Adversarially Learned Anomaly Detection on CMS open data: re-discovering the top quark
dc.contributor.author
Knapp, O.
dc.contributor.author
Cerri, O.
dc.contributor.author
Dissertori, Günther
dc.contributor.author
Nguyen, T.Q.
dc.contributor.author
Pierini, Maurizio
dc.contributor.author
Vlimant, J.R.
dc.date.accessioned
2021-03-04T09:00:32Z
dc.date.available
2021-03-04T04:22:15Z
dc.date.available
2021-03-04T09:00:32Z
dc.date.issued
2021
dc.identifier.issn
2190-5444
dc.identifier.other
10.1140/epjp/s13360-021-01109-4
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/472827
dc.identifier.doi
10.3929/ethz-b-000472827
dc.description.abstract
We apply an Adversarially Learned Anomaly Detection (ALAD) algorithm to the problem of detecting new physics processes in proton–proton collisions at the Large Hadron Collider. Anomaly detection based on ALAD matches performances reached by Variational Autoencoders, with a substantial improvement in some cases. Training the ALAD algorithm on 4.4 fb- 1 of 8 TeV CMS Open Data, we show how a data-driven anomaly detection and characterization would work in real life, re-discovering the top quark by identifying the main features of the tt¯ experimental signature at the LHC.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Springer
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
Adversarially Learned Anomaly Detection on CMS open data: re-discovering the top quark
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2021-02-19
ethz.journal.title
The European Physical Journal Plus
ethz.journal.volume
136
en_US
ethz.journal.issue
2
en_US
ethz.journal.abbreviated
Eur. Phys. J. Plus
ethz.pages.start
236
en_US
ethz.size
18 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Berlin
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02010 - Dep. Physik / Dep. of Physics::02532 - Institut für Teilchen- und Astrophysik / Inst. Particle Physics and Astrophysics::03593 - Dissertori, Günther / Dissertori, Günther
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02010 - Dep. Physik / Dep. of Physics::02532 - Institut für Teilchen- und Astrophysik / Inst. Particle Physics and Astrophysics::03593 - Dissertori, Günther / Dissertori, Günther
ethz.date.deposited
2021-03-04T04:22:19Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-03-04T09:00:44Z
ethz.rosetta.lastUpdated
2022-03-29T05:36:42Z
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=Adversarially%20Learned%20Anomaly%20Detection%20on%20CMS%20open%20data:%20re-discovering%20the%20top%20quark&rft.jtitle=The%20European%20Physical%20Journal%20Plus&rft.date=2021&rft.volume=136&rft.issue=2&rft.spage=236&rft.issn=2190-5444&rft.au=Knapp,%20O.&Cerri,%20O.&Dissertori,%20G%C3%BCnther&Nguyen,%20T.Q.&Pierini,%20Maurizio&rft.genre=article&rft_id=info:doi/10.1140/epjp/s13360-021-01109-4&
Files in this item
Publication type
-
Journal Article [132202]