ON STAR FORMATION RATES AND STAR FORMATION HISTORIES OF GALAXIES OUT TO z ∼ 3

By S. Wuyts, N. F. Förster Schreiber, D. Lutz, R. Nordon, S. Berta, B. Altieri, P. Andreani, H. Aussel, A. Bongiovanni, J. Cepa and 16 more. 2011

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We compare multi-wavelength star formation rate (SFR) indicators out to z ∼ 3 in the GOODS-South field. Our analysis uniquely combines U to 8 μm photometry from FIREWORKS, MIPS 24 μm and PACS 70, 100, and 160 μm photometry from the PEP, and Hα spectroscopy from the SINS survey. We describe a set of conversions that lead to a continuity across SFR indicators. A luminosity-independent conversion from 24 μm to total infrared luminosity yields estimates of LIR that are in the median consistent with the LIR derived from PACS photometry, albeit with significant scatter. Dust correction methods perform well at low-to-intermediate levels of star formation. They fail to recover the total amount of star formation in systems with large SFRIR/SFRUV ratios, typically occuring at the highest SFRs (SFRUV + IR ≳ 100 M☉ yr−1) and redshifts (z ≳ 2.5) probed. Finally, we confirm that Hα-based SFRs at 1.5 < z < 2.6 are consistent with SFRSED and SFRUV + IR provided extra attenuation toward H ii regions is taken into account (AV, neb = AV, continuum/0.44). With the cross-calibrated SFR indicators in hand, we perform a consistency check on the star formation histories inferred from spectral energy distribution (SED) modeling. We compare the observed SFR–M relations and mass functions at a range of redshifts to equivalents that are computed by evolving lower redshift galaxies backward in time. We find evidence for underestimated stellar ages when no stringent constraints on formation epoch are applied in SED modeling. We demonstrate how resolved SED modeling, or alternatively deep UV data, may help to overcome this bias. The age bias is most severe for galaxies with young stellar populations and reduces toward older systems. Finally, our analysis suggests that SFHs typically vary on timescales that are long (at least several 100 Myr) compared to the galaxies' dynamical time.

Subfields: Astronomy and Astrophysics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/0cb9fa9ac9db852c52ace40f47f8aaa469856602

