UV-bright Star-forming Clumps and Their Host Galaxies in UVCANDELS at 0.5 ≤ z ≤ 1

Alec Martin; Yicheng Guo; Xin Wang; Anton M. Koekemoer; Marc Rafelski; Harry I. Teplitz; Rogier A. Windhorst; Anahita Alavi; Norman A. Grogin; Laura Prichard; Ben Sunnquist; Daniel Ceverino; Nima Chartab; Christopher J. Conselice; Y. Sophia Dai; Avishai Dekel; Jonathan P. Gardner; Eric Gawiser; Nimish P. Hathi; Matthew J. Hayes; Rolf A. Jansen; Zhiyuan Ji; David C. Koo; Ray A. Lucas; Nir Mandelker; Vihang Mehta; Bahram Mobasher; Kalina V. Nedkova; Joel Primack; Swara Ravindranath; Brant E. Robertson; Michael J. Rutkowski; Zahra Sattari; Emmaris Soto; L. Y. Aaron Yung

doi:10.3847/1538-4357/aced3e

1. Introduction

Understanding galaxy formation and evolution requires tracking the evolution of different galactic substructures over cosmic time. One substructure of interest is giant star-forming clumps. In comparison to their host galaxies, these clumps have higher specific star formation rate (sSFR) by a factor of several (Guo et al. 2012; Wuyts et al. 2012; Soto et al. 2017). Such clumps are common structures within star-forming galaxies (SFGs) at 1 ≤ z ≤ 2 that generally contribute ∼10% of the total star formation rate (SFR) within SFGs (Guo et al. 2012, 2015). Clumps are thus very prominent features in rest-frame UV images and have been frequently detected through deep and high-resolution rest-frame UV and optical images with both space- (Conselice et al. 2004; Elmegreen et al. 2007, 2009; Murata et al. 2014; Soto et al. 2017) and ground-based telescopes (Mehta et al. 2021; Adams et al. 2022; Sok et al. 2022). However, they have also been detected at other wavelengths, such as in emission-line maps of Hα (Genzel et al. 2008, 2011; Mieda et al. 2016; Fisher et al. 2017; Zanella et al. 2019) and as CO line-emission detections from lensed galaxies (Jones et al. 2010; Swinbank et al. 2010; Dessauges-Zavadsky et al. 2017).

The physical properties of clumps have been studied in various ways. Previous work using spectral energy distribution (SED) analyses with the Hubble Space Telescope (HST) to study gravitationally lensed and unlensed clumps have suggested that they are much larger, brighter, and more massive than local star-forming regions. Several HST studies of unlensed galaxies have indicated that clumps have a typical mass range of log M_∗/M_⊙ ≃ 8–9 (Guo et al. 2012; Wuyts et al. 2012) and vary in effective sizes from ∼1 kpc (Elmegreen et al. 2007; Förster Schreiber et al. 2011; Soto et al. 2017) to a few hundred parsecs (Livermore et al. 2012; Dessauges-Zavadsky et al. 2017), while lensed studies have suggested much smaller clump masses of (log M_∗/M_⊙ ≃ 6–7) and sizes (≤100 pc; Rigby et al. 2017; Cava et al. 2018; Vanzella et al. 2021; Meštrić et al. 2022).

Investigating this discrepancy, Cava et al. (2018) analyzed multiple images of the same lensed galaxy at different magnification, finding that unlensed observations with ∼1 kpc resolution tend to overestimate both the size and luminosity of clumps, and therefore the mass due to the blending of smaller clumps into a single-resolution element. Studies resolving this blending using local high-z SFG analogs of DYNAMO galaxies (Fisher et al. 2017; Ambachew et al. 2022) and machine-learning methods trained on high-resolution simulations and then applied to HST observations (Huertas-Company et al. 2020; Ginzburg et al. 2021) have found that giant clump masses are typically on the order of log M_∗/M_⊙ ≃ 7−8.

Along with the effect of the blending of clumps toward determining individual masses, clump research suffers from a lack of other demographic properties. This makes uncertain our understanding of clump formation/evolution and their overall contribution to their host galaxy's development throughout their lifetimes. For example, the Sérsic index of clumpy host galaxies is one of the key measurements for distinguishing the clump formation mechanisms. The two most widely accepted mechanisms are (i) in situ formation from violent disk instabilities (VDI), and (ii) ex situ formation from major/minor merger events. The former predicts that clumps form in unstable regions where the Toomre Q parameter (Toomre 1964) is below an order of unity in gas-rich galaxy disks (Bournaud et al. 2007, 2009; Agertz et al. 2009, 2015; Dekel et al. 2009, 2022; Ceverino et al. 2010; Romeo & Agertz 2014). Such galaxies are fed continuously by dense streams of cold gas flowing along cosmic web filaments. These remote large surface densities and high gas fractions lead to VDI, while also increasing the velocity dispersion, which in turn increases the typical clump mass (Dekel et al. 2009; Ginzburg et al. 2021). Alternatively, it is worth mentioning that for high redshift and Toomre Q parameters significantly above unity, compressive modes of turbulence can initiate clump formation through both in situ and ex situ scenarios, complicating our understanding of VDI at higher redshifts (Inoue et al. 2016). However, a recent neural network detected clump study within CANDELS found matching clump stellar mass functions for simulated and observed clumps at 1 < z < 3 (Huertas-Company et al. 2020). This indicates that the majority of observed clumps within their sample formed through in situ scenarios. Moreover, cosmological simulations of Mandelker et al. (2014, 2017) suggests that ex situ formation through merger events only accounts for at most ∼30% of the overall clump population. Therefore, further examination of clump formation scenarios is needed.

For this purpose, characterizing the demographics can provide insight into clump formation. For example, if clumps are predominantly hosted by galaxies with Sérsic index n ≈ 1, then this would be consistent with clump formation through VDI, which requires a disk morphology. Additionally, simulations from Mandelker et al. (2014, 2017) show that a Sérsic index n ≈ 1 places constraints on the stellar mass ratio of minor mergers as mergers above a ratio of 1:10 would very likely destroy the disk morphology. Furthermore, Mandelker et al. (2017) show a far narrower distribution of SFR_c/SFR_g for in situ clumps than for ex situ clumps, with the peak value for in situ clumps around 10%. This means that clumps are more likely to form through VDI if demographics show a correlation between the fractional (clump and host galaxy) SFR. Thus, further work is needed to characterize the demographics of clumps and their host galaxies.

