UNEDF: Advanced Scientific Computing Collaboration Transforms the Low-Energy Nuclear Many-Body Problem

TL;DR

The UNEDF collaboration leverages multidisciplinary expertise and advanced computing to improve nuclear physics models, achieving significant milestones in predictive accuracy and computational efficiency.

Contribution

This paper introduces UNEDF as a successful collaborative effort that integrates theoretical, mathematical, and computational advances for nuclear physics.

Findings

Development of comprehensive nuclear models with quantified uncertainties

Integration of advanced algorithms with leadership-class computing resources

Milestones demonstrating improved predictive power in nuclear physics

Abstract

The demands of cutting-edge science are driving the need for larger and faster computing resources. With the rapidly growing scale of computing systems and the prospect of technologically disruptive architectures to meet these needs, scientists face the challenge of effectively using complex computational resources to advance scientific discovery. Multidisciplinary collaborating networks of researchers with diverse scientific backgrounds are needed to address these complex challenges. The UNEDF SciDAC collaboration of nuclear theorists, applied mathematicians, and computer scientists is developing a comprehensive description of nuclei and their reactions that delivers maximum predictive power with quantified uncertainties. This paper describes UNEDF and identifies attributes that classify it as a successful computational collaboration. We illustrate significant milestones accomplished by UNEDF through integrative solutions using the most reliable theoretical approaches, most advanced algorithms, and leadership-class computational resources.