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— Hubble Space Telescope Advanced Camera for Surveys images showing our SA02 field (top left), SA12 field (top right), SA15 field (bottom left) and SA22 field (bottom right). As described in the text, the tiling of the field pointings were chosen to maximize the integration time on galaxies with known high redshifts. Details are given in Table 1.
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We have used the Hubble Space Telescope's Advanced Camera for Surveys (Ford et al. 2003) to measure the cumulative mass density in morphologically selected early-type galaxies over the redshift range 0.8 < z < 1.7. Our imaging data set covers four well-separated sight lines and is roughly intermediate (in terms of both depth and area) between the G...
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... imaging data cover 67 square arcmin, or 55% of the total area of the GDDS, but by carefully choos- ing the locations of the pointings within the GDDS fields, and by varying the number of pointings per field, we were able to obtain ACS images for 63% of the galaxies in our spectroscopic sample. Fully re- duced ACS F814W images for each of the four fields are shown in Figure 1. Our field orientations were de- fined to produce additional depth for high priority tar- gets within the allocated orbit total. ...
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... as suggested by Bouwens et al. 2005 (see also Iye et al. 2007), significant star-formation activity only begins around z ∼ 6 (when the Universe is already about 1 Gyr old, so that the maximal age of a stellar population at z = 1.7 is 2.8 Gyr instead of the 3.8 Gyr age of the Universe at that redshift), then Figure 2 suggests that one would be able to probe maximally old stellar pop- ulations at solar-neighborhood mass densities out the limits of our survey with 20ks integrations. Our goal in defining the rather complicated-looking ACS imag- ing field geometry shown in Figure 1 was to cover as many GDDS galaxies with known redshifts as possi- ble, subject to the constraint of having at least 12ks of integration everywhere, and up to 33ks of integration in areas where fields overlap. These areas of overlap were chosen to correspond to regions with many high- redshift galaxies. ...
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... adopt a threshold of log 10 (M/M ⊙ ) > 10.5. As shown in Figure 1 of Paper III, this is the limit to which the GDDS is mass- complete for z < 1.7. In other words, red galaxies Fig. 6.-Postage-stamp images showing the morphologies of the 30 objects classified as early-type galaxies on the basis of the system described in the text. ...
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... color-selected samples cannot be used to de- fine samples of early-type galaxies without significant contamination, it is interesting to consider whether better samples of early-types might be constructed us- ing spectroscopy. Figure 10 shows the F814W images of the 21 galaxies classified as purely quiescent (class '001' in the taxonomy of Paper I) in our ACS sam- ple. About 2/3 of the sample (13/21) are early-types using our automated classifier. ...
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... conclude that a fairly good sample of early-type galaxies could be defined simply by selecting purely quiescent systems. However, Figure 11 makes it clear that care would have to be taken to exclude objects showing even small amounts of star-formation. This figure shows a montage of the 12 galaxies in our imag- ing sample with spectral classifications corresponding to a dominant old stellar population contaminated by low-level star formation (class '011' in the taxonomy of Paper I). ...
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... large symbols. Morphologically classified early-type galaxies are circled. A fraction of the other red galaxies are massive are highly-reddened star-forming galaxies ( Noll et al. 2006). The line shown near the top of the figure is the evolutionary track of a massive instantaneous starburst forming all of its stars at z = 3. See text for details. Fig. 10.-5 arcsec by 5 arcsec images of the 21 galaxies in our ACS imaging sample with spectral classifications corresponding to quiescent stellar populations (class 001). Early-type galaxies are circled. Gray regions surrounding groups of postage stamps indicate which of three broad redshift bins the objects fall within. These bins are used ...
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... with spectral classifications corresponding to quiescent stellar populations (class 001). Early-type galaxies are circled. Gray regions surrounding groups of postage stamps indicate which of three broad redshift bins the objects fall within. These bins are used to calculate a cumulative mass function, as described in §5. See text for details. Fig. 11.-5 arcsec by 5 arcsec images showing the morphologies of the 12 galaxies in our imaging sample with spectral classifications corresponding to a dominant old stellar population augmented by low-level star formation (class 011). Early-type galaxies are circled. Gray regions surrounding groups of postage stamps indicate which of three ...
