Visualizing the sensitivity of hadronic experiments to nucleon structure

Determinations of the proton's parton distribution functions (PDFs) are emerging with growing precision due to increased experimental activity at facilities like the Large Hadron Collider. While this copious information is valuable, the speed at which it is released makes it difficult to quickly assess its impact on the PDFs, short of performing computationally expensive global fits. As an alternative, we explore new methods for quantifying the potential impact of experimental data on the extraction of proton PDFs. Our approach relies on the Hessian correlation between theory-data residuals and the PDFs themselves, as well as on a correlation newly defined quantity - the sensitivity - which reflects both PDF-driven correlations and experimental uncertainties. This approach is realized in a new available analysis package PDFSENSE, which operates with these statistical measures to identify particularly sensitive experiments, weigh their relative impact on PDFs, and visualize their distributions in a space of the parton momentum fraction x and factorization scale \mu. This tool offers a new means of understanding the influence of individual measurements in existing fits, as well as a predictive device for directing future fits toward the highest impact data and assumptions.