STI Publications - View Publication Form #16782
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Publication Information
Title | Measuring Recoiling Nucleons from the Nucleus with the Electron Ion Collider | ||||
Abstract | Short range correlated nucleon-nucleon (NN) pairs are an important part of the nuclear ground state. They are typically studied by scattering an electron from one nucleon in the pair and detecting its spectator correlated partner (spectator-nucleon tagging). The Electron Ion Collider (EIC)should be able to detect these nucleons, since they are boosted to high momentum in the lab frame by the momentum of the ion beam. To determine the feasibility of these studies with the planned EIC detector configuration, we have simulated quasi-elastic scattering for two electron and ion beam energy configurations: 5 GeV electrons and 41 GeV/A ions, and 10 GeV electrons and 110 GeV/A ions. We show that the knocked-out and recoiling nucleons can be detected over a wide range of initial nucleon momenta. We also show that these measurements can achieve much larger momentum transfers than current fixed target experiments. By detecting both low and high initial-momentum nucleons | ||||
Author(s) | Florian Hauenstein, A. Jentsch, Jackson Pybus, Alexander Kiral, Mark Baker, Yulia Furletova, Douglas Higinbotham, Charles Hyde, Vasiliy Morozov, Dmitry Romanov, Larry Weinstein, O. Hen | ||||
Publication Date | March 2021 | ||||
Document Type | Journal Article | ||||
Primary Institution | Old Dominion University | ||||
Affiliation | Exp Nuclear Physics / Physics Division Office / Administrative | ||||
Funding Source | Nuclear Physics (NP) | ||||
Proprietary? | No | ||||
This publication conveys | Technical Science Results | ||||
Document Numbers |
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Associated with an experiment | No | ||||
Associated with EIC | Yes | ||||
Supported by Jefferson Lab LDRD Funding | No |
Journal Article
Journal Name | Physical Review C |
Refereed | Yes |
Volume | 105 |
Issue | |
Page(s) | 034001 |
Attachments/Datasets/DOI Link
Document(s) |
SRC_with_the_EIC.pdf
(STI Document)
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DOI Link | |
Dataset(s) | (none) |
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