Machine Can Automatically Discover Parametric Functions to Model HEP Data
The paper automates finding suitable mathematical functions to model binned data in high-energy physics (HEP) using symbolic regression. Instead of manual guessing, a machine searches vast function spaces to discover accurate models for spectra like dijet events. The resulting tool, SymbolFit, pairs this search with uncertainty modeling to provide statistically sound functions that can be used directly in analysis.