STI Publications - View Publication Form #17008
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Publication Information
| Title | Transverse charge and current densities in the nucleon from dispersively improved chiral effective field theory | ||||
| Abstract | Background: The transverse densities rho_{1, 2}(b) describe the distributions of electric charge and magnetic moment at fixed light-front time and connect the nucleon's elastic form factors with its partonic structure. The dispersive representation of the form factors F_{1, 2}(t) expresses the densities in terms of exchanges of hadronic states in the t-channel and permits their analysis using hadronic physics methods. Purpose: Compute the densities at peripheral distances b = O(M_pi^{-1}), where they are generated predominantly by the two-pion states in the dispersive representation. Quantify the uncertainties. Methods: Dispersively improved chiral effective field theory (DIXEFT) is used to calculate the isovector spectral functions Im F_{1, 2}(t) on the two-pion cut. The method includes pi-pi interactions (rho resonance) through elastic unitarity and provides realistic spectral functions up to t ~ 1 GeV^2. Higher-mass states are parametrized by effective poles and constrained by | ||||
| Author(s) | Christian Weiss | ||||
| Publication Date | September 2022 | ||||
| Document Type | Journal Article | ||||
| Primary Institution | Thomas Jefferson National Accelerator Facility, Newport News | ||||
| Affiliation | Theory & Comp Physics / THEORY CENTER / THEORY CENTER | ||||
| 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 | No | ||||
| Supported by Jefferson Lab LDRD Funding | No |
Journal Article
| Journal Name | Physical Review D |
| Refereed | Yes |
| Volume | 106 |
| Issue | |
| Page(s) | 054005 |
Attachments/Datasets/DOI Link
| Document(s) |
densities_dixeft.pdf
(STI Document)
PhysRevD.106.054005.pdf
(Accepted Manuscript)
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| DOI Link | |
| Dataset(s) | (none) |
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