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The modeling of nuclear reactions and radioactive decays in astrophysical orearth-based conditions requires detailed knowledge of the masses of essentiallyall nuclei. Microscopic mass models based on nuclear energy density functionals(EDFs) can be descriptive and used to provide this information. The concept ofintrinsic symmetry breaking is central to the predictive power of EDFapproaches, yet is generally not exploited to the utmost by mass models becauseof the computational demands of adjusting up to about two dozen parameters tothousands of nuclear masses. We report on a first step to bridge the gapbetween what is presently feasible for studies of individual nuclei andlarge-scale models: we present a new Skyrme-EDF-based model that was adjustedusing a three-dimensional coordinate-space representation, for the first timeallowing for both axial and triaxial deformations during the adjustmentprocess. To compensate for the substantial increase in computational costbrought by the latter, we have employed a committee of multilayer neuralnetworks to model the objective function in parameter space and guide ustowards the overall best fit. The resulting mass model BSkG1 is computed withthe EDF model independently of the neural network. It yields a root mean square(rms) deviation on the 2457 known masses of 741 keV and an rms deviation on the884 measured charge radii of 0.024 fm.

Skyrme-Hartree-Fock-Bogoliubov mass models on a 3D Mesh: Effect of triaxial shape