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... the Gini coefficient measured in a single red band (F814W) can be used as a simple and very robust classifier of early-type galaxy mor- phology out to z ∼ 2. We emphasize at the outset that this claim is true only when data is deep enough to allow quasi-Petrosian isophotes to be used to calculate the Gini coefficient, as described in the text. Fig. 12.-Asymmetry vs. Gini coefficient for 800 nearby galaxies observed in g'-band as part of the Sloan Digital Sky Survey. Quasi-Petrosian thresholds were used when measuring both quantities, as described in the text. Galaxies classified visually as being early-type systems are shown in red. The vertical line denotes the G = 0.5 cut used to ...
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... ACS imaging sample has a signal-to-noise ratio floor of 100 (only a single galaxy in our ACS imaging sample has has a signal-to-noise ratio below this) so our analysis will be restricted to galaxies with a u'-band signal-to-noise ratio > 100. Figure 12 shows the Asymmetry vs. Gini coefficient diagram for g'-band imaging of our SDSS sample. Galaxies classified visually by one of us (Preethi Nair) as being early-type systems are shown in red. ...
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... G = 0.5 cut evidently does a good job of distinguishing high signal-to-noise g'-band images of SDSS early- type galaxies from the rest of the galaxy population, but how robust is this cut to changes in rest wavelength of observation, and to decreasing signal-to-noise? Figure 13 is an attempt to address this question. The top row of Figure 13 shows the Gini coefficients of our SDSS reference sample measured at different wavelengths (using u', g', and i' filters) plotted against the Gini coefficients in g'-band. ...
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... G = 0.5 cut evidently does a good job of distinguishing high signal-to-noise g'-band images of SDSS early- type galaxies from the rest of the galaxy population, but how robust is this cut to changes in rest wavelength of observation, and to decreasing signal-to-noise? Figure 13 is an attempt to address this question. The top row of Figure 13 shows the Gini coefficients of our SDSS reference sample measured at different wavelengths (using u', g', and i' filters) plotted against the Gini coefficients in g'-band. The diagonal line shown in each panel delineates a perfect mapping between the two parameters, i.e. no change in Gini as a function of wavelength. ...
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... of the u'-band Gini coefficient probe wavelengths blueward of the 4000Å4000˚4000Å break, and our na¨ıvena¨ıve expectation was that Gini coefficients should be significantly different in u'-band when compared with measurements made at wavelengths redward of the break. At first inspection Figure 13 does seem to show this, in the form of systematic offsets between the g'-band and u'-band images. However, a more careful inspection shows that the trends seen are almost certainly due to the the low signal-to-noise ratio of the u'-band data, instead of being due to systematic differences in the intrinsic g'-band and u'-band images of galaxies. ...
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... panel in Figure 13 records the mean signal-to-noise level of the sample being plotted. It is seen that the SDSS u'-band data has a mean signal-to-noise ratio of ∼ 130, which is a factor two to three lower than the mean signal-to- noise ratios of our ACS images, and about a factor of five lower than the signal-to-noise ratios of the corresponding SDSS g', r', and i' images. ...
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... is a crucial point, because the ACS F814W filter begins to probe blueward of the 4000Å4000˚4000Å break at z > 1, where the bulk of our data lies. Since the SDSS u'-band filter data would seem to provide the best match to the rest-frame wavelengths being probed by much of our ACS data, understanding the reason why the Gini coefficients of u'-band data shown in Figure 13 appear be systematically lower than those measured at longer wavelengths is of special significance. The columnar base of the 'T' in Figure 13 is an attempt to understand the u'-band data by showing how the Gini coefficient of g'-band sample changes when noise is added to the images to lower the mean signal-to-noise ratios of the samples plotted. ...
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... the SDSS u'-band filter data would seem to provide the best match to the rest-frame wavelengths being probed by much of our ACS data, understanding the reason why the Gini coefficients of u'-band data shown in Figure 13 appear be systematically lower than those measured at longer wavelengths is of special significance. The columnar base of the 'T' in Figure 13 is an attempt to understand the u'-band data by showing how the Gini coefficient of g'-band sample changes when noise is added to the images to lower the mean signal-to-noise ratios of the samples plotted. The mean signal-to-noise ratio of the noise-degraded g'-band data in middle panel is similar to the mean signal-to-noise ratio for galaxies at z > 1.2 in our sample. ...
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... more explicit comparison of u'-band and noise-degraded g'-band Gini coefficients of our local calibration sample is shown in Figure 14. The mean signal-to-noise ratio of the g'-band sample has been harmonized to be nearly identical that that of the u'-band sample. ...
