Turbulence inference from CO spectral observations

Turbulence influences the structure and dynamics of molecular clouds, and plays a key role in regulating star formation. We therefore need methods to accurately infer turbulence properties of molecular clouds from position-position-velocity (PPV) spectral observations. A previous method calibrated with simulation data exists to recover the 3D turbulent velocity dispersion from PPV data. However, that method relies on ‘optically-thin conditions’, ignoring any radiative transfer (RT) and chemical effects. In the present study we determine how opacity, RT, and chemical effects influence turbulence measurements with CO lines. We post-process a chemo-dynamical simulation of a turbulent collapsing cloud with a non-local thermodynamic equilibrium line RT code to generate PPV spectral cubes of the CO(1-0) and CO(2-1) lines, and obtain moment maps. We isolate the turbulence in the first-moment maps by using a Gaussian smoothing approach. We compare the CO results with the optically-thin scenario to explore how line excitation and RT impact the turbulence measurements. We find that the turbulent velocity dispersion (σv) measured via CO requires a correction by a factor $\mathcal {R}_{\mathrm{CO}}$, with $\mathcal {R}_{\mathrm{CO,1\!-\!0}}=0.88^{+0.09}_{-0.08}$ for the CO(1-0) line and $\mathcal {R}_{\mathrm{CO,2\!-\!1}}=0.88^{+0.10}_{-0.08}$ for the CO(2-1) line. As a consequence, previous measurements of the σv were overestimated by $\sim 10-15~{{\ \rm per\ cent}}$ on average, with potential overestimates as high as 40 %, taking the 1-sigma uncertainty into account.