Deep neural network for the dielectric response of insulators

Fully anharmonic calculations of the dielectric response of insulators require costly a0{0ex}b i0{0ex}n0{0ex}i0{0ex}t0{0ex}i0{0ex}o molecular dynamics simulations. Here, the authors show that this electronic response property can be described efficiently by a deep neural network that retains the accuracy of a0{0ex}b i0{0ex}n0{0ex}i0{0ex}t0{0ex}i0{0ex}o molecular dynamics. The scheme is demonstrated with calculations of the infrared absorption spectrum of liquid water at standard conditions, and of the evolution of the spectrum of crystalline ice undergoing a pressure-induced structural transformation from molecular ice VII to ionic ice X.