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... conclude this appendix with Figure 15, which shows an object-by-object postage-stamp image montage of galaxies near the G = 0.5 border of the Gini coefficient vs. redshift diagram. This diagram can be used to inspect Fig. 14.-Gini coefficients of u'-band galaxies in the SDSS compared to Gini coefficients of corresponding noise- degraded g'-band images. ...
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... conclude this appendix with Figure 15, which shows an object-by-object postage-stamp image montage of galaxies near the G = 0.5 border of the Gini coefficient vs. redshift diagram. This diagram can be used to inspect Fig. 14.-Gini coefficients of u'-band galaxies in the SDSS compared to Gini coefficients of corresponding noise- degraded g'-band images. The mean signal-to-noise ratios of the samples have been harmonized to be nearly identical (∼ 130). The scatter is consistent with the random measurement error at these low signal-to-noise levels (see Nair ...
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... identical (∼ 130). The scatter is consistent with the random measurement error at these low signal-to-noise levels (see Nair et al. 2007 for details). As described in the text, when a quasi-Petrosian formalism is adopted for making the measurements, an individual galaxy's Gini coefficient is nearly independent of its wavelength of observation. Fig. 15.-An object-by-object comparison of Gini coefficient vs. redshift for galaxies near the border of the G = 0.5 cutoff threshold used to discriminate between early-type galaxies and all other systems. Objects in the gray region shown are worth looking at individually because they are at redshifts where F814W imaging is probing blueward of ...
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... in Fig. 5, the border of each postage stamp is is colored according to its spectral classification based on the system described in Paper I. See caption to Fig.5 for details. the morphologies of objects near the cutoff threshold used to discriminate between early-type galaxies and all other systems in the present paper. Objects in the gray region shown in Figure 15 shown are of particular interest, because these systems are at redshifts where F814W imaging is probing blueward of the 4000Å4000˚4000Å break, and also near enough to the G = 0.5 cutoff that they could conceivably be brought below it at very low signal-to-noise. However, all these objects are seen to be high signal-to-noise systems, and only one object (with a high star-formation rate spectrum) has a visual morphology even remotely consistent with that of an early-type galaxy. ...
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Citations
... The solid line between irregular and spiral galaxies is defined as log 10 (Asymmetry) = 2.353 × log 10 (Gini) + 0.353, while the solid line between spiral and elliptical galaxies is defined as log 10 (Asymmetry) = 5.5 × log 10 (Gini)+0.825. We also include a horizontal dashed line to separate the region where major mergers are expected, defined by log(Asymmetry) > −0.46 (Conselice 2003) and a vertical dashed line at log(Gini) = −0.3 which separates latetype from early-type galaxies according to Abraham et al. (2007). In Figure 9, bottom panel, we show the Gini parameter against M20. ...
... Here, we include dividing lines between the regions of mergers, Sb/Sc/Irr and E/S0/Sa galaxy types taken from Lotz et al. (2008), according to the following definitions, Mergers: G > −0.14 × M20 + 0.33; Early(E/S0/Sa): G −0.14 × M20 + 0.33, and G > 0.14×M20 + 0.80; Late (Sb/Ir): G −0.14×M20 + 0.33, and G 0.14 × M20 + 0.80. We note in both panels of Figure 9, that AGNs with outflow signatures are preferentially located in the region corresponding to early-type/elliptical galaxies, with -+ 95 9 1 % of them found in the area defined by Abraham et al. (2007) and -+ 86 11 4 % inside the areas defined by Capak et al. (2007) and Lotz et al. (2008). While for the AGNs with no asymmetric component in [O III], -+ 55 4 7 % are early-type galaxies according to Abraham et al. (2007) and Capak et al. (2007), and -+ 41 5 6 % according to the limits of Lotz et al. (2008). ...
... We note in both panels of Figure 9, that AGNs with outflow signatures are preferentially located in the region corresponding to early-type/elliptical galaxies, with -+ 95 9 1 % of them found in the area defined by Abraham et al. (2007) and -+ 86 11 4 % inside the areas defined by Capak et al. (2007) and Lotz et al. (2008). While for the AGNs with no asymmetric component in [O III], -+ 55 4 7 % are early-type galaxies according to Abraham et al. (2007) and Capak et al. (2007), and -+ 41 5 6 % according to the limits of Lotz et al. (2008). We do not obtain any galaxies with outflows in the region corresponding to mergers, and -+ 14 2 5 %, -+ 7 1 4 %, and -+ 4 1 4 % of AGN without outflows are mergers in accordance to Conselice (2003), Capak et al. (2007) and Lotz et al. (2008) respectively. ...
