Determining SMEFT and PDF parameters simultaneously based on the CTEQ-TEA framework

Abstract

The SM effective field theory (SMEFT) provides a model-independent and systematically improv-able framework for new physics searches. In this talk, we outline our approach to simultaneously fitting SMEFT parameters and Probability Density Functions (PDFs) in an extension of the CT18 global analysis framework. To enhance the efficiency of our global fitting and Lagrange multiplier scans, we leverage machine-learning techniques. We focus on several representative operators relevant to top-quark pair production and jet production. Through this approach, we establish self-consistent limitations on the associated Wilson coefficients, and explore the correlations between these Wilson coefficients and the PDFs.