Assessing the Impact of Astrochemistry on Molecular Cloud Turbulence
  Statistics
  We analyze hydrodynamic simulations of turbulent, star-forming molecular
clouds that are post-processed with the photo-dissociation region
astrochemistry code 3D-PDR. We investigate the sensitivity of 15 commonly
applied turbulence statistics to post-processing assumptions, namely variations
in gas temperature, abundance and external radiation field. We produce
synthetic $^{12}$CO(1-0) and CI($^{3}$P$_{1}$-$^{3}$P$_{0}$) observations and
examine how the variations influence the resulting emission distributions. To
characterize differences between the datasets, we perform statistical
measurements, identify diagnostics sensitive to our chemistry parameters, and
quantify the statistic responses by using a variety of distance metrics. We
find that multiple turbulent statistics are sensitive not only to the chemical
complexity but also to the strength of the background radiation field. The
statistics with meaningful responses include principal component analysis,
spatial power spectrum and bicoherence. A few of the statistics, such as the
velocity coordinate spectrum, are primarily sensitive to the type of tracer
being utilized, while others, like the delta-variance, strongly respond to the
background radiation field. Collectively, these findings indicate that more
realistic chemistry impacts the responses of turbulent statistics and is
necessary for accurate statistical comparisons between models and observed
molecular clouds.
