  A large fraction of cool, low-mass stars exhibit brightness fluctuations that
arise from a combination of convective granulation, acoustic oscillations,
magnetic activity, and stellar rotation. Much of the short-timescale
variability takes the form of stochastic noise, whose presence may limit the
progress of extrasolar planet detection and characterization. In order to lay
the groundwork for extracting useful information from these quasi-random
signals, we focus on the origin of the granulation-driven component of the
variability. We apply existing theoretical scaling relations to predict the
star-integrated variability amplitudes for 508 stars with photometric light
curves measured by the Kepler mission. We also derive an empirical correction
factor that aims to account for the suppression of convection in F-dwarf stars
with magnetic activity and shallow convection zones. So that we can make
predictions of specific observational quantities, we performed Monte Carlo
simulations of granulation light curves using a Lorentzian power spectrum.
These simulations allowed us to reproduce the so-called "flicker floor" (i.e.,
a lower bound in the relationship between the full light-curve range and power
in short-timescale fluctuations) that was found in the Kepler data. The Monte
Carlo model also enabled us to convert the modeled fluctuation variance into a
flicker amplitude directly comparable with observations. When the magnetic
suppression factor described above is applied, the model reproduces the
observed correlation between stellar surface gravity and flicker amplitude.
Observationally validated models like these provide new and complementary
evidence for a possible impact of magnetic activity on the properties of
near-surface convection.