Active galactic nucleus (AGN) driven outflows can have a significant impact on the evolution of the host galaxy. In this work, we compare the properties of galaxies that host AGNs with and without outflows. Our sample consists of 103 AGNs identified by mid-IR color–color selection and confirmed with optical spectroscopy at a redshift range of 0.3 ≲ z ≲ 0.9. We fit the [O iii ] λ 5007 line using spectra from the zCOSMOS survey to identify and study the occurrence of outflows. We find that ionized outflows are present in ∼25% of our sample, with the largest incidence at the highest [O iii ] and X-ray luminosity bins. The fastest outflows are found in the more extended and massive galaxies. We do not observe a difference in the star formation rate of AGNs with outflows compared to AGNs without outflows. From visual inspection and nonparametric morphological studies, we obtain that outflows are preferentially observed in galaxies with disk-type and elliptical morphologies.
... We make use of the Tasca Morphology Catalog (v1.1) (Tasca et al. 2009), which contains the morphological information of 237,192 sources in the COSMOS field that have Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) observations (Leauthaud et al. 2007). The morphological parameters are estimated using the MORPHEUS code (Abraham et al. 2007). To transform morphological parameters into morphological classes, they first eyeballed a training set of ∼500 galaxies into early, spiral, and irregular types, and performed a machine-learning technique to derive the types of remaining galaxies with the associated morphological parameters. ...
We present a systematic study of the environmental impact on star formation activities of galaxies using a mass-complete sample of ∼170k galaxies at z < 4 from the latest COSMOS2020 catalog. At z < 1, we find that the mean star formation rate (SFR) of all galaxies decreases with increasing density of the environment. However, when we only consider star-forming galaxies, the mean SFR becomes independent of the environment at z < 1. At z > 2, we observe a clear positive correlation between the SFR and the density of the environment for all the galaxies. On the other hand, the stellar mass of the galaxies increases significantly with the environment at all redshifts except for star-forming galaxies at z < 1. The fraction of quiescent galaxies increases with increasing density of the environment at z < 2, and the morphology–density relation is confirmed to be present up to z ∼ 1. We also find that environmental quenching is negligible at z > 1, whereas mass quenching is the dominant quenching mechanism for massive galaxies at all redshifts. Based on these results, we argue that stellar mass-regulated physical processes might be the major driving force for star formation activities of galaxies. At low redshift ( z < 1) massive galaxies are quenched primarily due to their high mass, resulting in a normal SFR–density relation. At high redshift ( z > 2) most of the galaxies are star-forming ones tightly following the star-forming main sequence, and the difference in their stellar mass in different environments naturally leads to a reversal of the SFR–density relation.
... Using the Morpheus program (Abraham et al. 2007), we calculate the nonparametric morphological parameters: the Gini coefficient (G) and the normalized second-order moment of the brightest 20% of the galaxy's flux (M 20 ) for all galaxies in our sample. Thus, we can investigate the correspondence between the galaxy morphological classification results and the physical relations between the various types of galaxies. ...
By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H -band-selected massive galaxies in the COSMOS-DASH field, which includes 17,292 galaxies with stellar mass M ⋆ > 10 ¹⁰ M ⊙ at 0.5 < z < 2.5. The classification scheme is designed to provide a complete morphology classification for galaxies via a combination of two machine-learning steps. We first use an unsupervised machine-learning method (i.e., bagging-based multiclustering) to cluster galaxies into five categories: spherical (SPH), early-type disk, late-type disk, irregular (IRR), and unclassified. About 48% of the galaxies (8258/17,292) are successfully clustered during this step. For the remaining sample, we adopt a supervised machine-learning method (i.e., GoogLeNet) to classify them, during which galaxies that are well classified in the previous step are taken as our training set. Consequently, we obtain a morphology classification result for the full sample. The t-SNE test shows that galaxies in our sample can be well aggregated. We also measure the parametric and nonparametric morphologies of these galaxies. We find that the Sérsic index increases from IRR to SPH and the effective radius decreases from IRR to SPH, consistent with the corresponding definitions. Galaxies from different categories are separately distributed in the G – M 20 space. Such consistencies with other characteristic descriptions of galaxy morphology demonstrate the reliability of our classification result, ensuring that it can be used as a basic catalog for further galaxy studies.
