  In recent years, wide-field sky surveys providing deep multi-band imaging
have presented a new path for indirectly characterizing the progenitor
populations of core-collapse supernovae (SN): systematic light curve studies.
We assemble a set of 76 grizy-band Type IIP SN light curves from Pan-STARRS1,
obtained over a constant survey program of 4 years and classified using both
spectroscopy and machine learning-based photometric techniques. We develop and
apply a new Bayesian model for the full multi-band evolution of each light
curve in the sample. We find no evidence of a sub-population of fast-declining
explosions (historically referred to as "Type IIL" SNe). However, we identify a
highly significant relation between the plateau phase decay rate and peak
luminosity among our SNe IIP. These results argue in favor of a single
parameter, likely determined by initial stellar mass, predominantly controlling
the explosions of red supergiants. This relation could also be applied for
supernova cosmology, offering a standardizable candle good to an intrinsic
scatter of 0.2 mag. We compare each light curve to physical models from
hydrodynamic simulations to estimate progenitor initial masses and other
properties of the Pan-STARRS1 Type IIP SN sample. We show that correction of
systematic discrepancies between modeled and observed SN IIP light curve
properties and an expanded grid of progenitor properties, are needed to enable
robust progenitor inferences from multi-band light curve samples of this kind.
This work will serve as a pathfinder for photometric studies of core-collapse
SNe to be conducted through future wide field transient searches.
