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Published September 10, 2020 | Published + Submitted
Journal Article Open

A Census of Sub-kiloparsec Resolution Metallicity Gradients in Star-forming Galaxies at Cosmic Noon from HST Slitless Spectroscopy

Abstract

We present the hitherto largest sample of gas-phase metallicity radial gradients measured at sub-kpc resolution in star-forming galaxies in the redshift range of z ∈ [1.2, 2.3]. These measurements are enabled by the synergy of slitless spectroscopy from the Hubble Space Telescope near-infrared channels and the lensing magnification from foreground galaxy clusters. Our sample consists of 76 galaxies with stellar mass ranging from 10⁷ to 10¹⁰ M_⊙, an instantaneous star formation rate in the range of [1, 100] M_⊙ yr⁻¹, and global metallicity [1/12, 2] of solar. At a 2σ confidence level, 15/76 galaxies in our sample show negative radial gradients, whereas 7/76 show inverted gradients. Combining ours and all other metallicity gradients obtained at a similar resolution currently available in the literature, we measure a negative mass dependence of Δlog(O/H)/ Δr [dex kpc⁻¹] = (−0.020 ± 0.007) + (−0.016 ± 0.008) log(M_∗/10^(9.4) M_⊙), with the intrinsic scatter being σ = 0.060 ± 0.006 over 4 orders of magnitude in stellar mass. Our result is consistent with strong feedback, not secular processes, being the primary governor of the chemostructural evolution of star-forming galaxies during the disk mass assembly at cosmic noon. We also find that the intrinsic scatter of metallicity gradients increases with decreasing stellar mass and increasing specific star formation rate. This increase in the intrinsic scatter is likely caused by the combined effect of cold-mode gas accretion and merger-induced starbursts, with the latter more predominant in the dwarf mass regime of M∗ ≲ 10⁹ M_⊙.

Additional Information

© 2020 The American Astronomical Society. Received 2019 November 21; revised 2020 July 16; accepted 2020 July 22; published 2020 September 15. We thank the anonymous referee for careful reading and constructive comments that improved the quality of our paper. This work is supported by NASA through HST grant HST-GO-13459. X.W. acknowledges support by UCLA through a dissertation year fellowship. X.W. is greatly indebted to his family, i.e., Dr. Xiaolei Meng, SX Wang, and ST Wang, for their tremendous love, care, and support during the COVID-19 pandemic, without which this work could not have been completed. Software: APLpy (Robitaille & Bressert 2012), AstroDrizzle (Gonzaga 2012), Astropy (Price-Whelan et al. 2018), Emcee (Foreman-Mackey et al. 2013), FAST (Kriek et al. 2009), Grizli (G. Brammer et al. 2020, in preparation), SExtractor (Bertin & Arnouts 1996), VorBin (Cappellari & Copin 2003).

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Published - Wang_2020_ApJ_900_183.pdf

Submitted - 1911.09841.pdf

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August 22, 2023
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