Turbulence inference from CO spectral observations

Abstract

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 (sigma_v) measured via CO requires a correction by a factor R_CO, with R_CO,1-0 = 0.88 (+0.09, -0.08) for the CO (1-0) line and R_CO,2-1 = 0.88 (+0.10, -0.08) for the CO (2-1) line. As a consequence, previous measurements of sigma_v were overestimated by about 10-15% on average, with potential overestimates as high as 40%, taking the 1-sigma uncertainty into account.