Abstract

We perform a spectral energy distribution fitting analysis on a COSMOS photometric sample covering the ultra-violet up to the far-infrared wavelengths and including emission lines from the Fiber Multi-Object Spectrograph survey. The sample consists of 182 objects with Hαand [OIII]λ5007 emission line measurements lying in a redshift range of 1.40 < z < 1.68. We obtain robust estimates of the stellar mass and star-formation rate spanning over a range of 109.5 − 1011.5M⊙and 101 − 103M⊙yr−1from the Bayesian analysis performed with CIGALE and using continuum photometry and Hαfluxes. Combining photometry and spectroscopy gives secure estimations of the amount of dust attenuation for both continuum and line emissions. We obtain a median attenuation ofAHα = 1.16 ± 0.19 mag andA[OIII] = 1.41 ± 0.22 mag. Hαand [OIII]λ5007 attenuations are found to increase with stellar mass, confirming previous findings with Hα. A difference of 57% in the attenuation experienced by emission lines and continuum is found to be in agreement with the emission lines being more attenuated than the continuum emission. Implementation of new CLOUDY HII-region models in CIGALE enables good fits of the Hα, Hβ, [OIII]λ5007 emission lines with discrepancies smaller than 0.2 dex in the predicted fluxes. Fitting the [NII]λ6584 line is found challenging due to well-known discrepancies in the locus of galaxies in the [NII]-BPT diagram at intermediate and high redshifts. We find a positive correlation between SFR andL[OIII]λ5007 after correcting for dust attenuation and we derive the linear relation log10(SFR/M⊙yr−1)=log10(L[OIII]/ergs s−1)−(41.20 ± 0.02). Leaving the slope as a free parameter leads to log10(SFR/M⊙yr−1)=(0.83 ± 0.06)log10(L[OIII]/ergs s−1)−(34.01 ± 2.63). The spread in the relation is driven by differences in the gas-phase metallicity and ionization parameter accounting for a 0.24 dex and 1.1 dex of the dispersion, respectively. We report an average value of logU ≈ −2.85 for this sample of galaxies. Including HII-region models to fit simultaneously photometric data and emission line fluxes is paramount to analyses of upcoming data sets from large spectroscopic surveys of the future, such as MOONS and PFS.

Highlights

  • The spectral energy distribution (SED) of a galaxy from the ultra-violet (UV) to the far-infrared reflects its stellar populations and the interplay of their emitted light with gas and dust in the interstellar medium (ISM)

  • We adopt the multi-wavelength catalog of Laigle et al (2016), COSMOS2015, containing photometry from Galaxy Evolution Explorer near ultra-violet (GALEX NUV) as well as U, B, V, r, i, z, y, J, H, and Ks, and the Spitzer Infrared Array Camera (IRAC) 3.6, 4.5, 5.8, and 8.0 μm photometry from Canada France Hawaii Telescope (CFHT) MegaCam and Widefield InfraRed Camera (WIRCam), SUBARU Prime Focus Camera (Suprime-Cam) and Hyper Suprime-Cam (HSC), and United Kingdom Infra-Red Telescope (UKIRT) Wide Field Infrared Camera (WFC), and Spitzer, respectively

  • We adopted the recipe proposed by Charlot & Fall (2000) (CIGALE module called dustatt_modified_CF00; hereafter CF00), where two stellar populations are considered: young stars that are still located in a birth cloud (BC), while older stars have already moved into the interstellar medium (ISM)

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Summary

Introduction

The spectral energy distribution (SED) of a galaxy from the ultra-violet (UV) to the far-infrared (far-IR) reflects its stellar populations and the interplay of their emitted light with gas and dust in the interstellar medium (ISM). The comparison of models predicting the full SED to observed fluxes from the continuum and line emission has been proven to be very powerful to infer these physical parameters in star-forming galaxy populations (Fossati et al 2018; Buat et al 2018; Corre et al 2018; Yuan et al 2019). For such comparisons, different categories of models are used.

UV-to-NIR Photometry
Spitzer MIPS and Herschel PACS and SPIRE data
Final sample selection
FMOS-COSMOS emission lines
SED fitting with CIGALE
Star-formation history
Nebular emission lines
Dust attenuation recipe and dust emission
Spectral energy distribution fitting results
Dust attenuation
Method
Gas-phase metallicity
Spectro-photometric modeling
Findings
Summary and conclusions

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