  We discuss a novel approach that allows to obtain effective potentials from
ab initio trajectories. Our method consists in fitting the weighted radial
distribution functions obtained from the ab initio data with the ones obtained
from simulations with the effective potential, and using the parameters of the
latter as fitting variables. As a case study, we consider the example of
amorphous silica, a material that is highly relevant in the field of glass
science as well as in geology. Our approach is able to obtain an effective
potential that gives a better description with respect to structural and
thermodynamic properties than the potential proposed by van Beest, Kramer, and
van Santen, and that has been very frequently used as a model for amorphous
silica. In parallel, we have also used the so-called "force matching" approach
proposed by Ercolessi and Adams to obtain an effective potential. We
demonstrate that for the case of silica this method does not yield a reliable
potential and discuss the likely origin for this failure.

Disordered Systems and Neural Networks;Materials Science