To obtain robust demographics of clumpy galaxies, large samples from deep surveys are necessary. An initial study of Murata et al. (2014) provided the clumpy fraction at 0.2 ≤ z ≤ 1 of optically selected clumpy and nonclumpy galaxies as a function of stellar mass and sSFR. Guo et al. (2015) provided their clumpy fraction for SFGs for a larger, UV-selected clump sample, but presented no demographics. Additionally, Huertas-Company et al. (2020) studied a sample of clumps detected through a machine-learning algorithm that was tested on VELA-simulated galaxies and utilized on SFG samples in the five CANDELS fields (Grogin et al. 2011; Koekemoer et al. 2011). This study contributed their clumpy fraction of SFGs in terms of host mass, Δlog(sSFR), Δlog(R_e) along with correlations between clump properties and their host galaxies, but not for a wide range of demographics. Shibuya et al. (2016) directly compared clumpy and nonclumpy galaxies that were UV- and optically selected for both SFGs and quiescent galaxies (QGs). Their main demographic results show that clumpy galaxies are statistically different from nonclumpy galaxies at 1 ≤ z ≤ 2 in terms of host-galaxy morphology for all stellar masses, and SFR for low- and intermediate-mass galaxies.

Within this work, we utilize the mosaics from a recent UV survey, Ultraviolet Imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey Fields (UVCANDELS; PI: H. Teplitz), that has been conducted on four of the five CANDELS fields (COSMOS, GOODS-N, GOODS-S, EGS). UVCANDELS, when combined with CANDELS, includes full coverage from the NUV (∼2600 Å) to I-band (∼8000 Å) filters providing ideal mosaics to study UV-bright clumps in the lower-redshift regime (z ≤ 1). We detect and analyze a sample of UV-selected clumps from these mosaics to further investigate the demographics of clumps and characteristic differences between clumpy and nonclumpy SFGs. By defining a clumpy galaxy as an SFG that contains at least one off-center clump, we are able to separate our UV-selected sample into clumpy and nonclumpy populations and analyze a large variety of averaged galactic properties of each population (stellar mass, optical size, UV color, SFR, and Sérsic index), as discussed further in Section 3. We compare these results directly to those of Shibuya et al. (2016) and discuss the implications of any differences. Furthermore, we present several relations between clump luminosity and their host-galaxy properties to further relate clumps and the types of galaxies that exhibit them. We also note that previous studies are not homogeneous in their definition (or constraints) of clumps, which could play a role in the demographic discrepancies present within the literature. To this end, our results are tested across several definitions for clumps and SFGs to show the impact of sample selection. We compare our findings to previous studies in Section 3.3.

We structure this paper as follows. First, we briefly summarize our surveys and SFG samples in Section 2. We discuss the method for clump detection within individual galaxies from their UV mosaic cutouts in Section 2.3. In Section 2.4, we describe the measurement of multiband photometry of individual clumps and test its accuracy. We then present our work's contribution to the clumpy fraction across cosmic time in Section 3.1. In Section 3.2, we present our demographic results between clumpy and nonclumpy SFGs and compare to the literature. In Section 3.3, we discuss the effect of sample selection and our definitions of clumpy and QGs that potentially impose biases. In Section 3.4 we present our clump luminosity relations and compare these results to the literature. In Section 4, we discuss the implication of our results toward the evolution of SFGs that contain clumps while noting some contaminating scenarios not studied by this work. Lastly, we conclude this paper while describing our future work. Throughout this paper, we adopt a flat Lambda cold dark matter cosmology with H₀ = 67 km s⁻¹ Mpc⁻¹, Ω_M = 0.31, and Ω_Λ = 0.69, and express all magnitudes in the AB system (Oke 1974).

2. Data and Methods

2.1. Surveys and Galaxy Properties

The samples of galaxies used in this work are derived from the mosaics of the recently completed Hubble Treasury program, the UVCANDELS. This survey is an extension of CANDELS (Grogin et al. 2011; Koekemoer et al. 2011) in UV coverage for four of the deep-wide survey fields (COSMOS, GOODS-N, GOODS-S, and EGS). UVCANDELS consists of Wide Field Camera 3 F275W imaging (imaging depth of AB = 27 mag for compact galaxies) over ∼430 arcmin² of UV coverage, an increase of 4× when combined with prior archival data, along with Advanced Camera for Surveys F435W (reaching AB ≥ 28.0 mag) imaging in parallel.

As a comparison sample, we use galaxies selected from the F275W mosaics of the Hubble Deep UV Legacy Survey (HDUV), which is a deeper survey (∼0.5 mag deeper in comparison to UVCANDELS at z ∼ 1) covering the GOODS-N and GOODS-S CANDELS fields. The additional depth allows us to test for survey sensitivity bias within the clump-detection process. We refer the reader to Oesch et al. (2018) for a more thorough description of the HDUV survey.

For our analysis, we utilize the galactic properties listed in the original CANDELS catalogs (Grogin et al. 2011; Koekemoer et al. 2011) matched to our galaxies from both UVCANDELS and HDUV. In brief, the derived photometric redshifts combine the results from more than a dozen photo-z measurements with various SED-fitting codes and templates, which is further described in Dahlen et al. (2013). Stellar masses were measured as the median of the results from 12 SED-fitting codes, as adopted from Santini et al. (2015) for GOODS-S, Stefanon et al. (2017) for EGS, Nayyeri et al. (2017) for COSMOS, and Barro et al. (2019) for GOODS-N. The SFRs were derived from UV luminosities using the relation from Kennicutt (1998) and corrected for dust using the slope of the UV continuum emission to the ratio of UV-to-IR luminosities as described in Barro et al. (2019). Galaxy size and morphology were derived using GALFIT with the H, J, and Y bands detailed in van der Wel et al. (2012). Lastly, we determined color for our UV-bright SFGs by using the CANDELS-cataloged rest-frame U- and V-band AB magnitudes, derived from observed-frame SEDs template fitting using the EAZY code (Brammer et al. 2008).

2.2. Sample Selection

We first constrained our UVCANDELS and HDUV galaxy samples by their listed CANDELS physical properties. A redshift range of 0.5 ≤ z ≤ 1 was selected in order to avoid observing the UV-bright clumps at optical wavelengths and when clumps are rare (z < 0.5). A minimum galaxy mass limit was set to log(M*) ≥ 9.5 M_⊙ to ensure a mass-complete sample. An axial ratio of q > 0.5 excludes "edge-on" galaxies minimizing the effects of dust extinction in our flux calculations in Section 2.4. To avoid contamination by stars, we set Star Class < 0.8, removing likely star candidates above 80% probability. We restrict our sample to actively star-forming galaxies by defining SFGs as galaxies with sSFR ≥ 0.1 Gyr⁻¹. Lastly, we placed constraints on galaxy size (R_e ≥ 0 farcs 2) and H-band magnitude (F160W < 25 AB) to remove small and faint galaxies, as their substructures may not be properly resolved. The above restrictions reduced our final sample to 513 SFGs for the four fields in UVCANDELS and 182 SFGs for the two fields of HDUV with four overlapping galaxies.

