iftpwa

Developed a framework for identifying and characterizing hadronic resonances through Bayesian inference over large parameter spaces, O(10⁶). The approach uses Gaussian processes and variational inference to model unknown components of mass spectra non-parametrically with phyiscal smoothness priors. These components can be interfered with parametric models of known processes, such as resonance line shapes, to describe the full spectrum.