THE SFR–M* RELATION AND EMPIRICAL STAR FORMATION HISTORIES FROM ZFOURGE AT 0.5 < z < 4

By A. Tomczak, R. Quadri, K. Tran, I. Labbé, C. Straatman, C. Papovich, Karl Glazebrook, R. Allen, G. Brammer, M. Cowley and 12 more. 2015

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We explore star formation histories (SFHs) of galaxies based on the evolution of the star formation rate stellar mass relation (SFR–M*). Using data from the FourStar Galaxy Evolution Survey (ZFOURGE) in combination with far-IR imaging from the Spitzer and Herschel observatories we measure the SFR–M* relation at 0.5 < z < 4. Similar to recent works we find that the average infrared spectral energy distributions of galaxies are roughly consistent with a single infrared template across a broad range of redshifts and stellar masses, with evidence for only weak deviations. We find that the SFR–M* relation is not consistent with a single power law of the form SFR ∝ M * &agr; ?> at any redshift; it has a power law slope of α ∼ 1 at low masses, and becomes shallower above a turnover mass (M0) that ranges from 109.5 to 1010.8 M⊙, with evidence that M0 increases with redshift. We compare our measurements to results from state-of-the-art cosmological simulations, and find general agreement in the slope of the SFR–M* relation albeit with systematic offsets. We use the evolving SFR–M* sequence to generate SFHs, finding that typical SFRs of individual galaxies rise at early times and decline after reaching a peak. This peak occurs earlier for more massive galaxies. We integrate these SFHs to generate mass growth histories and compare to the implied mass growth from the evolution of the stellar mass function (SMF). We find that these two estimates are in broad qualitative agreement, but that there is room for improvement at a more detailed level. At early times the SFHs suggest mass growth rates that are as much as 10× higher than inferred from the SMF. However, at later times the SFHs under-predict the inferred evolution, as is expected in the case of additional growth due to mergers.

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Citations in the corpus

• UniverseMachine: The correlation between galaxy growth and dark matter halo assembly from z = 0−10 (2018, methodology): “For SFRs, standardizing on the IMF appears important, but using the same SPS and dust model does not guarantee selfconsistency between SMFs and SFRs (Madau & Dickinson 2014; Leja et al. 2015; Tomczak et al. 2016, and references therein).”
• Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe (2016, methodology): “This approach minimizes systematics by using SFRs and masses derived from the same data sets, and in contrast to techniques which integrate over mass, is largely insensitive to the mass completeness limits (Leja et al. 2015; Tomczak et al. 2016).”
• The ALPINE-ALMA [CII] survey (2020, background): “…mass plane provide important constraints on the starburst duty cycle and merger rate of galaxies (Rodighiero et al. 2011; Guo et al. 2013; Tomczak et al. 2016; Tacchella et al. 2015) and ultimately their mass growth (cold accretion vs. merger paradigm Dekel et al. 2009; Davé et al. 2011;…”
• The star formation activity of IllustrisTNG galaxies: main sequence, UVJ diagram, quenched fractions, and systematics (2018, background): “In this case, the MS is allowed to deviate from a linear trend, as in fact it does by exhibiting a turnover at about Mstars & 1010.5 M , as suggested by several observations (Karim et al. 2011; Whitaker et al. 2012; Lee et al. 2015; Tomczak et al. 2016; Lee et al. 2018, see Section 4.2).”
• Evolution of Interstellar Medium, Star Formation, and Accretion at High Redshift (2017, methodology): “This MS definition was based on an extensive reanalysis of all previous work; similar MS definitions have been obtained by Béthermin et al. (2012), Whitaker et al. (2014), Schreiber et al. (2015), Lee et al. (2015) and Tomczak et al. (2016).”
• The Star Formation Main Sequence in the Hubble Space Telescope Frontier Fields (2017, methodology): “Comparison with previous works As first step, we compare our results with the analysis of Tomczak et al. (2016), who measured the SFR by stacking on far-infrared images.”