Dijet Resonance Search with Weak Supervision Using root S=13 TeV pp Collisions in the ATLAS Detector
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Author
Aad, G.Abbott, B.
Abbott, D. C.
Abud, A. Abed
Abeling, K.
Abhayasinghe, D. K.
Abidi, S. H.
AbouZeid, O. S.
Abraham, N. L.
Abramowicz, H.
Abreu, H.
Abulaiti, Y.
Acharya, B. S.
Achkar, B.
Adam, L.
Bourdarios, C. Adam
Adamczyk, L.
Adamek, L.
Adelman, J.
Adersberger, M.
Adiguzel, A.
Adorni, S.
Adye, T.
Affolder, A. A.
Afik, Y.
Agapopoulou, C.
Agaras, M. N.
Aggarwal, A.
Agheorghiesei, C.
Aguilar-Saavedra, J. A.
Ahmad, A.
Ahmadov, F.
Ahmed, W. S.
Ai, X.
Aielli, G.
Akatsuka, S.
Akesson, T. P. A.
Akilli, E.
Akimov, A., V
Al Khoury, K.
Alberghi, G. L.
Albert, J.
Verzini, M. J. Alconada
Alderweireldt, S.
Aleksa, M.
Aleksandrov, I. N.
Alexa, C.
Alexopoulos, T.
Alfonsi, A.
Alfonsi, F.
Alhroob, M.
Ali, B.
Ali, S.
Aliev, M.
Alimonti, G.
Allaire, C.
Allbrooke, B. M. M.
Allen, B. W.
Allport, P. P.
Aloisio, A.
Alonso, F.
Alpigiani, C.
Alshehri, A. A.
Camelia, E. Alunno
Alvarez Estevez, M.
Alviggi, M. G.
Amaral Coutinho, Y.
Ambler, A.
Ambroz, L.
Amelung, C.
Amidei, D.
Amor Dos Santos, S. P.
Amoroso, S.
Amrouche, C. S.
An, F.
Anastopoulos, C.
Andari, N.
Andeen, T.
Anders, C. F.
Anders, J. K.
Andrean, S. Y.
Andreazza, A.
Andrei, V
Anelli, C. R.
Angelidakis, S.
Angerami, A.
Anisenkov, A., V
Annovi, A.
Antel, C.
Anthony, M. T.
Antipov, E.
Antonelli, M.
Antrim, D. J. A.
Anulli, F.
Aoki, M.
Aparisi Pozo, J. A.
Aparo, M. A.
Aperio Bella, L.
Araujo Ferraz, V
Araujo Pereira, R.
Arcangeletti, C.
Arce, A. T. H.
Arduh, F. A.
Arguin, J-F
Argyropoulos, S.
Arling, J-H
Armbruster, A. J.
Armstrong, A.
Arnaez, O.
Arnold, H.
Tame, Z. P. Arrubarrena
Artoni, G.
Artz, S.
Asai, S.
Asawatavonvanich, T.
Asbah, N.
Asimakopoulou, E. M.
Asquith, L.
Assahsah, J.
Assamagan, K.
Astalos, R.
Atkin, R. J.
Atkinson, M.
Atlay, N. B.
Atmani, H.
Augsten, K.
Avolio, G.
Ayoub, M. K.
Azuelos, G.
Bachacou, H.
Bachas, K.
Backes, M.
Backman, F.
Bagnaia, P.
Bahmani, M.
Bahrasemani, H.
Bailey, A. J.
Bailey, V. R.
Baines, J. T.
Bakalis, C.
Baker, O. K.
Bakker, P. J.
Gupta, D. Bakshi
Balaji, S.
Baldin, E. M.
Balek, P.
Balli, F.
Balunas, W. K.
Balz, J.
Banas, E.
Bandieramonte, M.
Bandyopadhyay, A.
Banerjee, Sw
Barak, L.
Barbe, W. M.
Barberio, E. L.
Barberis, D.
Barbero, M.
Barbour, G.
Barillari, T.
Barisits, M-S
Barkeloo, J.
