Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at √s = 13 TeV with the ATLAS Detector

The ATLAS collaboration

doi:10.1103/PhysRevLett.132.081801

Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at √s = 13 TeV with the ATLAS Detector

The ATLAS collaboration

School of Physics and Astronomy

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140 fb⁻¹ of pp collisions at √s ¼ 13 TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e; μ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

Original language	English
Article number	081801
Journal	Physical Review Letters
Volume	132
Issue number	8
DOIs	https://doi.org/10.1103/PhysRevLett.132.081801
State	Published - 23 Feb 2024

Funding

Funders	Funder number
BSF-NSF
CEA-DRF
Cantons of Bern and Geneva
DNSRC	IN2P3-CNRS
EU-ESF
GenT Programmes Generalitat Valenciana, Spain
GridKA
Horizon 2020, ICSC-NextGenerationEU
INFN-CNAF
La Caixa Banking Foundation
MIZŠ
MNE
NDGF	CC-IN2P3
Norwegian Financial Mechanism	2014-2021
PROMETEO
RGC
UNCE	SCI/013
Wallenberg Foundation
U.S. Department of Energy
Alexander von Humboldt-Stiftung
Alabama Space Grant Consortium
Brookhaven National Laboratory
CRC Health Group	21/SCI/017
CRC Health Group
Canarie
Karlsruhe Institute of Technology
H2020 Marie Skłodowska-Curie Actions
Multiple Sclerosis Scientific Research Foundation
CERN
Compute Canada
Göran Gustafssons Stiftelser
Natural Sciences and Engineering Research Council of Canada
National Research Council Canada
Canada Foundation for Innovation
Science and Technology Facilities Council
Leverhulme Trust
European Research Council
European Cooperation in Science and Technology
Australian Research Council
National Stroke Foundation
Neurosurgical Research Foundation
Helmholtz-Gemeinschaft
Minerva Foundation
Deutsche Forschungsgemeinschaft
Agence Nationale de la Recherche
Japan Society for the Promotion of Science
Ministry of Education, Culture, Sports, Science and Technology
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Danmarks Grundforskningsfond
Fundação de Amparo à Pesquisa do Estado de São Paulo
National Natural Science Foundation of China
Ministerstvo Školství, Mládeže a Tělovýchovy
Fundação para a Ciência e a Tecnologia
Bundesministerium für Bildung und Forschung
Chinese Academy of Sciences
Austrian Science Fund
Generalitat de Catalunya
Ministry of Science and Technology of the People's Republic of China
Agencia Nacional de Promoción Científica y Tecnológica
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Bundesministerium für Wissenschaft, Forschung und Wirtschaft
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Nella and Leon Benoziyo Center for Neurological Diseases, Weizmann Institute of Science
Israel Science Foundation
Instituto Nazionale di Fisica Nucleare
Narodowe Centrum Nauki
Javna Agencija za Raziskovalno Dejavnost RS
Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja
Ministerio de Ciencia e Innovación
Centre National pour la Recherche Scientifique et Technique
Staatssekretariat für Bildung, Forschung und Innovation
British Columbia Knowledge Development Fund
European Regional Development Fund
Defence Science Institute
Narodowa Agencja Wymiany Akademickiej
Institutul de Fizică Atomică
Agencia Nacional de Investigación y Desarrollo
Royal Society of South Australia
Irish Rugby Football Union

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10.1103/PhysRevLett.132.081801

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@article{33c237a7745942149ba8076539421edf,

title = "Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at √s = 13 TeV with the ATLAS Detector",

abstract = "Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140 fb−1 of pp collisions at √s ¼ 13 TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e; μ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.",

author = "{The ATLAS collaboration} and G. Aad and B. Abbott and Abbott, {D. C.} and {Abed Abud}, A. and K. Abeling and Abhayasinghe, {D. K.} and Abidi, {S. H.} and A. Aboulhorma and H. Abramowicz and H. Abreu and Y. Abulaiti and {Abusleme Hoffman}, {A. C.} and Acharya, {B. S.} and B. Achkar and L. Adam and {Adam Bourdarios}, C. and L. Adamczyk and L. Adamek and Addepalli, {S. V.} and J. Adelman and A. Adiguzel and S. Adorni and T. Adye and Affolder, {A. A.} and Y. Afik and C. Agapopoulou and Agaras, {M. N.} and J. Agarwala and A. Aggarwal and C. Agheorghiesei and Aguilar-Saavedra, {J. A.} and A. Ahmad and F. Ahmadov and Ahmed, {W. S.} and X. Ai and G. Aielli and I. Aizenberg and {Alconada Verzini}, {M. J.} and L. Barak and G. Bella and Y. Benhammou and Biswal, {J. P.} and H. Cohen and E. Etzion and O. Kuprash and Lutz, {M. S.} and R. Nayak and D. Reikher and A. Soffer and Tamir, {N. M.}",

note = "Publisher Copyright: {\textcopyright} 2024 CERN, for the ATLAS Collaboration.",

year = "2024",

month = feb,

day = "23",

doi = "10.1103/PhysRevLett.132.081801",

language = "אנגלית",

volume = "132",

journal = "Physical Review Letters",

issn = "0031-9007",

publisher = "American Physical Society",

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AU - The ATLAS collaboration

AU - Aad, G.

AU - Abbott, B.

AU - Abbott, D. C.

AU - Abed Abud, A.

AU - Abeling, K.

AU - Abhayasinghe, D. K.

AU - Abidi, S. H.

AU - Aboulhorma, A.

AU - Abramowicz, H.

AU - Abreu, H.

AU - Abulaiti, Y.

AU - Abusleme Hoffman, A. C.

AU - Acharya, B. S.

AU - Achkar, B.

AU - Adam, L.

AU - Adam Bourdarios, C.

AU - Adamczyk, L.

AU - Adamek, L.

AU - Addepalli, S. V.

AU - Adelman, J.

AU - Adiguzel, A.

AU - Adorni, S.

AU - Adye, T.

AU - Affolder, A. A.

AU - Afik, Y.

AU - Agapopoulou, C.

AU - Agaras, M. N.

AU - Agarwala, J.

AU - Aggarwal, A.

AU - Agheorghiesei, C.

AU - Aguilar-Saavedra, J. A.

AU - Ahmad, A.

AU - Ahmadov, F.

AU - Ahmed, W. S.

AU - Ai, X.

AU - Aielli, G.

AU - Aizenberg, I.

AU - Alconada Verzini, M. J.

AU - Barak, L.

AU - Bella, G.

AU - Benhammou, Y.

AU - Biswal, J. P.

AU - Cohen, H.

AU - Etzion, E.

AU - Kuprash, O.

AU - Lutz, M. S.

AU - Nayak, R.

AU - Reikher, D.

AU - Soffer, A.

AU - Tamir, N. M.

PY - 2024/2/23

Y1 - 2024/2/23

N2 - Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140 fb−1 of pp collisions at √s ¼ 13 TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e; μ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

AB - Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140 fb−1 of pp collisions at √s ¼ 13 TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e; μ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

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AN - SCOPUS:85186742137

SN - 0031-9007

VL - 132

JO - Physical Review Letters

JF - Physical Review Letters

IS - 8

M1 - 081801

ER -

Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at √s = 13 TeV with the ATLAS Detector

Abstract

Funding

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