3 papers
hep-ph2026
Machine-Learning-Inspired SMEFT Simplified Template Cross Sections: A Case Study in ZH Production
Daniel Conde, Miguel G. Folgado, Veronica Sanz
The Simplified Template Cross Section (STXS) program has become the standard interface between Higgs measurements and global fits, but its fixed one-dimensional boundaries are not…
hep-ph2025
Angular Coefficients from Interpretable Machine Learning with Symbolic Regression
Josh Bendavid, Daniel Conde, Manuel Morales-Alvarado +2
We explore the use of symbolic regression to derive compact analytical expressions for angular observables relevant to electroweak boson production at the Large Hadron Collider (LH…
hep-ph2024
Symbolic regression for precision LHC physics
Manuel Morales-Alvarado, Daniel Conde, Josh Bendavid +2
We study the potential of symbolic regression (SR) to derive compact and precise analytic expressions that can improve the accuracy and simplicity of phenomenological analyses at t…