Subject Area



The theoretical uncertainties of the Large Hadron Collider (LHC) observables are decreasing with the increasing statistics of the LHC experiments, and it is becoming more and more important to reduce the uncertainties in the knowledge of the nucleon structure. The latest LHC high-energy experiments, future experimental proposals, and computational tools are expected to enhance the knowledge of the nucleon structure. However, the global analysis that assesses their impact on Parton Distribution Functions (PDFs) knowledge is computationally expensive due to the corresponding large size of data. I developed a new approach that can make a quick preliminary evaluation to help the analysis process. It quantifies the impact of hadronic experiments on PDFs based on Hessian correlation and quality of measurements. This approach is accessible through an open source software called PDFSense. I used PDFSense and other statistical methods to evaluate the impact of the latest LHC datasets on PDFs. In addition, I used this software to investigate the synergy of lattice calculations and $\overline{MS}$ PDFs on improving the picture of the nucleon's collinear structure. The assessment of the impact of PDFs knowledge imposed by high luminosity upgrade to the LHC (HL-LHC), Large Hadron-electron Collider (LHeC), and Electron Ion Collider (EIC), some future high-energy experimental proposals, is also implemented.

Degree Date

Fall 12-21-2019

Document Type


Degree Name





Pavel M. Nadolsky

Second Advisor

Fredrick I. Olness



Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License