Abreu, H., Antel, C., Ariga, A. et al. (44 more authors) (2020) Detecting and studying high-energy collider neutrinos with FASER at the LHC. The European Physical Journal C, 80 (1). 61. ISSN 1434-6044
Abstract
Neutrinos are copiously produced at particle colliders, but no collider neutrino has ever been detected. Colliders produce both neutrinos and anti-neutrinos of all flavors at very high energies, and they are therefore highly complementary to those from other sources. FASER, the Forward Search Experiment at the LHC, is ideally located to provide the first detection and study of collider neutrinos. We investigate the prospects for neutrino studies with FASERν, a proposed component of FASER, consisting of emulsion films interleaved with tungsten plates with a total target mass of 1.2 t, to be placed on-axis at the front of FASER. We estimate the neutrino fluxes and interaction rates, describe the FASERν detector, and analyze the characteristics of the signals and primary backgrounds. For an integrated luminosity of 150 fb^−1 to be collected during Run 3 of the 14 TeV LHC in 2021–23, approximately 1300 electron neutrinos, 20,000 muon neutrinos, and 20 tau neutrinos will interact in FASERν, with mean energies of 600 GeV to 1 TeV. With such rates and energies, FASER will measure neutrino cross sections at energies where they are currently unconstrained, will bound models of forward particle production, and could open a new window on physics beyond the standard model.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made (http://creativecommons.org/licenses/by/4.0/). |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 09 Mar 2020 15:01 |
Last Modified: | 09 Mar 2020 15:01 |
Status: | Published |
Publisher: | Springer Nature |
Refereed: | Yes |
Identification Number: | 10.1140/epjc/s10052-020-7631-5 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156930 |
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