... Using the Morpheus program (Abraham et al. 2007), we calculate the nonparametric morphological parameters Gini coefficient (G) and the normalized second-order moment of the brightest 20% of the galaxy's flux (M 20 ) for all galaxies in our sample. Thus, we can investigate the correspondence between the galaxy morphological classification results and the physical relations between the various types of galaxies. ...
By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H-band selected massive galaxies in the COSMOS-DASH field, which includes 17292 galaxies with stellar mass $M_{\star}>10^{10}~M_{\odot}$ at $0.5<z<2.5$. The classification scheme is designed to provide a complete morphology classification for galaxies via a combination of two machine-learning steps. We first use an unsupervised machine learning method (i.e., bagging-based multi-clustering) to cluster galaxies into five categories: spherical (SPH), early-type disk (ETD), late-type disk (LTD), irregular (IRR), and unclassified (UNC). About 48\% of galaxies (8258/17292) are successfully clustered during this step. For the remaining sample, we adopt a supervised machine learning method (i.e., GoogLeNet) to classify them, during which galaxies that are well-classified in the previous step are taken as our training set. Consequently, we obtain a morphology classification result for the full sample. The t-SNE test shows that galaxies in our sample can be well aggregated. We also measure the parametric and nonparametric morphologies of these galaxies. We find that the S\'{e}rsic index increases from IRR to SPH and the effective radius decreases from IRR to SPH, consistent with the corresponding definitions. Galaxies from different categories are separately distributed in the $G$--$M_{20}$ space. Such consistencies with other characteristic descriptions of galaxy morphology demonstrate the reliability of our classification result, ensuring that it can be used as a basic catalog for further galaxy studies.
... Morphological studies have played a key role since the earliest days of extragalactic astronomy; Hubble's (1926) "tuning fork" morphological classification system is still in widespread use, and research continues into when in the universe's history the earliest irregular, clumpy progenitors give way to the regular morphological types it depicts (see Conselice 2014 for a review). Previous work, driven primarily by deep Hubble Space Telescope (HST) observations, determined that the modern Hubble sequence was not yet in place by z ∼ 1.5 (Abraham et al. 1996a(Abraham et al. , 2007Elmegreen et al. 2007;Conselice et al. 2011;Elmegreen & Elmegreen 2013). At z > 2 the galaxy population is dominated by irregular morphologies (Conselice et al. 2005;Buitrago et al. 2013;van Dokkum et al. 2013;Conselice 2014), while kinematic observations suggest an epoch of early disk assembly (e.g., Wisnioski et al. 2015;Simons et al. 2017; see Glazebrook 2013 for a review). ...
... For each of our sources we automatically calculate values of the Gini coefficient (G) and asymmetry (A) parameters from the rest-frame i-band images, following the formulation of Abraham et al. (1996b) and Abraham et al. (2007). The Gini coefficient is high in concentrated and symmetrical early-type galaxies, and is more robust against isophote thresholds than the standard concentration parameter (Abraham et al. 2007), but can also be high in asymmetrical late-type galaxies dominated by a few bright clumps. ...
... For each of our sources we automatically calculate values of the Gini coefficient (G) and asymmetry (A) parameters from the rest-frame i-band images, following the formulation of Abraham et al. (1996b) and Abraham et al. (2007). The Gini coefficient is high in concentrated and symmetrical early-type galaxies, and is more robust against isophote thresholds than the standard concentration parameter (Abraham et al. 2007), but can also be high in asymmetrical late-type galaxies dominated by a few bright clumps. The asymmetry parameter A is determined by calculating the residual difference of a galaxy with its own rotated image, along with a noise correction (per Abraham et al. 1996a;Lotz et al. 2004). ...
