  We present the formulation and implementation of an analytical gradient
algorithm for extended multiconfiguration quasidegenerate perturbation theory
(XMCQDPT2) with the resolvent-fitting approximation by Granovsky. This
algorithm is powerful when optimizing molecular configurations with a
moderate-sized active space and many electronic states. First, we present the
powerfulness and accuracy of resolvent-fitting approximations compared to the
canonical XMCQDPT2 theory. Then, we demonstrate the utility of the current
algorithm in frequency analyses, optimizing the minimum energy conical
intersection (MECI) geometries of the retinal chromophore model RPSB6, and
evaluating nuclear gradients when there are many electronic states.
Furthermore, we parallelize the algorithm using the OpenMP/MPI hybrid approach.
Additionally, we report the computational cost and parallel efficiency of the
program.
