The difference in the energy gap is about 25 meV. The increase of the energy gap can be explained, as the Rbf interpolator smoothens the PE surfaces. Therefore, it is particularly difficult for the Rbf interpolator to predict the kink at the intersection. More advanced fitting algorithms like neural networks may be better suited to overcome that limitation. After training and validation of the properties, the SPP provides global surfaces for energies, gradients and optionally other properties, which can be used in further applications. In this study, the PE surfaces and gradients are used to run surface-hopping dynamics simulations, which can be directly compared with reference calculations. As reference calculations 1000 trajectories, based on an independent Wigner sampling, are propagated for 100 fs using the fitted PE surfaces and gradients without consultation of the model. For a one-to-one comparison, reference calculations using the same initial conditions and the same random number seeds for the Landau-Zener algorithm were performed. Fig. shows the population dynamics for the 5D model of the simulations based on the fitted properties (dashed line) compared to the populations of the reference calculations (solid line). The populations are in very good agreement within the first 20 fs. Subsequently, a more extensive population transfer is observed for the reference simulations, leading to a final population in the S 1 state of almost 90 %. The simulations using the fitted properties stretch the population transfer slightly, leading to a smaller population of the S 1 state and a larger population in the S 2 state compared to the reference calculations for the time between 20 fs and 60 fs. However, they reproduce the modulations of the population curves during the transfer process. From 60 fs to the end, the populations coincide very well again. Considering the accuracy of the surface-hopping method in general, which neglects all nuclear quantum effects, using the fitted properties seems an appropriate approximation. A possible explanation for slightly faster population transfer of the reference data is that it is hard for the Rbf to reproduce the kink of the conical intersection accurately, as shown in Fig. . This leads to a larger energy gap and a smaller second derivative close to the conical intersection, leading to an overall smaller hopping probability of the Landau-Zener algorithm.