radbase: Statistical tools for a next-generation evaluation of nuclear charge radii

Root-mean-square nuclear charge radii serve as an input to nuclear models, precision calculations in atomic and molecular spectroscopy, and precision tests of the standard model. The previous evaluation [1], published in 2013, received over 1300 citations from various fields. In the last twelve years, facilities producing nuclear charge radius data have increased [2, 3], existing experimental and theoretical methods have been refined, and new techniques for determining nuclear charge radii have been developed [4, 5]. Therefore, there is an urgent demand for flexible, statistically robust methods of critical evaluation. To meet this demand, we have developed radbase, an open-source set of Python codes that assists in visualizing and optimizing the network of nuclear radius data. Additionally, radbase supports the inclusion of correlations between different data via a generalized least squares procedure. We present the current status of the project, tests of the codes on critically evaluated data from the current recommended values, and design challenges.

[1] I. Angeli and K. Marinova, Atomic Data and Nuclear Data Tables, Volume 99, Issue 1, January 2013, Pages 69-95

[2] K. Tsukada et al., Phys. Rev. Lett. 118, 262501 (2021)

[3] F. Wauters, A. Knecht, SciPost Phys. Proc. 5, 022 (2021)

[4] P. Plattner et al., Phys. Rev. Lett. 131, 222502 (2023)

[5] A. Hosier et al., J. Phys. B, 57(19), 195001 (2024)