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The evolution of molecular clouds and star formation is fundamentally controlled by turbulence. However, methods for accurately measuring the turbulent velocity dispersion of clouds, particularly in clouds that include systematic motion, such as rotation, are not well defined. Motivated by this, we have developed a new method to recover the three-dimensional turbulence of clouds from observable data. We simulated a rotating turbulent, collapsing molecular cloud and compared its intrinsic 3D turbulent velocity dispersion with measures of the turbulent velocity dispersion accessible from observational data. We found that after applying suitable filters to the moment maps, the intrinsic turbulent velocity dispersion of the cloud could be recovered from the spatial mean of the second-moment map or from the standard deviation of the rotation-corrected first-moment map by multiplying by an empirically determined factor, which is reasonably universal, i.e., it does not significantly depend on the evolutionary stage of the cloud, the column density threshold, or the telescope resolution (as long as the resolution is better than 0.1 pc). |
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