foundation},
organization = {Herakleitos programme - EU-ESF},
organization = {Thales programme - EU-ESF},
organization = {Aristeia programme - EU-ESF},
organization = {Greek NS RF, Greece},
organization = {BSF-NSF, Israel},
organization = {German-Israeli Foundation for Scientific Research and Development},
organization = {CERCA Programme Generalitat de Catalunya, Spain},
organization = {PROMETEO Programme Generalitat Valenciana, Spain},
organization = {Goran Gustafssons Stiftelse, Sweden},
organization = {Royal Society of London},
organization = {Leverhulme Trust},
publisher = {Amer Physical Soc},
title = {Dijet Resonance Search with Weak Supervision Using ffisffi p =13 TeV pp Collisions in the ATLAS Detector},
doi = {10.1103/PhysRevLett.125.131801},
author = {Aad, G. and Aguilar Saavedra, Juan Antonio and Atlas Collaboration},
}