Chemical post-processing of magneto-hydrodynamical simulations of
  star-forming regions: robustness and pitfalls
  A common approach to model complex chemistry in numerical simulations is via
post-processing of existing magneto-hydrodynamic simulations, relying on
computing the evolution of chemistry over the dynamic history of a subset of
particles from within the raw simulation. Here, we validate such a technique,
assessing its ability to recover the abundances of chemical species, using the
chemistry package KROME. We also assess, for the first time, the importance of
the main free input parameters, by means of a direct comparison with a
self-consistent state-of-the-art simulation in which chemistry was directly
coupled to hydrodynamics. We have found that the post-processing is highly
reliable, with an accuracy at the percent level, even when the most relaxed
input parameters are employed. In particular, our results show that the number
of particles used does not affect significantly the average properties,
although it suppresses the appearance of possibly important spatial features.
On the other hand, the choice of the integration time-step plays a crucial
role. Longer integration time-steps can produce large errors, as the
post-processing solution will be forced towards chemical equilibrium, a
condition that does not always necessarily apply. When the interpolation-based
reconstruction of chemical properties is performed, the errors further increase
up to a factor of $\sim2$. Concluding, our results suggest that this technique
is extremely useful when exploring the relative quantitative effect of
different chemical parameters and/or networks, without the need of re-running
simulations multiple times, but some care should be taken in the choice of
particles sub-sample and integration time-step.
