Statistical Modeling of Deeply Virtual Exclusive Scattering Reactions: Database Construction and Maximum Likelihood Methods

This project presents the development of a reproducible framework for the statistical analysis of deeply virtual exclusive scattering data, focusing on maximum likelihood estimation (MLE) techniques. Using GitHub, a structured, publicly accessible database was made to organize experimental data from various deeply virtual exclusive scattering processes to ensure database traceability and version control. The data from Jefferson Lab, Brookhaven National Laboratory, and CERN's COMPASS experiment were compiled into a database. MLE methods were then applied to extract the physical observables, or the Compton form factors, from data. The latter are believed to describe quark and gluon angular momentum in Quantum Chromodynamics, the theory of strong interactions. The Markov Chain Monte Carlo (MCMC) method was used for statistical modeling and visualization. Model fits were then assessed with attention given to the propagation of experimental uncertainties. The project demonstrates how modern computational tools and Bayesian statistical methods can enhance the analysis of data in nuclear physics. It provides versatile methods that support preliminary data-based research. All data and code are open-source and available via GitHub to encourage reuse and collaboration.