Fully nonperturbative charm-quark tuning using machine learning

We present a relativistic heavy-quark action tuning for the charm sector on ensembles generated by the Coordinated Lattice Simulations consortium. We tune a particular five-parameter action in an entirely nonperturbative and-up to the chosen experimental input-model-independent way using machine learning and the continuum experimental charmonium ground-state masses with various quantum numbers. In the end, we are reasonably successful; obtaining a set of simulation parameters that we then verify produces the expected spectrum. In the future, we will use this action for finite-volume calculations of hadron-hadron scattering.

Automated summary

This research presents a tuning method for a relativistic heavy-quark action using machine learning and experimental data, resulting in simulation parameters that can be used for calculations of hadron-hadron scattering.