Federal Grant Award Summary

The University of Minnesota received a $440,325 Project Grant from the National Science Foundation (NSF) Division of Physics under the Mathematical and Physical Sciences program (CFDA 47.049), effective October 1, 2026, through September 30, 2029. The award funds development of ML4GW, an open-source, PyTorch-based machine learning framework designed to accelerate gravitational wave (GW) data analysis. The framework delivers graphics processing unit (GPU)-enabled tools and algorithms that reduce detection latency to under one second, enable identification of astrophysical signals missed by traditional analysis methods, and decrease computational costs by orders of magnitude. By providing open-source code, open data, trained models, and educational resources, the project makes gravitational wave discovery faster, more accurate, and accessible to the broader scientific community.

Beyond its primary gravitational wave applications, the project strengthens national computing infrastructure benefiting particle physics, neutrino astronomy, and time-domain astronomy. The initiative includes a significant workforce development component, training high school students, undergraduates, graduate students, and researchers at smaller institutions through shared educational materials and open computational resources. This collaborative research effort advances the national interest by accelerating discovery across multiple astronomical and physics disciplines while broadening participation in federally funded science.