2.3. Clump Detection

Clumps were detected from the HST/UVIS F275W 60 mas mosaics through an automated detection algorithm, with quality control by visual inspection. Within the four UVCANDELS fields and two HDUV fields, we made a 150 × 150 pixel cutout image of each galaxy and convolved them with a Tophat 2D-smoothing kernel set to r = 7 pixels (0 farcs 42). From the resulting residual image (original − smoothed), the median global background contribution was measured with a 25 × 25 pixel box and all pixels with a flux value less than 3σ masked out, leaving only UV-bright pixels that are potentially associated with clumps. From this, we identified sources that contain a FWHM of 3 pixels brighter than 3σ and labeled them as potential clumps. In order to verify the robustness of our algorithm, we experimented with a wide range of values for the roundness, threshold background-subtracted flux value, and minimal FWHM for clumps. Visual inspection of each galaxy for each set of such parameters confirms that our algorithm consistently detects bright clumps in both UVCANDELS and HDUV. Figure 1 shows the detection algorithm process for five example galaxies and includes their corresponding H-band image for reference.

**Figure 1.** Example galaxies (rows) from our clump-detection algorithm. The respective columns show (from left to right) each galaxy in the H-band filter, NUV filter, smoothed (F275W), residual (F275W − smoothed), and original F275W cutout with detected clumps marked. Each galaxy center is marked with a cyan "x" and our clump-detection size limit of r ≤ 3 × R_e indicated by black dashed circles. The detected clumps that pass (fail) our fiducial selection criterion are marked with green (red) circles. Our selection criterion removed one clump from both IDs 8008 and 15209 due to their proximity to the host galaxy's center. Additionally, another clump was removed from ID 8008 due to its radial distance being greater than 3 R_e, which suggests a probable association with an external galaxy.
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Standard image High-resolution image

Within our samples not all of the detected clumps are of interest. Specifically, we excluded (i) central clumps, and (ii) clumps not associated with the target galaxy. The former exclusion removed galactic nuclei misidentified as clumps by flagging the detected sources with radial distance ≤ 0 farcs 1 from the CANDELS-listed galactic center. The latter exclusion removes clumps or other bright sources that originated within other nontargeted galaxies/objects also present within a cutout. This restriction is set by mandating a clump be within a radial distance of 3 times the CANDELS-listed effective radius (R_e) in arcseconds. Using similar methods to that of Graham & Driver (2005), we find that a radius of r = 3 × R_e for n = 1 (4) encompasses 98.2% (93.4%) of the galaxy's total flux allowing for detections across the majority of the target galaxy regardless of their morphology. Visual inspection of both UVCANDELS and HDUV samples were again performed to validate both distance restrictions.

Additionally, we investigated the possibility that our clump statistics are contaminated by the superimposition of foreground/background galaxies within our mosaics. To accomplish this, we used the number density of observed galaxies in UVCANDELS in each sky area to calculate the probability of two galaxies falling into the same area as large as a typical galaxy in our sample. More specifically, to estimate the number density, we included all UVCANDELS galaxies at 0.5 ≤ z ≤ 2.0 with F275W magnitude brighter than 28 AB. We limited the redshift to z = 2.0, because beyond it the Lyman limit will be redshifted into the F275W filter so that the number of observed galaxies would be quite low (see Wang et al. 2023). We also used sources brighter than 28 AB because our clump detection completeness drops to nearly zero for fainter clumps according to our test involving simulated clumps in Section 2.4. We determined that the average number of galaxies in a circular region with a radius of 3'' is ∼0.1. This radius is 3 times the maximum radius of all galaxies in our sample (1''). Assuming a Poisson distribution, with this average number, the probability of observing two galaxies simultaneously in such a region is 0.45%, meaning only ∼two of our 513 SFGs would be affected by the foreground/background contaminations. This result is negligible for our later statistical analysis. Visual inspection of each UV mosaic also indicated no obvious merger pairs within our sample.

2.4. Aperture Photometry

For our clump photometry, we measure the flux within an aperture of radius 0 farcs 18 (3 pixels) for each clump. Since clumps are not isolated sources, other clumps can fall within each defined aperture/annulus. Therefore, while measuring the flux for individual clumps, all others are masked out from our calculations.

Once the total aperture flux is measured, we apply two corrections. First, since clumps are substructural features that lie embedded within the gaseous disks of galaxies, the local background contribution—measured using an annulus of size 0 farcs 3–0 farcs 42 (5−7 pixels) with clumps masked from the image—was subtracted from the total to exclude the flux contributed from the disk profile. Both our aperture and annulus size are slightly larger than the fiducial method in Guo et al. (2018), but still provide reasonable estimates. We acknowledge that our chosen 3 pixel-sized masks do not fully block the signal contributions from the point-spread function (PSF) wings of other clumps within our defined background annulus. However, at a radius of r > 3 pixels, the PSF flux per pixel is less than 2% of its central maximum flux. Here, for simplicity, we assume each clump is a PSF. Moreover, since a nearby clump (if present) only occupies one direction of the entire background annulus, our use of the median to estimate the background with the entire annulus would not be significantly affected. Therefore, the contribution from the PSF wings of nearby clumps is negligible in our later measurement of clump fluxes.

Second, our choice of aperture size might not encapsulate the entire PSF of our sources, and therefore may miss the contributions from the PSF wings of their light profiles. To correct for the light outside of our defined apertures, we estimated a correction factor by calculating the ratio of flux encircled within our 3 pixel aperture to the total flux of the PSF. We determined that our aperture encapsulates ∼77% of the total light from each source, leading to a global correction factor of 1.29 for all four CANDELS fields.

To evaluate the completeness of our clump detection, we compare in Figure 2 the ratio of the number of clumps to the number of SFGs (N_c/N_g) in UVCANDELS and HDUV, with the latter being about ∼0.5 mag deeper than the former. Clumps from HDUV have the same method of detection and luminosity measurement as those from UVCANDELS. We converted the flux of each clump to the absolute magnitude in rest-frame UV (λ ∼ 1600 Å) following the method of Hogg et al. (2002). For simplicity, we assumed that clumps have the same stellar population and dust as their host galaxies, simplifying the conversion process to only require the host galaxy's redshift. This assumption is, in general, valid for clumps as a population (e.g., Guo et al. 2012, 2018). Although individual clumps may have different M_∗/L ratios (e.g., varying with their galactocentric distances), this assumption would not affect our completeness estimate here. The two surveys match at the bright end down to ∼−16.7 AB (rightmost dashed line), indicating that the shallower UVCANDELS still yields a complete detection of clumps above this luminosity. For luminosities fainter than −16.7 AB, the number of clumps per galaxy in UVCANDELS is significantly lower than in HDUV, indicating an incomplete clump detection.