We present a rest-frame optical morphological analysis of galaxies observed with the NIRCam imager on the James Webb Space Telescope (JWST) as part of the GLASS-JWST Early Release Science program. We select 388 sources at redshifts 0.8 < z < 5.4 and use the seven 0.9–5 μ m NIRCam filters to generate rest-frame gri composite color images, and conduct visual morphological classification. Compared to Hubble Space Telescope (HST)–based work we find a higher incidence of disks and bulges than expected at z > 1.5, revealed by rest-frame optical imaging. We detect 123 clear disks (58 at z > 1.5) of which 76 have bulges. No evolution of bulge fraction with redshift is evident: 61% at z < 2 ( N = 110) versus 60% at z ≥ 2 ( N = 13). A stellar mass dependence is evident, with bulges visible in 80% of all disk galaxies with mass >10 9.5 M ⊙ ( N = 41) but only 52% at M < 10 9.5 M ⊙ ( N = 82). We supplement visual morphologies with nonparametric measurements of Gini and asymmetry coefficients in the rest-frame i band. Our sources are more asymmetric than local galaxies, with slightly higher Gini values. When compared to high- z rest-frame ultraviolet measurements with HST, JWST shows more regular morphological types such as disks, bulges, and spiral arms at z > 1.5, with smoother (i.e., lower Gini) and more symmetrical light distributions.
... Nonparametric methods are usually used to identify irregular structures in galaxies, especially for high-redshift galaxies, with high irregularity (Bluck et al. 2012;Conselice 2014). We have performed the measurements of the Gini coefficient (G; Lotz et al. 2004) and the second-order moment of the 20% brightest pixels (M 20 ; Lotz et al. 2004) on the near-IR images using the MORPHEUS software developed by Abraham et al. (2007). More detailed definitions and calculations for these nonparametric measurements refer to Gu et al. (2018). ...
To investigate the effects of environment in the quenching phase, we study the empirical relations for green valley (GV) galaxies between overdensity and other physical properties (i.e., effective radius r e , Sérsic indices n , and specific star formation rate (sSFR)). Based on five 3D-HST/CANDELS fields, we construct a large sample of 2126 massive ( M ⋆ > 10 ¹⁰ M ☉ ) GV galaxies at 0.5 < z < 2.5 and split it into the higher overdensity quarter and the lower overdensity quarter. The results shows that GV galaxies in denser environments have higher n values and lower sSFR at 0.5 < z < 1, while there is no discernible distinction at 1 < z < 2.5. No significant enlarging or shrinking is found for GV galaxies in different environments within the same redshift bin. This suggests that a dense environment would promote the growth of bulges and suppress star formation activity of GV galaxies at 0.5 < z < 1.5 but would not affect the galaxy size. We also study the dependence of the fraction of three populations (blue cloud, GV, and red sequence) on both environments and M ⋆ . At a given M ⋆ , blue cloud fraction goes down with increasing environment density, while red sequence fraction is opposite. For the most massive GV galaxies, a sharp drop appears in the denser environment. Coupled with the mass dependence of three fractions in different redshift bins, our result implies that stellar mass and environments jointly promote the quenching process. Such a dual effect is also confirmed by recalculating the new effective GV fraction as the number of GV galaxies over the number of nonquiescent galaxies.
... Morphological studies have played a key role since the earliest days of extragalactic astronomy; Hubble's (1926) 'tuning fork' morphological classification system is still in widespread use, and research continues into when in the Universe's history the earliest irregular, clumpy progenitors give way to the regular morphological types it depicts (see Conselice 2014 for a review). Previous work, driven primarily by deep Hubble Space Telescope (HST) observations, determined that the modern Hubble sequence was not yet in place by z ∼ 1.5 (Elmegreen et al. 2007;Abraham et al. 2007;Conselice et al. 2011;Elmegreen & Elmegreen 2013;Abraham et al. 1996a). At z > 2 the galaxy population is dominated by irregular morphologies (Conselice et al. 2005;van Dokkum et al. 2013;Buitrago et al. 2013;Conselice 2014), while kinematic observations suggest an epoch of early disk assembly (e.g. ...
... For each of our sources we automatically calculate values of the Gini coefficient (G) and asymmetry (A) parameters from the rest-frame i-band images, following the formulation of Abraham et al. (1996b) and Abraham et al. (2007). The Gini coefficient is high in concentrated and symmetrical early type galaxies, and is more robust against isophote thresholds than the standard concentration parameter (Abraham et al. 2007), but can also be high in asymmetrical late type galaxies dominated by a few bright clumps. ...
