CLEAR: The Gas-Phase Metallicity Gradients of Star-Forming Galaxies at 0.6 < z < 2.6

TL;DR

This study measures gas-phase metallicity gradients in 264 star-forming galaxies at redshifts 0.6 to 2.6, finding most have flat or slightly positive gradients, with scatter increasing at lower masses, and no clear correlation with other galaxy properties.

Contribution

It provides the largest sample to date of metallicity gradients at these redshifts and investigates their relation to galaxy properties, constraining theoretical models.

Findings

Majority of galaxies have zero or positive metallicity gradients.

Scatter in gradients increases with decreasing stellar mass.

No significant correlation between gradients and galaxy properties like SFR or size.

Abstract

We report on the gas-phase metallicity gradients of a sample of 264 star-forming galaxies at 0.6 < z < 2.6, measured through deep near-infrared Hubble Space Telescope slitless spectroscopy. The observations include 12-orbit depth Hubble/WFC3 G102 grism spectra taken as a part of the CANDELS Lya Emission at Reionization (CLEAR) survey, and archival WFC3 G102+G141 grism spectra overlapping the CLEAR footprint. The majority of galaxies (84%) in this sample are consistent with a zero or slightly positive metallicity gradient across the full mass range probed (8.5 < log M_*/M_sun < 10.5). We measure the intrinsic population scatter of the metallicity gradients, and show that it increases with decreasing stellar mass---consistent with previous reports in the literature, but confirmed here with a much larger sample. To understand the physical mechanisms governing this scatter, we search for correlations between the observed gradient and various stellar population properties at fixed mass. However, we find no evidence for a correlation with the galaxy properties we consider---including star-formation rates, sizes, star-formation rate surface densities, and star-formation rates per gravitational potential energy. We use the observed weakness of these correlations to provide material constraints for predicted intrinsic correlations from theoretical models.