Searching for Molecular Outflows with Support Vector Machines: Dark
  Cloud Complex in Cygnus
  We present a survey of molecular outflows across the dark cloud complex in
the Cygnus region, based on 46.75 deg^2 field of CO isotopologues data from
Milky Way Imaging Scroll Painting (MWISP) survey. A supervised machine learning
algorithm, Support Vector Machine (SVM), is introduced to accelerate our visual
assessment of outflow features in the data cube of 12CO and 13CO J = 1-0
emission. A total of 130 outflow candidates are identified, of which 77 show
bipolar structures and 118 are new detections. Spatially, these outflows are
located inside dense molecular clouds and some of them are found in clusters or
in elongated linear structures tracing the underlying gas filament morphology.
Along the line of sight, 97, 31, and 2 candidates reside in the Local, Perseus,
and Outer arm, respectively. Young stellar objects as outflow drivers are found
near most outflows, while 36 candidates show no associated source. The clusters
of outflows that we detect are inhomogeneous in their properties; nevertheless,
we show that the outflows cannot inject turbulent energy on cloud scales.
Instead, at best, they are restricted to affecting the so called "clump" and
"core" scales, and this only on short (~0.3 Myr) estimated timescales. Combined
with outflow samples in the literature, our work shows a tight outflow
mass-size correlation.
