Work

Improving the predictive power of empirical shell-model Hamiltonians

Year: 2025

Type: article

Abstract: We present two developments which enhance the predictive power of empirical shell-model Hamiltonians for cases in which calibration data are sparse. A recent improvement in the $\mathit{abinitio}$ derivation of effective Hamiltonians leads to a much better starting point for the optimization procedure. In addition, we introduce a protocol to avoid overfitting, enabling a more reliable extrapolation beyond available data. These developments will enable more robust predictions for exotic isotopes produced at rare isotope beam facilities and in astrophysical environments.

Source: Physical Review C

DOI: 10.1103/physrevc.111.044313

Authors: J. A. Purcell, B. A. Brown, B. C. He, S. R. Stroberg, W. B. Walters

Institutions: Michigan State University, University of Notre Dame, University of Maryland, College Park

Language: English

Topic: Nuclear physics research studies

Subfield: Nuclear and High Energy Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

Funder: National Science Foundation

Awards: CAREER: Quantifying Uncertainties of Ab initio Nuclear Structure Calculations for New Physics Searches, Nuclear Structure Theory and its Applications to Nuclear Properties, Astrophysics and Fundamental Physics