To ensure complete statistics in our later analyses, we set a minimum clump luminosity limit derived from a comparison to the far-UV (FUV) luminosity of the largest local H ii regions from Relaño & Kennicutt (2009). More specifically, we derive the FUV luminosity of NGC 604 from Relaño & Kennicutt (2009) from their extinction-corrected Hα luminosity with the assumption that SFR_Hα ≈ SFR_FUV. We find that clumps with luminosity M_UV ≤ −16 AB (leftmost dashed line of Figure 2) are ∼3 times brighter than the most luminous local H ii regions (in comparison to NGC 604), ensuring that our clumps are intrinsically different from typical H ii regions. This limit provides the highest number statistics for our clump sample, while also maintaining a reasonable completeness limit for our detections (∼60% at M_UV = −16 AB), as shown in Figure 2. We set clumps brighter than this threshold as our fiducial sample, however we note that this sample remains incomplete when compared to the HDUV detections. We will also discuss further, in Section 3.3, the effects of using a complete sample (M_UV ≤ −16.7 AB limit) that suffers from lower number statistics and compare the results to our fiducial sample. Additionally, we compare other sample-selection criteria to our results, for completeness.

Furthermore, we have conducted a thorough test of our clump-detection algorithm to evaluate its completeness, by using a method similar to Guo et al. (2015) and Sattari et al. (2023). Our test involved the use of simulated clumps, which were represented as point-like sources with normalized magnitudes between F275W mag = 25−30 AB. These clumps were embedded within the cutout mosaic of a specific nonclumpy, HDUV galaxy that is characterized by a disk profile. We then tested our detection algorithm, processing the new image in a similar manner as described before, and repeated this approach 100 times for each incremental step in clump magnitude for the full redshift range of 0.5 ≤ z ≤ 1. For comparison to our fiducial cutoff of M_UV ≤ −16 AB, we converted the flux of our simulated clumps to absolute magnitudes using the same method as before for our observed clumps. Our findings indicate that our detection algorithm achieves ∼100% completeness for clumps down to our fiducial cutoff at the median redshift of z ∼ 0.8 for our HDUV sample. We therefore claim that our clump-detection algorithm is complete within our study.

In Figure 3, we show the number of clumps per galaxy for our two survey samples that were detected from our algorithm. After applying our selection criterion, our fiducial sample (filled bars) consists of 233 and 188 clumps for UVCANDELS and HDUV, respectively, with the majority of SFGs in UVCANDELS (88%) and HDUV (69%) hosting one to two clumps. The two most clumpy galaxies, seen within each respective survey, both host seven clumps within each of their substructures.

3. Results

In this section, we present our main results: the clumpy fraction, the properties of clumpy galaxies, and relations between clump luminosity and host galaxies' properties. We then discuss the effects of different sample selections and clump definitions on our results. To investigate clump properties in different galaxy M_∗ regimes, we divide our sample into three mass bins (low mass, 9.5 < M_∗/M_⊙ < 10; intermediate mass, 10 ≤ M_∗/M_⊙ ≤ 10.5; and high mass, M_∗/M_⊙ > 10.5) throughout our work.

3.1. Clumpy Fraction

To evaluate the importance of clumpy substructures to the evolution of SFGs, we measure the fraction of clumpy galaxies, f_clumpy, defined as the number of SFGs containing at least one off-center clump, to the total number of SFGs in our sample. Figure 4 shows our result (outlined circles) and their corresponding binomial errors within our redshift range. For low-mass galaxies (left panel) ∼35% of SFGs are considered "clumpy," while the fraction decreases to ∼22% for both intermediate-mass (middle panel) and high-mass (right panel) galaxies. As indicated, the frequency of clumpy SFGs decreases between cosmic noon and the present day. However, a significant fraction of SFGs are clumpy at z ≥ 0.5 regardless of stellar mass.

We compare our results to those within the literature in Figure 4. Murata et al. (2014, blue lines) derived f_clumpy from optically (HST/F814W) detected galaxies in the COSMOS field. Their sample of galaxies covered a similar redshift range to ours, however they defined their clumpy galaxies differently based on the I-band flux ratio of the three brightest clumps in each galaxy. Guo et al. (2015) sampled galaxies from the CANDELS/GOODS-South and UDS fields, while Shibuya et al. (2016) sampled galaxies from all five CANDELS fields, along with data in the Hubble Ultra Deep Field (HUDF; Beckwith et al. 2006) and two parallel Hubble Frontier Fields (HFFs), A2744 and MACS0416 (Lotz et al. 2017). Both studies used a similar sample selection, with the exception of slightly different binning for low/intermediate/high stellar mass, and defined their clumps using the ratio of clump UV luminosity to the total UV luminosity of the host galaxy (e.g., L_c/L_G ≥ 8%). Sattari et al. (2023) studied clumps within UVCANDELS and CANDELS that contribute a minimum of 10% of the galaxy's total rest-frame UV flux and are detected by their algorithm based on a fast Fourier transform; their results are consistent with other rest-frame UV-detected samples. Lastly, Sok et al. (2022) used deconvolution of ground-based images of the COSMOS field to resolve 20,185 SFGs at 0.5 ≤ z ≤ 2. They detected sources as high, U-band surface density regions within the plane of surface brightness density and host-galaxy size (Σ/Σ_e, R/R_e) and similarly defined them as "clumps" if their fractional U_rest luminosity was above 8%. We find that our measured clumpy fraction agrees very well with the literature for each mass bin.

We note the importance of detecting clumps in the UV as detections at redder wavelengths tend to undersample clumps due to their lower contrast with their host galaxy's disk profile (Wuyts et al. 2012). This has been verified through morphology studies of concentration, asymmetry, and smoothness parameters from Mager et al. (2018) in which the authors observed a mild decrease in clumpiness (smoothness) within a wide range of galaxy morphologies when switching observations from UV to optical wavelengths. This effect is best shown from our results in the low-mass bin of Figure 4, for which the optical-selected (I-band) clumps of Murata et al. (2014) reported a lower clumpy fraction.

3.2. Clumpy versus Nonclumpy: Galactic Property–Stellar Mass Relations

In Figure 5, we plot several galactic properties (host size, SFR, color, and Sérsic index) against galaxy stellar mass for our clumpy and nonclumpy SFG distributions. The median of each population in each mass bin was calculated and are represented by diamonds within the figure. The uncertainty of each median was determined from bootstrapping with replacement over N = 1000 trials for both clumpy and nonclumpy populations. In most cases, the error bars are smaller than the median symbols (diamonds). To quantify the difference between clumpy and nonclumpy SFGs, we calculated the statistical significance between the two distributions (shown at the top of each panel), which is the difference in medians normalized by the quadrature sum of their respective uncertainty.

We find that the differences between the clumpy and nonclumpy galaxies are statistically significant (≥3σ) for host-galaxy size in high-mass SFGs (top panel), host log(SFR) (second panel), and color (third panel) in low- and intermediate-mass SFGs. The bottom panel of Figure 5 indicates no significant differences between the Sérsic index of clumpy and nonclumpy SFGs, with clumpy SFGs of low and intermediate mass showing clear disk-like structures (n ≈ 1). We argue that the slightly higher Sérsic index (n ∼ 2.5) seen for high-mass SFGs results from massive galaxies containing a more developed central bulge than lower-mass galaxies, however still representing a disk-like morphology.

