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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

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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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. / ATLAS Collaboration.
In: Physical review letters, Vol. 132, No. 8, 081801, 23.02.2024.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

ATLAS Collaboration 2024, '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', Physical review letters, vol. 132, no. 8, 081801. https://doi.org/10.1103/physrevlett.132.081801

APA

ATLAS Collaboration (2024). 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. Physical review letters, 132(8), Article 081801. https://doi.org/10.1103/physrevlett.132.081801

Vancouver

ATLAS Collaboration. 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. Physical review letters. 2024 Feb 23;132(8):081801. Epub 2024 Feb 20. doi: 10.1103/physrevlett.132.081801

Author

ATLAS Collaboration. / 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. In: Physical review letters. 2024 ; Vol. 132, No. 8.

Bibtex

@article{68358a02ea844f9ca539501a73ef7968,
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=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.",
keywords = "General Physics and Astronomy",
author = "{ATLAS Collaboration} and A.E. Barton and I.A. Bertram and G. Borissov and E.V. Bouhova-Thacker and R.A.M. Ferguson and James Ferrando and H. Fox and Alina Hagan and R.C.W. Henderson and R.W.L. Jones and V. Kartvelishvili and P.A. Love and E.J. Marshall and L. Meng and D. Muenstermann and N. Ribaric and K. Rybacki and M. Smizanska and S. Spinali and A.M. Wharton",
year = "2024",
month = feb,
day = "23",
doi = "10.1103/physrevlett.132.081801",
language = "English",
volume = "132",
journal = "Physical review letters",
issn = "0031-9007",
publisher = "American Physical Society",
number = "8",

}

RIS

TY - JOUR

T1 - 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

AU - ATLAS Collaboration

AU - Barton, A.E.

AU - Bertram, I.A.

AU - Borissov, G.

AU - Bouhova-Thacker, E.V.

AU - Ferguson, R.A.M.

AU - Ferrando, James

AU - Fox, H.

AU - Hagan, Alina

AU - Henderson, R.C.W.

AU - Jones, R.W.L.

AU - Kartvelishvili, V.

AU - Love, P.A.

AU - Marshall, E.J.

AU - Meng, L.

AU - Muenstermann, D.

AU - Ribaric, N.

AU - Rybacki, K.

AU - Smizanska, M.

AU - Spinali, S.

AU - Wharton, A.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=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=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.

KW - General Physics and Astronomy

U2 - 10.1103/physrevlett.132.081801

DO - 10.1103/physrevlett.132.081801

M3 - Journal article

VL - 132

JO - Physical review letters

JF - Physical review letters

SN - 0031-9007

IS - 8

M1 - 081801

ER -