Pieter Maris

Located at the neutron shell closure N = 8 , the long-lived radioactive isotope C 14 plays a critical role in geochronology and nuclear structure studies. Despite its widespread use, the nuclear charge radius of C 14 has remained less precisely known than that of its stable counterpart C 12 . Here, we report a high-precision determination of the C 14 charge radius using collinear laser spectroscopy at the COALA setup at TU Darmstadt, improving upon the precision of previous muonic measurements by a factor of 5 and revealing a 1.9 σ discrepancy of combined uncertainty, indicating a likely underestimated uncertainty in the muonic determination. This measurement challenges state-of-the-art nuclear theory calculations, including auxiliary field diffusion Monte Carlo, the valence-space in-medium similarity renormalization group, and the no-core shell model, augmented by neural-network techniques. With C 12 and C 14 now forming one of the most precisely characterized even-even isotope pairs, these results also enable improved QED tests.

In nuclear structure theory, accurately predicting electromagnetic observables, such as moments and transition rates, is essential for a comprehensive understanding of nuclear properties. However, computational limitations and conceptual difficulties often hinder the precise calculation of these observables. In this work, we extend machine learning methods for model-space extrapolations to electric quadrupole moments. We further present a new machine learning approach that leverages the correlations between energies, radii, and electromagnetic observables. By learning these correlations from no-core shell model calculations in accessible model spaces, this new model enables the prediction of electromagnetic observables in the full Hilbert space from predictions of full-space energies and radii, which can be obtained with established machine learning extrapolation tools. An essential property of our approach is the capability of uncertainty quantification, allowing for reliable predictions with combined statistical error estimates for many-body and interaction uncertainties. Being solely built upon the physical correlations of different observables, it can be generalized across different methods. We demonstrate the power of this new extrapolation scheme through a precision study of electric quadrupole moments across a wide range of p -shell nuclei.

We perform a precision study of radii in Boron isotopes for multiple realistic interactions from chiral effective field theory. We obtain predictions of radii with combined many-body and interaction uncertainty quantification from no-core shell-model calculations together with machine-learning extrapolation methods. An extension to radius differences further allows us to investigate a potential proton halo in B 8 and, moreover, provide predictions that relate directly to the isotope shift, which can be precisely measured in experiments.

We present a comparison of model-space extrapolation methods for No-Core Shell Model calculations of ground-state energies and root-mean-square radii in Li isotopes. In particular, we benchmark the latest machine-learning tools against widely used exponential and infrared extrapolations for energies and crossing point estimates for radii. Our findings demonstrate that, while some machine-learning-based approaches provide reliable predictions with robust statistical uncertainties for both observables even in small model spaces, others perform less consistently. The predictions of the former are compatible with established exponential and infrared extrapolations for energies while also providing a notable improvement over conventional radius estimates. Published by the American Physical Society 2025

The spectrum of 12Be exhibits exotic features, e.g., an intruder ground state and shape coexistence, normally associated with the breakdown of a shell closure. While previous phenomenological treatments indicated the ground state has substantial contributions from intruder configurations, it is only with advances in computational abilities and improved interactions that this intruder mixing is observed in ab initio no-core shell model (NCSM) predictions. In this work, we extract electromagnetic observables and symmetry decompositions from the NCSM wave functions to demonstrate that the low-lying positive parity spectrum can be explained in terms of mixing of rotational bands with very different intrinsic structure coexisting within the low-lying spectrum. These observed bands exhibit an approximate SU(3) symmetry and are qualitatively consistent with Elliott model predictions.