Towards next-generation optical potentials for nuclear reactions and structure calculations

TL;DR

This paper discusses the development of advanced, data-driven optical-model potentials for nuclear reactions that incorporate non-locality, dispersion, and uncertainty quantification, aiming to improve accuracy and predictive power.

Contribution

It introduces a framework for creating next-generation optical potentials that integrate multiple sophisticated features for enhanced nuclear modeling.

Findings

Preliminary model shows promising data description.

Incorporates non-local and dispersive features.

Includes uncertainty quantification.

Abstract

Optical-model potentials (OMPs) are critical ingredients for basic and applied nuclear physics. Present-day computational capabilities allow us to generate data-driven nucleon-nucleus OMPs that are non-local and exactly dispersive (as theoretically required to be), include statistically-sound uncertainty quantification, and are trained on both scattering and bound-state data from a wide area of the nuclear chart. Combined together, these features allow for significant improvement in fidelity and extrapolative power of the model. Here, we present preliminary work toward the development and training of such an OMP. The capability of the model to describe data at this first stage is encouraging.