  In this technical report we present first results of applying Genetic
Programming (GP) to obtain equations for constructing reduced order models of
quantum systems, with a particular interest in nuclear Density Functional
Theory. We employ the reduced basis method to obtain reduced coordinates as the
amplitudes of the reduced basis, and use GP to avoid the need of constructing
the reduced equations through, for example, a Galerkin projection. The reduced
order models constructed through GP show excellent accuracy and speed
performance, including extrapolations in the controlling parameters, and show
promise as an effective method for emulating computationally demanding
calculations in nuclear physics.
