Dataset for "Solving deep-learning density-functional theory via variational autoencoder"

The dataset contains the ground state energies, the ground state density profiles, and the external potentials of a 3D single particle system with a Gaussian-like external potential.The number of grid points for each dimension is \(N_g=18\), the linear length of the box is \(L=a_0\) with \(a_0\) the unit of length. The unit of energy is \(E_0=\frac{ \hbar^2}{(m a_0^2)}\). The dataset is zip file of a Python npz file with the following keys: - "density" that corresponds to the ground state density profile.- "potential" is the external potential.-"energy" is the ground state energy. The number of instances is 36000. -3D_gaussian.zip -> 3D_gaussian.npz a dictionary with three keys -density, potential, energy-. The dimension of both potential and density is \([N_d,N_g,N_g,N_g]\). The shape of energy is \([N_d]\). \(N_d=36000\)