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Abstract In this work, we test the frequent assumption that Lyα-emitting galaxies (LAEs) are experiencing their first major burst of star formation at the time of observation. To this end, we identify 74 LAEs from the ODIN Survey with rest-UV-through-NIR photometry from UVCANDELS. For each LAE, we perform nonparametric star formation history (SFH) reconstruction using the Dense Basis Gaussian-process-based method of spectral energy distribution fitting. We find that a strong majority (67%) of our LAE SFHs align with the frequently assumed archetype of a first major star formation burst, with at most modest star formation rates (SFRs) in the past. However, the rest of our LAE SFHs have significant amounts of star formation in the past, with 28% exhibiting earlier bursts of star formation, with the ongoing burst having the highest SFR (dominant bursts) and the final 5% having experienced their highest SFR in the past (nondominant bursts). Combining the SFHs indicating first and dominant bursts, ∼95% of LAEs are experiencing their largest burst yet: a formative burst. We also find that the fraction of total stellar mass created in the last 200 Myr is ∼1.3 times higher in LAEs than in mass-matched Lyman break galaxy (LBG) samples, and that a majority of LBGs are experiencing dominant bursts, reaffirming that LAEs differ from other star-forming galaxies. Overall, our results suggest that multiple evolutionary paths can produce galaxies with strong observed Lyαemission. 

Abstract We report the first spatially resolved measurements of gas-phase metallicity radial gradients in star-forming galaxies in overdense environments at z ≳ 2. The spectroscopic data are acquired by the MAMMOTH-Grism survey, a Hubble Space Telescope (HST) cycle 28 medium program. This program is obtaining 45 orbits of WFC3/IR grism spectroscopy in the density peak regions of three massive galaxy protoclusters (BOSS 1244, BOSS 1542, and BOSS 1441) at z = 2–3. Our sample in the BOSS 1244 field consists of 20 galaxies with stellar mass ranging from 10 9.0 to 10 10.3 M ⊙ , star formation rate (SFR) from 10 to 240 M ⊙ yr −1 , and global gas-phase metallicity ( 12 + log ( O / H ) ) from 8.2 to 8.6. At 1 σ confidence level, 2/20 galaxies in our sample show positive (inverted) gradients—the relative abundance of oxygen increasing with galactocentric radius, opposite the usual trend. Furthermore, 1/20 shows negative gradients, and 17/20 are consistent with flat gradients. This high fraction of flat/inverted gradients is uncommon in simulations and previous observations conducted in blank fields at similar redshifts. To understand this, we investigate the correlations among various observed properties of our sample galaxies. We find an anticorrelation between metallicity gradient and global metallicity of our galaxies residing in extreme overdensities, and a marked deficiency of metallicity in our massive galaxies as compared to their coeval field counterparts. We conclude that the cold-mode gas accretion plays an active role in shaping the chemical evolution of galaxies in the protocluster environments, diluting their central chemical abundance, and flattening/inverting their metallicity gradients. 

Abstract The UltraViolet imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey Fields (UVCANDELS) program provides Hubble Space Telescope (HST)/UVIS F275W imaging for four CANDELS fields. We combine this UV imaging with existing HST/near-IR grism spectroscopy from 3D-HST+AGHAST to directly compare the resolved rest-frame UV and H α emission for a sample of 979 galaxies at 0.7 < z < 1.5, spanning a range in stellar mass of 10 8−11.5 M ⊙ . Using a stacking analysis, we perform a resolved comparison between homogenized maps of rest-UV and H α to compute the average UV-to-H α luminosity ratio (an indicator of burstiness in star formation) as a function of galactocentric radius. We find that galaxies below stellar mass of ∼10 9.5 M ⊙ , at all radii, have a UV-to-H α ratio higher than the equilibrium value expected from constant star formation, indicating a significant contribution from bursty star formation. Even for galaxies with stellar mass ≳10 9.5 M ⊙ , the UV-to-H α ratio is elevated toward their outskirts ( R / R eff > 1.5), suggesting that bursty star formation is likely prevalent in the outskirts of even the most massive galaxies, but is likely overshadowed by their brighter cores. Furthermore, we present the UV-to-H α ratio as a function of galaxy surface brightness, a proxy for stellar mass surface density, and find that regions below ∼10 7.5 M ⊙ kpc −2 are consistent with bursty star formation, regardless of their galaxy stellar mass, potentially suggesting that local star formation is independent of global galaxy properties at the smallest scales. Last, we find galaxies at z > 1.1 to have bursty star formation, regardless of radius or surface brightness. 

Abstract We present a new method based on information theory to find the optimal number of bands required to measure the physical properties of galaxies with desired accuracy. As a proof of concept, using the recently updated COSMOS catalog (COSMOS2020), we identify the most relevant wave bands for measuring the physical properties of galaxies in a Hawaii Two-0- (H20) and UVISTA-like survey for a sample ofi< 25 AB mag galaxies. We find that with the availablei-band fluxes,r,u, IRAC/ch2, andzbands provide most of the information regarding the redshift with importance decreasing fromrband tozband. We also find that for the same sample, IRAC/ch2,Y,r, andubands are the most relevant bands in stellar-mass measurements with decreasing order of importance. Investigating the intercorrelation between the bands, we train a model to predict UVISTA observations in near-IR from H20-like observations. We find that magnitudes in theYJHbands can be simulated/predicted with an accuracy of 1σmag scatter ≲0.2 for galaxies brighter than 24 AB mag in near-IR bands. One should note that these conclusions depend on the selection criteria of the sample. For any new sample of galaxies with a different selection, these results should be remeasured. Our results suggest that in the presence of a limited number of bands, a machine-learning model trained over the population of observed galaxies with extensive spectral coverage outperforms template fitting. Such a machine-learning model maximally comprises the information acquired over available extensive surveys and breaks degeneracies in the parameter space of template fitting inevitable in the presence of a few bands.