2022MNRAS.515.2951S


Query : 2022MNRAS.515.2951S

2022MNRAS.515.2951S - Mon. Not. R. Astron. Soc., 515, 2951-2969 (2022/September-2)

Bayesian hierarchical modelling of the M*-SFR relation from 1 ≲ z ≲ 6 in ASTRODEEP.

SANDLES L., CURTIS-LAKE E., CHARLOT S., CHEVALLARD J. and MAIOLINO R.

Abstract (from CDS):

The Hubble Frontier Fields represent the opportunity to probe the high-redshift evolution of the main sequence of star-forming galaxies to lower masses than possible in blank fields thanks to foreground lensing of massive galaxy clusters. We use the BEAGLE SED-fitting code to derive stellar masses, $\rm{{M_{\star }}}=\log ({\it M}/{\rm{M_{\odot }}})$, SFRs, $\rm{{\Psi }}=\log (\rm{{\psi }}/{\rm{M_{\odot }}}\, {\rm{yr}}^{-1})$, and redshifts from galaxies within the ASTRODEEP catalogue. We fit a fully Bayesian hierarchical model of the main sequence over 1.25 < z < 6 of the form $\rm{{\Psi }}= \rm{\alpha _\mathrm{9.7}}(z) + \rm{\beta }({\rm{M_{\star }}}-9.7) + \mathcal {N}(0,\rm{\sigma }^2)$ while explicitly modelling the outlier distribution. The redshift-dependent intercept at $\rm{{M_{\star }}}=9.7$ is parametrized as $\rm{\alpha _\mathrm{9.7}}(z) = \log [{\it N}(1+{\it z})^{\rm{\gamma }}] + 0.7$. Our results agree with an increase in normalization of the main sequence to high redshifts that follows the redshift-dependent rate of accretion of gas on to dark matter haloes with $\rm{\gamma }=2.40^{+0.18}_{-0.18}$. We measure a slope and intrinsic scatter of $\rm{\beta }=0.79^{+0.03}_{-0.04}$ and $\rm{\sigma }=0.26^{+0.02}_{-0.02}$. We find that the sampling of the SED provided by the combination of filters (Hubble + ground-based Ks-band + Spitzer 3.6 and 4.5 μm) is insufficient to constrain M⋆ and Ψ over the full dynamic range of the observed main sequence, even at the lowest redshifts studied. While this filter set represents the best current sampling of high-redshift galaxy SEDs out to z > 3, measurements of the main sequence to low masses and high redshifts still strongly depend on priors employed in SED fitting (as well as other fitting assumptions). Future data sets with JWST should improve this.

Abstract Copyright: © The Author(s) 2022. Published by Oxford University Press on behalf of Royal Astronomical Society.

Journal keyword(s): methods: data analysis - methods: statistical - galaxies: evolution - galaxies: formation - galaxies: high-redshift - galaxies: star formation ;

Simbad objects: 11

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Number of rows : 11
N Identifier Otype ICRS (J2000)
RA
ICRS (J2000)
DEC
Mag U Mag B Mag V Mag R Mag I Sp type #ref
1850 - 2026
#notes
1 [MAC2016] A2744cl 331 EmG 00 14 18.796 -30 24 40.75   28.5843 26.1778   25.4958 ~ 6 0
2 ACO 2744 ClG 00 14 20.03 -30 23 17.8           ~ 1077 0
3 NAME Hubble Ultra Deep Field reg 03 32 39.0 -27 47 29           ~ 1900 0
4 [MAC2016] M0416cl 1192 G 04 16 03.981 -24 04 34.85   25.0067 24.6722   23.7763 ~ 4 0
5 MCS J0416.1-2403 ClG 04 16 08.380 -24 04 20.80           ~ 425 0
6 [MAC2016] M0416cl 541 G 04 16 10.530 -24 05 04.77   25.0450 24.4968   23.8948 ~ 4 0
7 CLASH MACSJ0717.0+3745 5637 rG 07 17 34.44414 +37 44 32.4769           ~ 5 0
8 ClG J0717+3745 ClG 07 17 36.50 +37 45 23.0           ~ 511 0
9 MCS J1149.5+2223 ClG 11 49 35.8 +22 23 55           ~ 546 0
10 ALMA J114936.0+222424 rG 11 49 36.090 +22 24 24.60           ~ 9 0
11 NAME HDF-S reg 22 32 56 -60 33.0           ~ 580 0

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