To compare to the literature, we further placed our results for SFR and Sérsic index into histograms, as shown in Figure 6. We display our clumpy (red) distribution and nonclumpy (outlined) distribution from top to bottom for low-mass, intermediate-mass, and high-mass galaxies, respectively. We also calculate the two-sample Kolmogorov–Smirnov parameter in each panel, indicating whether the two distributions for clumpy and nonclumpy SFGs are statistically similar (p > 5%) or distinct (p ≤ 5%). We find consistent results for host morphology to our median comparison in that clumpy galaxies are statistically similar in disk-like morphology. Conversely, the distributions of clumpy and nonclumpy SFGs are distinct for host SFR in all mass bins.

We compare these results with those found within Shibuya et al. (2016), who used similar criteria to select galaxies from CANDELS, HUDF, and HFFs as mentioned in Section 4. Their results for SFR and Sérsic index show a distinction for galaxies in all mass bins, with the exception of high-mass SFR. Conversely to theirs, our clumpy and nonclumpy distributions are distinct for SFR and identical for morphology in all mass bins. However, their study includes QGs, which have a higher Sérsic index and are predominately nonclumpy. Therefore, including them will increase the average Sérsic index of nonclumpy galaxies, resulting in the apparent distinction between the two populations. We note the existence of a second "peak" in the distribution of host-galaxy SFRs for high-mass clumpy galaxies. This may be due to poor statistics (22 galaxies) for clumpy galaxies in this mass bin. Therefore, it is possible that insufficient statistics result in the discrepancy in SFR between our results for high-mass SFGs.

3.3. Effect of Sample Selection and Clump Definitions

In this section, we discuss several effects of sample selection and clump definition on our results for our fiducial (M_UV ≤ −16 AB) sample. Previous studies of clumps have defined their galaxies/clumps using different methods. Furthermore, how we define "clumps" and "SFGs" can be important factors when comparing past and future studies, and the impact of using different methods has not been fully explored. The purpose of this section is to provide a reference of these effects to make direct and fair comparisons in the literature, where the selections of clumps or clumpy galaxies vary from work to work. We provide our full range of sample selections in a single plot (Figure 12) in the Appendix for further reference.

3.3.1. UVJ versus sSFR Quiescent Cutoff

Here, we specifically test two quiescent cutoff definitions for SFGs and quantify the impact to each of our two mass-binned distributions. The first method uses a sSFR limit (0.1 Gyr⁻¹) that is sufficiently lower than the SFR– M_∗ main sequence, while the second method uses a color–color relation referred to as the "UVJ diagram" (Williams et al. 2009).

Compared to our fiducial sample, the UVJ definition for SFGs reclassifies two, 14, and 16 SFGs as QGs in our low-, intermediate- and high-mass bins, respectively. Conversely, six, eight, and 14 QGs would then be considered star-forming. Therefore, out of the total number of galaxies (SF + QG), 3%, 10%, and 16% of each respective mass bin were defined differently as either QGs or SFGs between the two methods. Figure 12, located in the Appendix, shows this impact to our results more clearly. In comparison to our fiducial sample, we find that the UVJ definition only affects our conclusions regarding host-galaxy color for high-mass SFGs, while all other results for size, SFR, color, and morphology are unaffected. Therefore, we conclude that the particular QG cutoff definition used within a study has a marginal effect on SFG demographic results.

3.3.2. Surface Brightness Bias

One concern is that the difference in demographics may be affected by a difference in surface brightness for our SFG samples. For example, if clumpy galaxies have higher surface brightness on average this may be an indication that clumps are only detected above a certain brightness threshold. One possible solution to this problem would be to implement a minimum F275W magnitude to our SFGs so that our clumpy and nonclumpy samples are relatively similar with respect to their range in surface brightness distributions.

Figure 7 shows the surface brightness to apparent UV-magnitude relation for our fiducial sample distribution with the medians and errors of our clumpy (blue) and nonclumpy (red) samples superimposed. We tested several UV-magnitude cutoff limits and set a range of F275W mag ≤ 25 as the optimal limit, as shown by the gray shaded region in the right panel, with the recalculated medians. This limit lowered the discrepancies between the median surface brightness of the two populations to below 0.3 dex, indicating that the bias has been significantly reduced.

The impact of this magnitude constraint on our results can be seen in the left column of Figure 11, located in the Appendix A. The panels again show the relations of galaxy size, SFR, color, and morphology with respect to galaxy stellar mass for our two populations. We find that the distinction between clumpy and nonclumpy SFGs for intermediate-mass SFR and color as well as high mass size are no longer present. Furthermore, no new distinctions emerge from the added magnitude constraint.

Although the new constraint sufficiently corrects for surface brightness bias within our sample, a new issue arises that is twofold. As shown in the right panel of Figure 7, this limit excludes a large portion of nonclumpy SFGs from our sample, which affects completeness from the inclusion of only bright SFGs. This also creates a sample of clumpy and nonclumpy galaxies that are nearly identical, as indicated by the nearly matching distribution medians shown in the left column of Figure 11. The concern with these issues is that it may be physical that fainter galaxies are nonclumpy. Therefore, we find it unsuitable to apply this limit to our clump sample as the comparison of clumpy and nonclumpy galaxy properties may be misleading without considering intrinsically fainter systems. However, we note that surface brightness can be an important factor in demographic results.

3.3.3. Clump Luminosity Threshold

For our clump definition, we define clumps based on a luminosity minimum (M_UV ≤ −16 AB) that separates them from typical (local) H ii regions as described in Section 2.4. However, as mentioned, the resulting clump sample may still suffer from incompleteness. Here, we compare three different luminosity thresholds (no constraint, M_UV ≤ −16 AB, and M_UV ≤ −16.7 AB) to show the impact on our galactic property relations.

Figure 13, located in the Appendix B, shows the effects of each luminosity threshold on each of our four galactic property results. From left to right, we varied the threshold with no added constraint ("all" clumps), our fiducial result, and −16.7 AB, which is less affected by incompleteness in our clump sample.

For galaxy size, we find size dependence only within our "all" clump sample for intermediate- and high-mass SFGs and within our fiducial sample for high-mass SFGs. Our M_UV ≤ −16.7 AB constraint shows no size dependence in all mass bins. For galaxy SFR, we find distinction between clumpy and nonclumpy SFGs for all constraints in low-mass SFGs and within our "all" clump and fiducial samples for intermediat-mass SFGs. We find no distinction in each constraint for high-mass SFGs. For galaxy color, we find distinction in all mass bins for all constraints, with the exception of our fiducial and M_UV ≤ −16.7 AB samples for high-mass SFGs. Lastly, we find no change in galaxy morphology with each constraint as the overall structure related to the Sérsic index remains "disk-like" for all mass bins of each population. We note the large increase in Sérsic index to high-mass clumpy SFGs, which most likely arises from low statistics for our fiducial and complete samples.

