Nuclear charge radii in Bayesian neural networks revisited

Nuclear charge radii of (21-32)Mg.

Charge radii of all magnesium isotopes in the sd shell have been measured, revealing evolution of the nuclear shape throughout two prominent regions of assumed deformation centered on (24)Mg and (32)Mg. A striking correspondence is found between the nuclear charge radius and the neutron shell structure. The importance of cluster configurations towards N=8 and collectivity near N=20 is discussed...

Garvey-Kelson Relations for Nuclear Charge Radii

The Garvey-Kelson relations (GKRs) are algebraic expressions originally developed to predict nuclear masses. In this letter we show that the GKRs provide a fruitful framework for the prediction of other physical observables that also display a slowly-varying dynamics. Based on this concept, we extend the GKRs to the study of nuclear charge radii. The GKRs are tested on 455 out of the approximat...

Covalent radii revisited.

A new set of covalent atomic radii has been deduced from crystallographic data for most of the elements with atomic numbers up to 96. The proposed radii show a well behaved periodic dependence that allows us to interpolate a few radii for elements for which structural data is lacking, notably the noble gases. The proposed set of radii therefore fills most of the gaps and solves some inconsisten...

Indirect Causes in Dynamic Bayesian Networks Revisited

Modeling causal dependencies often demands cycles at a coarse-grained temporal scale. If Bayesian networks are to be used for modeling uncertainties, cycles are eliminated with dynamic Bayesian networks, spreading indirect dependencies over time and enforcing an infinitesimal resolution of time. Without a “causal design,” i.e., without anticipating indirect influences appropriately in time, we ...

Uncertainty in Bayesian Neural Networks