Non-parametric Star Formation History Reconstruction with Gaussian
  Processes I: Counting Major Episodes of Star Formation
  The star formation histories (SFHs) of galaxies contain imprints of the
physical processes responsible for regulating star formation during galaxy
growth and quenching. We improve the Dense Basis SFH reconstruction method of
Iyer & Gawiser (2017), introducing a nonparametric description of the SFH based
on the lookback times at which a galaxy assembles certain quantiles of its
stellar mass. The method uses Gaussian Processes to create smooth SFHs that are
independent of any functional form, with a flexible number of parameters that
is adjusted to extract the maximum possible amount of SFH information from the
SEDs being fit. We apply the method to reconstruct the SFHs of 48,791 galaxies
with $H<25$ at $0.5 < z < 3.0$ across the five CANDELS fields. Using these
SFHs, we study the evolution of galaxies as they grow more massive over cosmic
time. We quantify the fraction of galaxies that show multiple major episodes of
star formation, finding that the median time between two peaks of star
formation is $\sim 0.42_{-0.10}^{+0.15}t_{univ}$ Gyr, where $t_{univ}$ is the
age of the universe at a given redshift and remains roughly constant with
stellar mass. Correlating SFHs with morphology, we find that studying the
median SFHs of galaxies at $0.5<z<1.0$ at the same mass ($10^{10}< M_* <
10^{10.5}M_\odot$) allows us to compare the timescales on which the SFHs
decline for different morphological classifications, ranging from
$0.60^{-0.54}_{+1.54}$ Gyr for galaxies with spiral arms to
$2.50^{-1.50}_{+2.25}$ Gyr for spheroids. The Gaussian Process-based SFH
description provides a general approach to reconstruct smooth, nonparametric
SFH posteriors for galaxies with a flexible number of parameters that can be
incorporated into Bayesian SED fitting codes to minimize the bias in estimating
physical parameters due to SFH parametrization.
