FRIB undergraduate student leads study on how new surrogate models enable faster and more efficient calculations

Understanding how physical systems respond to small disturbances is challenging across many scientific disciplines and often requires complex calculations. FRIB scientists developed a computational method to significantly reduce the time needed to perform these analyses. Lauren Jin, undergraduate student research assistant at FRIB, led the study. The team published its findings in Physical Review Research (“Surrogate models for linear response”).

Linear response theory explores how a system reacts to a weak external disturbance. Nuclear response functions inform applications such as nuclear structure theory and astrophysics. Calculating these responses for atomic nuclei is a computational challenge, however, as the motion of protons and neutrons is governed by complex equations. The calculations needed to understand nuclei from the very light to the very heavy require large supercomputers for precise simulations. 

The researchers addressed this challenge using surrogate models—simplified mathematical representations trained to reproduce the system’s full physical response. The team developed two complementary emulators and tested them against key nuclear properties: the electric dipole polarizability of ytterbium-180 and the beta decay half-life of nickel-80. Once trained, the surrogate models generated predictions up to a million times faster while maintaining the accuracy of the full calculations.

The authors made their emulators available online. The emulators include interactive visualization tools that run the calculations in real time to illustrate key concepts of their work. These surrogate models allow scientists to explore a broader range of scenarios and evaluate parameter dependencies more efficiently in nuclear physics and in other areas of science where linear response theory is applied.

Jin is a third-year undergraduate student majoring in physics at Michigan State University (MSU). She came to FRIB in 2024 through the National Science Foundation’s Research Experiences for Undergraduates program while she was a student at the University of Toledo. Due to the mentorship she received at FRIB, she transferred to MSU to obtain her physics degree, focusing on nuclear theory for rare isotopes. MSU nominated Jin for the 2026 Goldwater Scholarship.

Computational resources for this study were provided by the Institute for Cyber-Enabled Research at Michigan State University. This work was supported by the National Science Foundation and by the U.S. Department of Energy.

Michigan State University (MSU) operates the Facility for Rare Isotope Beams (FRIB) as a user facility for the U.S. Department of Energy Office of Science (DOE-SC), with financial support from and furthering the mission of the DOE-SC Office of Nuclear Physics. Hosting the most powerful heavy-ion accelerator, FRIB enables scientists to make discoveries about the properties of rare isotopes in order to better understand the physics of nuclei, nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry. User facility operation is supported by the DOE-SC Office of Nuclear Physics as one of 28 DOE-SC user facilities.

The U.S. Department of Energy Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of today’s most pressing challenges. For more information, visit energy.gov/science.