We conclude that our threshold definition has a small effect on our results due to the disagreement in galaxy SFR between our complete and fiducial sample for intermediate-mass SFGs. However, we argue that the discrepancies seen within high-mass galaxy size can be explained by small number statistics and that our overall results for our fiducial sample (compared to the complete sample) are robust. We do emphasize that it is necessary to distinguish clumps from H ii regions, as applying no constraints has a major impact on galaxy size dependence.

3.3.4. Clump Definition

Clumps, and therefore clumpy galaxies, have been previously defined differently using minimum thresholds to the luminosity ratio of the brightest detected clumps within each galaxy (Murata et al. 2014) and their total UV contributions (Guo et al. 2015; Shibuya et al. 2016; Huertas-Company et al. 2020; Adams et al. 2022). In this section, we discuss how our defined clump luminosity threshold sample compares to a common definition first presented in Guo et al. (2015), who require that individual clumps contribute ≥8% of the total UV flux of their host galaxies.

The right column of Figure 11, located in the Appendix A, shows demographic results for our SFG sample with clumps defined as having ≥8% of the total UV flux of their host galaxies. We find that the results fully match our complete sample (M_UV ≤ −16.7 AB) results from Section 3.3.3. Again, we find no size or morphology dependence for all mass bins and only a ≥3σ for low-mass galaxy SFR as well as low- and intermediate-mass galaxy color. We note that the applied constraint changed from an intrinsic property (clump luminosity) for our fiducial sample to a minimum flux ratio in which the brightness of the galaxy is a significant factor, as a brighter host galaxy causes a higher clump brightness threshold. It is also known that the size and brightness of a galaxy is directly connected with larger galaxies being brighter on average, shown in the top panel for our own sample in Figure 8. Therefore, we investigate directly the changes to the UV apparent magnitude between the two constraints shown in the middle and bottom panels of Figure 8.

As indicated by the bottom panel of Figure 8, applying the 8% flux ratio minimum switches some of the brightest clumpy galaxies within each mass bin to a nonclumpy classification due to a higher clump brightness threshold redefining their clumps. Compared to our fiducial results, this reclassification directly causes the decrease/increase in medians seen for clumpy/nonclumpy galaxies within our 8% minimum size results in the top panel of Figure 11. Furthermore, higher star formation results in higher UV luminosity from a SFG, and a change to the brightest UV galaxies would also explain the decrease/increase in medians seen in the SFR high-mass bin (second panel of Figure 11). We conclude that both constraints (fiducial and flux ratio ≥8%) provide robust results but lead to different conclusions regarding properties that depend on the host galaxy's brightness. We leave it to future studies to decide whether or not they wish to define their clumps based on intrinsic clump properties (fiducial) or overall galaxy properties (flux ratio ≥8%).

3.4. Star-forming Region Luminosity–Galaxy Properties Relation

As described in detail in Section 2.4, we measured the rest-frame UV luminosity for each clump detected in our UVCANDELS sample. In Figure 9, we directly compare our clump luminosities to several distinct galactic properties (host sSFR, luminosity, size, and normalized clump galactocentric distance). Here, we include all detected star-forming regions beyond our luminosity limit of M_UV ≤ −16 AB to provide a comprehensive picture of star-forming regions and host-galaxy relations independent of our clump definition. Subsequently, this inclusion also increases the dynamical range of the investigated star-forming region luminosities. Each relation was fit linearly to determine a gradient for our distribution of clumps. We also show the Spearman's rank coefficient (ρ- and r-values), which denote the statistical dependence between the rankings of two variables, at the top of each panel to demonstrate that the relations seen are significant beyond a linear fit. For these properties we find robust relations (≥3σ), indicating that on average more luminous clumps reside in small, but luminous, SFGs that have higher sSFR. Furthermore, the rightmost panel of Figure 9 indicates that more luminous clumps are found closer to the galactic center of each SFG, regardless of the host's overall size.

4. Discussion

4.1. What Types of Galaxies Tend to Form Clumps?

Based on our results, our main conclusions are that (i) clumpy galaxies exhibit higher SFRs and appear bluer in rest-frame U − V colors compared to nonclumpy galaxies, and (ii) clumpy galaxies are only marginally larger than nonclumpy galaxies. These two results provide support for the hypothesis that clumps form through VDI.

First, the systematic difference between the median SFRs of clumpy and nonclumpy galaxies is inconsistent with the prediction from major mergers. The second panel of Figure 5 shows that in low/intermediate/high regimes, clumpy galaxies have higher SFRs by a factor of 2, 2, and 1.7, respectively, to those of nonclumpy galaxies. This difference is larger than the difference caused by mergers. According to Pearson et al. (2019), merging galaxies in CANDELS do not significantly affect the SFR of galaxies compared to nonmerging galaxies. Their findings indicate a systematic increase of SFR caused by merger of only a factor of 1.2. Moreover, minor mergers are not able to result in such a large observed SFR difference as well. We assume each minor merger component could contribute an additional SFR up to a few tens of percents to its host galaxy considering that the average clump UV luminosity compared to the host galaxies' UV luminosity is ∼6.6% for our sample (see also Guo et al. 2015; Shibuya et al. 2016). Assuming a generous boost of 10% to host SFR with each minor merger, to increase the host SFR by a factor of ∼2 requires having 10 minor merger components at the same time. This number is much larger than the average clump numbers per galaxy in our sample (Figure 3). Therefore, we argue that the clumpy appearance and high SFR are associated with some internal reasons.