Barklow, T.
Barnea, R.
Barnett, B. M.
Barnett, R. M.
Barnovska-Blenessy, Z.
Baroncelli, A.
Barone, G.
Barr, A. J.
Barranco Navarro, L.
Barreiro, F.
Guimaraes da Costa, J. Barreiro
Barron, U.
Barsov, S.
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Bartoldus, R.
Bartolini, G.
Barton, A. E.
Bartos, P.
Basalaev, A.
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Basso, M. J.
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Batley, J. R.
Batool, B.
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Beacham, J. B.
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Bechtle, P.
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Beck, H. P.
Becker, K.
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Bednyakov, V. A.
Bedognetti, M.
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Beermann, T. A.
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Behera, A.
Behr, J. K.
Beisiegel, F.
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Bella, G.
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Bellerive, A.
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Beloborodov, K.
Belotskiy, K.
Belyaev, N. L.
Benchekroun, D.
Benekos, N.
Benhammou, Y.
Benjamin, D. P.
Benoit, M.
Bensinger, J. R.
Bentvelsen, S.
Beresford, L.
Beretta, M.
Berge, D.
Kuutmann, E. Bergeaas
Berger, N.
Bergmann, B.
Bergsten, L. J.
Beringer, J.
Berlendis, S.
Bernardi, G.
Bernius, C.
Bernlochner, F. U.
Berry, T.
Berta, P.
Bertella, C.
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Bylund, O. Bessidskaia
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Bethani, A.
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Bevan, A. J.
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Biedermann, D.
Bielski, R.
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Biglietti, M.
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Madden, W. D. Breaden
Brendlinger, K.
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Briglin, D. L.
Britton, D.
Britzger, D.
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de Renstrom, P. A. Bruckman
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Schmidt-Sommerfeld, K. R.
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Schmitt, C.
Schmitt, S.
Schmoeckel, J. C.
Schoeffel, L.
Schoening, A.
Scholer, P. G.
Schopf, E.
Schott, M.
Schouwenberg, J. F. P.
Schovancova, J.
Schramm, S.
Schroeder, F.
Schulte, A.
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Schwemling, Ph
Affiliation
Univ Arizona, Dept PhysIssue Date
2020-09
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AMER PHYSICAL SOCCitation
Aad, G., Abbott, B., Abbott, D. C., Abed Abud, A., Abeling, K., Abhayasinghe, D. K., … & Zwalinski, L. (2020). Dijet resonance search with weak supervision using √ s= 13 TeV pp collisions in the ATLAS detector. Physical Review Letters, 125(13).Journal
PHYSICAL REVIEW LETTERSRights
© 2020 CERN, for the ATLAS Collaboration. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.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.Note
Open access articleISSN
0031-9007EISSN
1079-7114PubMed ID
33034503Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1103/PhysRevLett.125.131801
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Except where otherwise noted, this item's license is described as © 2020 CERN, for the ATLAS Collaboration. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license.
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Ye X, Yeletskikh I, Yexley MR, Yin P, Yorita K, Young CJS, Young C, Yuan M, Yuan R, Yue X, Zaazoua M, Zabinski B, Zacharis G, Zaid E, Zakareishvili T, Zakharchuk N, Zambito S, Zanzi D, Zaplatilek O, Zeißner SV, Zeitnitz C, Zeng JC, Zenger DT, Zenin O, Ženiš T, Zenz S, Zerradi S, Zerwas D, Zhang B, Zhang DF, Zhang G, Zhang J, Zhang K, Zhang L, Zhang M, Zhang R, Zhang S, Zhang X, Zhang X, Zhang Z, Zhao H, Zhao P, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng Z, Zhong D, Zhou B, Zhou C, Zhou H, Zhou N, Zhou Y, Zhu CG, Zhu C, Zhu HL, Zhu H, Zhu J, Zhu Y, Zhuang X, Zhukov K, Zhulanov V, Zieminska D, Zimine NI, Zimmermann S, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L, ATLAS Collaboration
- Issue date: 2023 Aug 11
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