Advances in the development of quantum chemical methods
and progress
in multicore architectures in computer science made the simulation
of infrared spectra of isolated molecules competitive with respect
to established experimental methods. Although it is mainly the multidimensional
potential energy surface that controls the accuracy of these calculations,
the subsequent vibrational structure calculations need to be carefully
converged in order to yield accurate results. As both aspects need
to be considered in a balanced way, we focus on approaches for molecules
of up to 12–15 atoms with respect to both parts, which have
been automated to some extent so that they can be employed in routine
applications. Alternatives to machine learning will be discussed,
which appear to be attractive, as long as local regions of the potential
energy surface are sufficient. The automatization of these methods
is still in its infancy, and the generalization to molecules with
large amplitude motions or molecular clusters is far from trivial,
but many systems relevant for astrophysical studies are already in
reach.