This scenario is consistent with in situ formation through VDI. To form clumps in a low-redshift unstable disk, the Toomre Q parameter should be less than unity (Toomre 1964; Bournaud et al. 2007, 2009; Elmegreen et al. 2007, 2009; Genzel et al. 2008, 2011; Agertz et al. 2009; Dekel et al. 2009, 2022; Ceverino et al. 2010).²⁵ Here, we use the formulas of Genzel et al. (2011) to investigate the dependence of Q on SFR and R_e. We start from Equation (3) of Genzel et al. (2011):

$\begin{eqnarray}&&{Q}_{\mathrm{gas}}=\left(\displaystyle \frac{{\sigma }_{0}}{{V}_{c}}\right)\left(\displaystyle \frac{a({V}_{c}^{2}{R}_{d})/G}{\pi {R}_{d}^{2}{{\rm{\Sigma }}}_{\mathrm{gas}}}\right),\end{eqnarray} \tag{ 1 }$

where σ₀, V_c, R_d, and Σ_gas are the velocity dispersion, circular velocity, disk radius, and cold gas surface density of a disk, respectively. For simplicity, we only discuss the gas component here and ignore all the constants (geometric coefficients a, π, and G). To connect Σ_gas to SFR, we use the inverted Schmidt–Kennicutt law (see Equation (2) of Genzel et al. 2011): ${{\rm{\Sigma }}}_{\mathrm{gas}}\propto {({{\rm{\Sigma }}}_{\mathrm{SFR}})}^{\alpha }\propto {(\mathrm{SFR}/{R}_{d}^{2})}^{\alpha }$ , where α = 0.73. We also have ${V}_{c}\propto \sqrt{{M}_{\mathrm{tot}}/{R}_{d}}$ , where M_tot includes the mass of stars, gas, and dark matter. According to Wuyts et al. (2016), the baryonic budget, $\mathrm{log}({M}_{* }/{M}_{\mathrm{tot}})\sim 0.58$ at z ∼ 1.0, with a small scatter of about 0.2 dex. For simplicity, we assume the scatter is caused mainly by M_∗ dependence (e.g., see Figure 5 of Wuyts et al. 2016) rather than by R_e dependence. Therefore, in a given M_∗ bin, we assume M_tot has no correlation with R_e. We also assume R_d ∝ R_e, the effective radius. This assumption is valid because, on average, the galaxies in our sample have a Sérsic index n ∼ 1 (the bottom panel of Figure 5). For this profile, the radius containing 95% of galaxy light is about 3−4 R_e (see Graham & Driver 2005 for a concise reference of Sérsic R^1/n profiles).

With all above assumptions, we have

$\begin{eqnarray}&&Q\sim {Q}_{\mathrm{gas}}\propto {\sigma }_{0}{M}_{\mathrm{tot}}^{1/2}{R}_{e}^{2\alpha -3/2}{(1/\mathrm{SFR})}^{\alpha }.\end{eqnarray} \tag{ 2 }$

Given that α = 0.73, at a fixed σ₀ and M_tot, we have $Q\propto {R}_{e}^{-0.04}{\mathrm{SFR}}^{-0.73}$ . This result suggests that the higher the SFR a galaxy has, the lower its Q, and therefore the easier it is for the galaxy to form clumps. Meanwhile, Q only shows little, if any, dependence on R_e. Even if we considered a mild correlation between σ₀ and R_e (for example, ${\sigma }_{0}\propto {R}_{e}^{-0.14}$ ; see Newman et al. 2013), the dependence of Q on R_e would still be marginal, $Q\propto {R}_{e}^{-0.18}$ . This deduction is in very good agreement with the top and second panels of Figure 5. Therefore, we argue that our results provide strong supporting evidence for VDI.

4.2. How Luminous Are the Clumps Formed in Different Galaxies?

Another major result of this paper is the correlations between the UV luminosity of star-forming regions and host-galaxy properties (Figure 9). Among these relations, the most interesting one is the negative correlation between clump luminosity and their host-galaxy size. Since galaxy size increases with their M_∗ (van der Wel et al. 2014), to remove the mass dependence we also study this clump luminosity–galaxy size correlation in our three mass bins separately. The negative correlation persists in the low- and intermediate-mass bins. The high-mass bin, however, shows no correlation, likely due to the small sample size and poor number statistics. Here, we discuss the implications of this result.

According to Escala & Larson (2008), the mass of clumps formed through VDI can be calculated as

$\begin{eqnarray}&&{M}_{\mathrm{cl}}\propto {M}_{\mathrm{gas}}{\eta }^{2}={M}_{\mathrm{gas}}{\left(\displaystyle \frac{{M}_{\mathrm{gas}}}{{M}_{\mathrm{tot}}}\right)}^{2}.\end{eqnarray} \tag{ 3 }$

Similar to the discussion above, we have ${M}_{\mathrm{gas}}\,\propto {{\rm{\Sigma }}}_{\mathrm{gas}}{R}_{e}^{2}\propto {{\rm{\Sigma }}}_{\mathrm{SFR}}^{\alpha }{R}_{e}^{2}\propto {\mathrm{SFR}}^{\alpha }{R}_{e}^{2-2\alpha }$ and M_tot is not correlated with R_e at a given M_∗. We then have

$\begin{eqnarray}&&{M}_{\mathrm{cl}}\propto {\mathrm{SFR}}^{3\alpha }{R}_{e}^{3(2-2\alpha )}.\end{eqnarray} \tag{ 4 }$

This relation predicts that the maximum clump mass increases with two parameters: (i) SFR, and (ii) R_e, when α = 0.73. The first correlation with SFR is supported by panels 1 and 2 of Figure 9, if we assume clumps are simple stellar population systems so that their M_UV is a good representative of their M_∗. The second correlation with R_e, however, is opposite to our observed result.

This inconsistency could have a few explanations. First, at face value, it suggests that there is another parameter that determines clump mass rather than R_e. We speculate this parameter is Σ_SFR (or Σ_gas). Indeed, the clump luminosity shows a correlation with Σ_SFR, as depicted in Figure 10. Σ_gas also shows a similar trend if we convert Σ_SFR to Σ_gas by using the Kennicutt–Schmidt law. Since Σ_SFR is inversely proportional to R_e ², this speculation is consistent with the first three panels of Figure 9. Second, in our discussion above, we use clump UV luminosity M_UV to represent clump mass M_cl. This simplification would not be valid if clumps have different stellar populations and dust extinction. Therefore, deriving clump mass M_cl would provide a more straightforward comparison to models. This work will be presented in a future paper. Third, related to the issue of M_cl, Figure 9 in fact shows a mixed result of clump formation and evolution. Its fourth panel shows a gradient of clump luminosity with respect to their normalized galactocentric distance. This result is consistent with the inward-migration scenario of clump evolution (Bournaud et al. 2007, 2014; Elmegreen et al. 2008; Dekel et al. 2009, 2022; Ceverino et al. 2010; Förster Schreiber et al. 2011; Mandelker et al. 2014; Shibuya et al. 2016; Guo et al. 2018; Zanella et al. 2019; Lenkić et al. 2021). Therefore, it is possible that the most luminous clumps (i.e., those found in small galaxies) are also those which have already migrated close to the center of their galaxies. At a given M_∗, small galaxies have higher mass density and therefore shorter dynamical timescale, which would result in a faster clump migration in small galaxies than in large galaxies. During this fast migration, merger or continuing growth of clumps (Bournaud et al. 2007, 2014; Dekel et al. 2009, 2022; Elmegreen et al. 2009) would increase both clump mass and UV luminosity. This scenario is supported by the locations of the most luminous clumps in the second and fourth panels of Figure 9. To further shed light on this scenario, as well as the maximum M_cl, the age of clumps needs to be determined. We will present relevant work in a future paper.

