  A stochastic configuration interaction method based on evolutionary algorithm
is designed as an affordable approximation to full configuration interaction
(FCI). The algorithm comprises of initiation, propagation and termination
steps, where the propagation step is performed with cloning, mutation and
cross-over, taking inspiration from genetic algorithm. We have tested its
accuracy in 1D Hubbard problem and a molecular system (symmetric bond breaking
of water molecule). We have tested two different fitness functions based on
energy of the determinants and the CI coefficients of determinants. We find
that the absolute value of CI coefficients is a more suitable fitness function
when combined with a fixed selection scheme.
