An Exploration of the Statistical Signatures of Stellar Feedback
  All molecular clouds are observed to be turbulent, but the origin, means of sustenance, and evolution of the turbulence remain debated. One possibility is that stellar feedback injects enough energy into the cloud to drive observed motions on parsec scales. Recent numerical studies of molecular clouds have found that feedback from stars, such as protostellar outflows and winds, injects energy and impacts turbulence. We expand upon these studies by analyzing magnetohydrodynamic simulations of molecular clouds, including stellar winds, with a range of stellar mass-loss rates and magnetic field strengths. We generate synthetic $^{12}$CO(1-0) maps assuming that the simulations are at the distance of the nearby Perseus molecular cloud. By comparing the outputs from different initial conditions and evolutionary times, we identify differences in the synthetic observations and characterize these using common astrostatistics. We quantify the different statistical responses using a variety of metrics proposed in the literature. We find that multiple astrostatistics, including principal component analysis, the spectral correlation function and the velocity coordinate spectrum, are sensitive to changes in stellar mass-loss rates and/or time evolution. A few statistics, including the Cramer statistic and velocity coordinate spectrum, are sensitive to the magnetic field strength. These findings demonstrate that stellar feedback influences molecular cloud turbulence and can be identified and quantified observationally using such statistics. 
Ryan D. Boyden, Eric W. Koch, Erik W. Rosolowsky, Stella S. R. Offner
astro-ph.GA astro-ph.SR