Nonparametric Star Formation History Reconstruction with Gaussian Processes. I. Counting Major Episodes of Star Formation

Abstract

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 ∼ 0.42 +0.15 −0.10 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 ) 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.

The diversity and variability of star formation histories in models of galaxy evolution

“…Carnall et al (2018) study a sample of quiescent galaxies from UltraVISTA at 0.25 < z < 3.75 and find that the majority of galaxies quench on timescales of ∼ 0.4τ H , with a rising set of galaxies towards the lower redshift portion of their observations with quenching timescales ∼ 0.6τ H . Iyer et al (2019) analysed a sample of CANDELS galaxies at 0.5 < z < 3.0 and found that ∼ 15 − 20% of galaxies showed evidence for multiple strong episodes of star formation, with the median timescale separating multiple peaks to be ∼ 0.4τ H , which matches the predictions using cosmoto the PSDs of individual galaxy SFHs over time. This assumption is explored in detail in Wang & Lilly (2020a).…”

“…As observations continue to grow in quality, techniques that reconstruct the SFHs from observations are able to extract more robust constraints on the SFHs of individual galaxies and ensembles (Pacifici et al 2012;Smith & Hayward 2015;Leja et al 2017;Carnall et al 2018;Iyer et al 2019). We now approach the point where we can compare observational distributions of galaxy SFHs to those from simulations to obtain constraints on intermediate-to-long timescales.…”

“…Since the shapes of the SFHs are intimately linked by scaling relations to the other physical properties of galaxies like stellar mass, environment and morphology (Kauffmann et al 2003;Whitaker et al 2014;Iyer et al 2019;Tacchella et al 2019), understanding the link between SFHs and the power on different timescales acts as a step towards linking these properties to the underlying physical processes responsible. For all the models, Section 3.1 reports the median SFHs and PSDs in bins of stellar mass, and examines their characteristics.…”

“…2. Constraints on the timescales for observed phenomena: Combining the spectral features from distant galaxies across a range of wavelengths in a full SED fitting code allows us to estimate the star formation histories of individual galaxies with uncertainties (Heavens et al 2000;Tojeiro et al 2007;Pacifici et al 2012;Pacifici et al 2016;Smith & Hayward 2015;Leja et al 2017;Iyer & Gawiser 2017;Carnall et al 2018;Leja et al 2019a;Iyer et al 2019). While these observationally derived SFHs are not sensitive to variability on short timescales, they can be useful for measuring the timescales for morphological transformations, mergers, quenching and rejuvenation, and even recent starbursts.…”

“…That being said, techniques to model and extract SFH information from galaxy SEDs are growing increasingly sophisticated (Leja et al 2019b;Iyer et al 2019), and are (i) better at estimating the older star formation in galaxies, (ii) using fully Bayesian techniques accounting for possible covariances between parameters, and (iii) implementing well motivated priors being used to break degeneracies between parameters like dust, metallicity and SFH. With this in mind, it is hoped that in addition to timescales, SFHs from upcoming surveys will also be able to provide direct constraints on PSD slope and power on the longest timescales.…”