**Figure 10.** Clump luminosity vs. host galactic SFR density. The format is the same as in Figure 9.
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5. Summary and Conclusion

In this work, we used the newly obtained F275W 60 mas mosaics from UVCANDELS for four of the premier CANDELS fields (GOODS-N, GOODS-S, EGS, and COSMOS) to detect our sample of UV-selected clumps at 0.5 ≤ z ≤ 1, thus sampling their rest-frame 1600 Å. By subdividing our host SFGs into "clumpy" and "nonclumpy" galaxies based on whether or not they contain at least one off-center clump within their structure, we determined different distinctions for host-galaxy properties as well as clumpy luminosity relations. Our final fiducial sample applies a luminosity threshold to individual clumps, requiring them to be 3 times brighter in their UV emission than the most massive/brightest H ii regions found within the local Universe. In doing so, we shed light on the physical properties of galaxies that host clumps and what distinguishes them from the general population of SFGs. Furthermore, we have shown several effects on our results of sample selection and constraints that are commonly used throughout the literature to provide a guide toward potential bias in our clump samples for future work. Our major conclusions are listed as follows:

1.
We present the clumpy fraction (the fraction of clumpy galaxies with respect to the total) of our sample of SFGs in Figure 4. We find that for low-mass galaxies f_clumpy ∼ 35%, which decreases to ∼22% for the intermediate- and high-mass bins. This result shows that clumpy SFGs make up a significant fraction of all SFGs at all galaxy masses at 0.5 ≤ z ≤ 1, which is consistent with other UV-selected samples found within the literature.
2.
Using a distinction limit of (≥3σ), we find that clumpy SFGs on average have higher SFRs and are bluer in rest-frame U − V color for low and intermediate masses, and are larger in size for massive SFGs when compared to nonclumpy SFGs of the same mass. Clumpy SFGs are, however, similar in overall morphology to nonclumpy SFGs as both clumpy and nonclumpy SFGs contain disk-like structures. Each of our results supports the scenario of in situ clump formation through VDI.
3.
For the distributions of clump luminosity versus galactic properties, we find that all detected clumps show robust linear relations for host sSFR, UV luminosity, size, and clump galactocentric distance. We conclude that the relations shown indicate inward migration of clumps through their host disk profiles, however future work deriving the clump ages is needed to further confirm this theory.
4.
We test the effect of different galaxy selections and clump definitions on the demographics of clumpy galaxies. The overall result is summarized in Figure 12 in the Appendix A. In each panel with 3 × 3 cells, if any of the four surrounding cells shows a different color from the central cell, the demographic result is changed. Overall, in summary: (i) the demographics of low-mass galaxies are not changed by various galaxy or clump selections; (ii) the lack of difference in Sérsic index between clumpy and nonclumpy galaxies are robust; (iii) using UVJ or sSFR to select SFGs generally does not affect the demographics; and (iv) using a more restrained galaxy or clump selection method to ensure high completeness would reduce the sample size as well as reduce the difference between clump and nonclumpy galaxies (namely, the more conditions one applies, the more similar the two selected populations become).

In future work, we will explore two avenues that will build upon these results. The first project will determine clump properties through SED fitting of the rest-frame FUV (F275W) to mid-IR (F160W) passbands and dust extinction estimates. We aim to determine the most accurate estimates of masses, ages, SFRs (both UV corrected and Hα based), and burstiness for the largest sample of clumps to date. In doing so, we will utilize the ages and established property gradients to shed light on the longevity of clumps as well as possible evolutionary tracks of clumps as galaxies evolve over time. Second, we will compare our results with additional observations out to z ∼ 3 with an ensemble of simulations with varying feedback levels in order to determine maximum constraints on theoretical modeling of galaxies. In brief, the clumpy nature of these substructures can be smoothed out of simulated galaxies if excessive levels of feedback (e.g., UV/IR radiation pressure, supernovae, stellar winds, etc.) are implemented within the models. As we have observed, primordial galaxies host clumps in their morphologies, making it vital that our constraints to feedback reproduce these same clumpy structures within our theoretical models.

Acknowledgments

This work is based on observations with the NASA/ESA Hubble Space Telescope obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. Support for program numbers HST-GO-15647 and HST-AR-15798 was provided through a grant from the STScI under NASA contract NAS5-26555.

D.C. is a Ramon-Cajal Researcher and is supported by the Ministerio de Ciencia, Innovación y Universidades (MICIU/FEDER) under research grant No. PGC2018-094975-C21.

Y.S.D. acknowledges the support from National Key R&D Program of China for grant No. 2022YFA1605300, and the NSFC grant Nos. 12273051 and 11933003.

The specific observations analyzed can be accessed via 10.17909/96zb-g146.

Appendix A: Extensive Review of Sample-selection Effects

Here, we display the plots that indicate the effects of sample selection on our results for our four galactic properties: galaxy size, SFR, color, and Sérsic index. Figure 11 (left) shows the demographic results for our galaxy brightness constraint of M_UV < 25 mag to correct for surface brightness bias. As described in Section 3.3.2, we find this has a major effect on our results as the medians of each mass bin for each galactic property become nearly identical. Figure 11 (right) shows the demographic results for clumps that provide at least 8% of their host galaxy's total UV luminosity.

**Figure 11.** Relations of host-galaxy properties vs. stellar mass for clumpy and nonclumpy galaxies with magnitude F275W ≤ 25 AB (left) and whose clumps contribute at least 8% of the total UV luminosity. From top to bottom, we show host-galaxy size, SFR, color, and morphology. Symbols, colors, and lines are the same as in Figure 5.
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In Figure 12, we show a comprehensive representation of all of our sample-selection comparisons between clumpy and nonclumpy SFGs performed throughout this work. We again show the comparison for galaxy host size, SFR, color, and morphology and represent the two populations as distinct/similar by coloring them as red/cyan squares, respectively. Within this figure, we do not show the results for our 8% flux ratio sample as it produced the same conclusions as our −16.7 AB threshold sample. Therefore, we only represent the luminosity threshold results within Figure 12.

Appendix B: Clump Luminosity Threshold Plots

In Figure 13, the results for the different clump luminosity thresholds for our four galactic properties—galaxy size, SFR, color, and Sérsic index—with no constraint, M_UV ≤ −16 AB, and M_UV ≤ −16.7 AB are shown. We find that including "all" detected clumps within our sample reveals differences between our two populations (in low- and intermediate-mass galaxy size) not present in our fiducial sample. However, the inclusion of all detections does not distinguish the sample of clumps from typical H ii regions. Differences in conclusions for our strict M_UV ≤ −16.7 AB constraint to our fiducial sample for galaxy size may result from low number statistics of clumpy galaxies, as described in the main body of the text.

UV-bright Star-forming Clumps and Their Host Galaxies in UVCANDELS at 0.5 ≤ z ≤ 1

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Abstract

1. Introduction