Publications
Publication Information
| Title | Deeply Virtual Compton Scattering on the Proton in Hall A at Jefferson Lab |
| Authors | Alexa Johnson |
| JLAB number | JLAB-PHY-20-3292 |
| LANL number | (None) |
| Other number | DOE/OR/23177-5087 |
| Document Type(s) | (Thesis) |
| Associated with EIC: | No |
| Supported by Jefferson Lab LDRD Funding: | No |
| Funding Source: | Nuclear Physics (NP) |
|
Thesis A PHD thesis Advisor(s) : Gregg Franklin (CMU) Julie Roche (Ohio) | |
| Publication Abstract: | The structure of nucleons as they are composed of quarks and gluons is not well understood. Non-perturbative methods (such as lattice-QCD) describing quark/gluon interactions are ongoing in development, but still cannot fully reproduce the structure of hadrons. Among the observables which describe longitudinal momentum and transverse position of partons, generalized parton distributions (GPDs) describe the correlations between the two, and are accessible through p(right-arrow e;e'y)p scattering experiments in the Bjorken limit when factorization holds. A complete understanding of these functions will help us to better understand the structure of nucleons. Experiment E12-06-114 was performed by JLab's DVCS Hall A Collaboration in 2014 and 2016. Using a polarized electron beam and a liquid hydrogen target, the collaboration measured cross sections for the exclusive reaction p(right-arrow e;e'y)p at xB=0.36, 0.48, and 0.60,3 .2 lte Q2 lte 9.00, and -1.28 lte t lte -0.69. This dissertation details the analysis and results of measuring the p(right-arrow e;e'y)p cross section at xB=0.48. The measured cross section results allow us to demonstrate the validity of factorization in our kinematic regime, and extract Compton Form Factor combinations important for understanding GPDs. Additionally, the cross section results are used to test existing GPD models, KM10a and KM15. |
| Experiment Numbers: | E12-06-114 |
| Group: | Hall A |
| Document: | |
| DOI: | https://doi.org/10.2172/1727383 |
| Accepted Manuscript: | |
| Supporting Documents: | |
| Supporting Datasets: | |