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.
