“School of Astronomy”
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| Paper IPM / Astronomy / 18189 |
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To understand early star formation, it is essential to determine the dust mass budget of high-redshift galaxies. Sub-millimeter rest-frame emission, dominated by cold dust, is an unbiased tracer of dust mass. The New IRAM KID Arrays 2 (NIKA2) conducted a deep blank field survey at 1.2 and 2.0 mm in the GOODS-N field as part of the NIKA2 Cosmological Legacy Survey (N2CLS), detecting 65 sources with S/N ⥠4.2. Thanks to a dedicated interferometric program with NOEMA and other high-angular resolution data, we identified the multi-wavelength counterparts of these sources and resolved them into 71 individual galaxies. We built detailed spectral energy distributions (SEDs) and assigned a redshift to 68 of them over the range 0.6 < z < 7.2. We fit these SEDs using modified blackbody and Draine & Li (2007, ApJ, 657, 810) models and the panchromatic approaches MAGPHYS, CIGALE, and SED3FIT, thus deriving their dust mass (Mdust), infrared luminosity (LIR), and stellar mass (Mâ). Eight galaxies require an active galactic nucleus torus component, and another six require an unextinguished young stellar population. A significant fraction of our galaxies are classified as starbursts based on their position on the Mâ versus star formation rate plane or their depletion timescales. We computed the dust mass function in three redshift bins (1.6 < z ⤠2.4, 2.4 < z ⤠4.2 and 4.2 < z ⤠7.2) and determined the Schechter function that best describes it. The dust cosmic density, Ïdust, increases by at least an order of magnitude from z â¼ 7 to z â¼ 1.5, as predicted by theoretical works. At lower redshifts, the evolution flattens. Nonetheless, significant differences exist between results obtained with different selections and methods. The superb GOODS-N data set enabled a systematic investigation into the dust properties of distant galaxies. N2CLS holds promise for combining these deep field findings with the wide COSMOS field into a self-consistent analysis of dust in galaxies both near and far
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