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Citations in the corpus

• THE KMOS3D SURVEY: DESIGN, FIRST RESULTS, AND THE EVOLUTION OF GALAXY KINEMATICS FROM 0.7 ⩽ z ⩽ 2.7 (2014, methodology): “A. F. M. Moorwood & M. Iye, 1179–1186 The KMOS 3D survey 19 Skelton, R. E., Whitaker, K. E., Momcheva, I. G., et al. 2014, ArXiv e-prints, arXiv:1403.3689 Sobral, D., Swinbank, A. M., Stott, J. P., et al. 2013, ApJ, 779, 139 Sparre, M., Hayward, C. C., Springel, V., et al. 2014, ArXiv e-prints, arXi”
• THE SFR–M* RELATION AND EMPIRICAL STAR FORMATION HISTORIES FROM ZFOURGE AT 0.5 < z < 4 (2015, methodology): “This suggests that the fainter, non-detected galaxies have SEDs that are not consistent with their more luminous counterparts (Muzzin et al. 2010; Wuyts et al. 2011).”
• CANDELS: THE PROGENITORS OF COMPACT QUIESCENT GALAXIES AT z ∼ 2 (2012, methodology): “Our observations connect two recent results at z ∼ 2: a population of compact (n & 2) galaxies with enhanced star formation activity (Wuyts et al. 2011b) and an increasing fraction of small, post-starburst galaxies recently arrived on the red sequence (Whitaker et al. 2012).”
• CONSTRAINING THE LOW-MASS SLOPE OF THE STAR FORMATION SEQUENCE AT 0.5 < z < 2.5 (2014, methodology): “There does not exist a single SFR indicator that can probe the full dynamic range of stellar masses for individual galaxies (Wuyts et al. 2011).”
• THE MOSDEF SURVEY: MEASUREMENTS OF BALMER DECREMENTS AND THE DUST ATTENUATION CURVE AT REDSHIFTS z ∼ 1.4–2.6 (2015, background): “…attenuation of the gas versus the stellar continuum, again with most studies assuming that the same attenuation curve applies for both the stars and gas (e.g., Förster Schreiber et al. 2009; Yoshikawa et al. 2010; Wuyts et al. 2011; Kashino et al. 2013; Wuyts et al. 2013; Price et al. 2014).”
• GALAXY STRUCTURE AND MODE OF STAR FORMATION IN THE SFR–MASS PLANE FROM z ∼ 2.5 TO z ∼ 0.1 (2011, methodology): “This crudely reflects our ability to recover the intrinsic surface brightness profile shape (B.2), as well as imperfections with which observables are translated to physical parameters (see, e.g., Wuyts et al. 2009, 2011a).”
• SPECTRAL ENERGY DISTRIBUTIONS OF LOCAL LUMINOUS AND ULTRALUMINOUS INFRARED GALAXIES (2012, background): “The recipe from Wuyts et al. (2011) gives the following calibration for converting from infrared and monochromatic UV luminosity at 2800Å to star formation rate: SFRUV+IR[M⊙yr −1] = 1.09×10−10(LIR+3.3L2800)/L⊙ .”
• Panchromatic spectral energy distributions of Herschel sources (2013, methodology): “Stellar massesM∗ are based on Bruzual & Charlot (2003) models, as applied to our data by Wuyts et al. (2011b).”
• The Herschel view of the dominant mode of galaxy growth from z = 4 to the present day (2014, background): “Although there exist other calibrations that are applicable to higher redshifts (e.g., Elbaz et al. 2011; Wuyts et al. 2011), we do not know how they would impact the measurement of the scatter of the main sequence.”
• The evolution of the dust and gas content in galaxies (2013, methodology): “We also repeated the same test by making use of a “ladder of SFR indicators” (SFRladder, e.g. Wuyts et al. 2011a) as input for the grid production.”
• THE MOSFIRE DEEP EVOLUTION FIELD (MOSDEF) SURVEY: REST-FRAME OPTICAL SPECTROSCOPY FOR ∼1500 H-SELECTED GALAXIES AT 1.37 ≤ z ≤ 3.8 ?> (2014, background): “…Williams et al. 2009; Whitaker et al. 2011), the strong clustering of red galaxies (e.g., Quadri et al. 2008), the mass-metallicity relation (e.g., Erb et al. 2006), and the correlation between stellar population properties and structural parameters (e.g., Williams et al. 2010; Wuyts et al. 2011a).”
• A CANDELS–3D-HST SYNERGY: RESOLVED STAR FORMATION PATTERNS AT 0.7 < z < 1.5 (2013, methodology): “Here, we place a special emphasis on dust corrections, and in particular extra extinction towards the HII regions from which the Hα line emission originates, using UV+IR based SFRs as an additional calibrator.”
• THE STAR FORMATION MASS SEQUENCE OUT TO z = 2.5 (2012, background): “Wuyts et al. (2011b) observed similar trends across the SFR-M⋆ plane, where LIR/LUV increases along the sequence and at a given M⋆ towards high SFRs.”
• The VISTA deep extragalactic observations (VIDEO) survey (2012, background): “…probe sufficient volume over a large fraction of cosmic time to determine the full spectral energy distribution (SED) of galaxies (e.g. Smith et al. 2012) and also the evolution of dust and obscured star formation in the Universe (e.g. Dunne et al. 2011; Lapi et al. 2011; Wuyts et al. 2011).”
• The HDUV Survey: A Revised Assessment of the Relationship between UV Slope and Dust Attenuation for High-redshift Galaxies (2017, background): “…correlations between star-formation rate and stellar mass (e.g., Noeske et al. 2007; Reddy et al. 2006b; Daddi et al. 2007; Pannella et al. 2009; Wuyts et al. 2011; Reddy et al. 2012b; Whitaker et al. 2014; Schreiber et al. 2015; Shivaei et al. 2015), and between star-formation rate and dust…”
• THE LESSER ROLE OF STARBURSTS IN STAR FORMATION AT z = 2 (2011, background): “More recently Nordon et al. (2010) suggest that UV-based SFRs might actually be overestimated up to a factor of 1.5-2 at z ∼ 2, using Herschel observations (although see Wuyts et al. 2011a for a discussion of how this conclusion depends on sample selections).”
• VALIDATION OF THE EQUILIBRIUM MODEL FOR GALAXY EVOLUTION TO z ∼ 3 THROUGH MOLECULAR GAS AND DUST OBSERVATIONS OF LENSED STAR-FORMING GALAXIES (2013, methodology): “To compute stellar masses from these IRAC fluxes that will be consistent with the masses of the comparison sample, we use the catalog of Wuyts et al. (2011b) for the GOODS fields as a calibration set.”
• PHIBSS: MOLECULAR GAS CONTENT AND SCALING RELATIONS IN z ∼ 1–3 MASSIVE, MAIN-SEQUENCE STAR-FORMING GALAXIES (2012, methodology): “These ‘main-sequence’ SFGs are typically characterized by disky, exponential rest-UV/rest-optical light distributions (nSersic~1-2, Wuyts et al. 2011a).”
• The SINS/zC-SINF Survey of z ∼ 2 Galaxy Kinematics: SINFONI Adaptive Optics–assisted Data and Kiloparsec-scale Emission-line Properties (2018, methodology): “The SFRUV+IR estimates were derived following the prescriptions of Wuyts et al. (2011a): the UV contribution was calculated from the rest-frame 2800 Å luminosity and the IR contribution was derived from the longest wavelength at which an object is detected.”