Search for new phenomena in two-body invariant mass distributions using unsupervised machine learning for anomaly detection at √s =13TeV with the ATLAS detector
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...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Corporate Author: | |
| Format: | Article (Journal) |
| Language: | English |
| Published: |
23 February 2024
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| In: |
Physical review letters
Year: 2024, Volume: 132, Issue: 8, Pages: 1-23 |
| ISSN: | 1079-7114 |
| DOI: | 10.1103/PhysRevLett.132.081801 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1103/PhysRevLett.132.081801 Verlag, kostenfrei, Volltext: https://link.aps.org/doi/10.1103/PhysRevLett.132.081801 |
| Author Notes: | G. Aad et al.* (ATLAS Collaboration) |
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