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Author Sanchis-Lozano, M.A.; Sarkisyan-Grinbaum, E.K.
Title Searching for new physics with three-particle correlations in pp collisions at the LHC Type Journal Article
Year 2018 Publication Physics Letters B Abbreviated Journal (up) Phys. Lett. B
Volume 781 Issue Pages 505-509
Keywords pp interactions at LHC; Models beyond the Standard Model; Multiparticle azimuthal and rapidity correlations; Hidden Valley models; Correlated clusters
Abstract New phenomena involving pseudorapidity and azimuthal correlations among final-state particles in pp collisions at the LHC can hint at the existence of hidden sectors beyond the Standard Model. In this paper we rely on a correlated-cluster picture of multiparticle production, which was shown to account for the ridge effect, to assess the effect of a hidden sector on three-particle correlations concluding that there is a potential signature of new physics that can be directly tested by experiments using well-known techniques.
Address [Sanchis-Lozano, Miguel-Angel] CERN, Dept Theoret Phys, CH-1211 Geneva 23, Switzerland, Email: Miguel.Angel.Sanchis@ific.uv.es;
Corporate Author Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0370-2693 ISBN Medium
Area Expedition Conference
Notes WOS:000435653100065 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 3634
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Author Alekhin, S. et al; Hernandez, P.
Title A facility to search for hidden particles at the CERN SPS: the SHiP physics case Type Journal Article
Year 2016 Publication Reports on Progress in Physics Abbreviated Journal (up) Rep. Prog. Phys.
Volume 79 Issue 12 Pages 124201 - 137pp
Keywords beyond the standard model physics; intensity frontier experiment; hidden sectors; heavy neutral leptons; dark photons
Abstract This paper describes the physics case for a new fixed target facility at CERN SPS. The SHiP (search for hidden particles) experiment is intended to hunt for new physics in the largely unexplored domain of very weakly interacting particles with masses below the Fermi scale, inaccessible to the LHC experiments, and to study tau neutrino physics. The same proton beam setup can be used later to look for decays of tau-leptons with lepton flavour number non-conservation, tau -> 3 μand to search for weakly-interacting sub-GeV dark matter candidates. We discuss the evidence for physics beyond the standard model and describe interactions between new particles and four different portals-scalars, vectors, fermions or axion-like particles. We discuss motivations for different models, manifesting themselves via these interactions, and how they can be probed with the SHiP experiment and present several case studies. The prospects to search for relatively light SUSY and composite particles at SHiP are also discussed. We demonstrate that the SHiP experiment has a unique potential to discover new physics and can directly probe a number of solutions of beyond the standard model puzzles, such as neutrino masses, baryon asymmetry of the Universe, dark matter, and inflation.
Address [Alekhin, Sergey] DESY, Platanenallee 6, D-15738 Zeuthen, Germany, Email: oleg.ruchayskiy@cern.ch
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0034-4885 ISBN Medium
Area Expedition Conference
Notes WOS:000387025400001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 2852
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Author Kasieczka, G. et al; Sanz, V.
Title The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics Type Journal Article
Year 2021 Publication Reports on Progress in Physics Abbreviated Journal (up) Rep. Prog. Phys.
Volume 84 Issue 12 Pages 124201 - 64pp
Keywords anomaly detection; machine learning; unsupervised learning; weakly supervised learning; semisupervised learning; beyond the standard model; model-agnostic methods
Abstract A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.
Address [Kasieczka, Gregor] Univ Hamburg, Inst Expt Phys, Hamburg, Germany, Email: gregor.kasieczka@uni-hamburg.de;
Corporate Author Thesis
Publisher IOP Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0034-4885 ISBN Medium
Area Expedition Conference
Notes WOS:000727698500001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5039
Permanent link to this record