... For each of our sources we automatically calculate values of the Gini coefficient (G) and asymmetry (A) parameters from the rest-frame i-band images, following the formulation of Abraham et al. (1996b) and Abraham et al. (2007). The Gini coefficient is high in concentrated and symmetrical early type galaxies, and is more robust against isophote thresholds than the standard concentration parameter (Abraham et al. 2007), but can also be high in asymmetrical late type galaxies dominated by a few bright clumps. The asymmetry parameter A is determined by calculating the residual difference of a galaxy with its own rotated image, along with a noise correction (per Abraham et al. 1996a;Lotz et al. 2004). ...
We present a rest-frame optical morphological analysis of galaxies observed with the NIRCam imager on the James Webb Space Telescope (JWST) as part of the GLASS Early Release Science program. We select 217 sources at redshifts 0.8 < z < 5.4 and use the seven 0.9-5um NIRCam filters to generate rest-frame gri composite color images, and conduct visual morphological classification. Compared to HST-based work we find a higher incidence of disks and bulges than expected at z > 1.5, revealed by rest frame optical imaging. We detect 73 clear disks (43 at z > 1.5) of which 45 have bulges. No evolution of bulge fraction with redshift is evident: 60% at z < 2 (N = 26) versus 64% at z >= 2 (N = 19). A stellar mass dependence is evident, with bulges visible in 47% of all disk galaxies with mass 10^9.5 M_sun (N = 30) but only 9% at M < 10^9.5 M_sun (N = 15). We supplement visual morphologies with non-parametric measurements of Gini and Asymmetry coefficients in the rest-frame i-band. Our sources are more asymmetric than local galaxies, with slightly higher Gini values. When compared to high-z rest-frame ultraviolet measurements with Hubble Space Telescope, JWST shows more regular morphological types such as disks, bulges and spiral arms at z > 1.5, with smoother (i.e. lower Gini) and more symmetrical light distributions. The unexpected prevalence of detectable bulges and regular morphology at z > 1.5 will allow new tests of theoretical models of galaxy evolution.
... The nonparametric measurements are also introduced. We take the measurements of Gini and M 20 using the program Morpheus developed by Abraham et al. (2007) on the H-band (F160W) images. The Gini coefficient (G) is defined as (Lotz et al. 2004) ...
In order to obtain morphological information of unlabeled galaxies, we present an unsupervised machine-learning (UML) method for morphological classification of galaxies, which can be summarized as two aspects: (1) the methodology of convolutional autoencoder (CAE) is used to reduce the dimensions and extract features from the imaging data; (2) the bagging-based multiclustering model is proposed to obtain the classifications with high confidence at the cost of rejecting the disputed sources that are inconsistently voted. We apply this method on the sample of galaxies with H < 24.5 in CANDELS. Galaxies are clustered into 100 groups, each contains galaxies with analogous characteristics. To explore the robustness of the morphological classifications, we merge 100 groups into five categories by visual verification, including spheroid, early-type disk, late-type disk, irregular, and unclassifiable. After eliminating the unclassifiable category and the sources with inconsistent voting, the purity of the remaining four subclasses are significantly improved. Massive galaxies ( M * > 10 ¹⁰ M ⊙ ) are selected to investigate the connection with other physical properties. The classification scheme separates galaxies well in the U − V and V − J color space and Gini– M 20 space. The gradual tendency of Sérsic indexes and effective radii is shown from the spheroid subclass to the irregular subclass. It suggests that the combination of CAE and multiclustering strategy is an effective method to cluster galaxies with similar features and can yield high-quality morphological classifications. Our study demonstrates the feasibility of UML in morphological analysis that would develop and serve the future observations made with China Space Station telescope.
... To quantitatively describe the bulge of a galaxy, we perform the nonparametric measurements on the near-IR (NIR) images, using the Morpheus software developed by Abraham et al. (2007). The nonparametric parameter refers to the concentration index (C), which can describe the concentration of the surface brightness distribution of a galaxy. ...
... Nonparametric measurements are performed on the NIR images to derive the concentration index (C) by using the Morpheus software (Abraham et al. 2007). The concentration index C, defined by Abraham et al. (1994), can be calculated by the ratio between the integral flux within the inner isophotal radius, 0.3R, and the integral flux within the outer isophotal radius, R. For a given galaxy with a high C, this implies that the light of a galaxy is concentrated at the center, and a galaxy with a higher C might further possess a centrally concentrated bulge, which can bind more masses through its central gravitational potential. ...
... The standard errors of medians are estimated by bootstrapping the samples in each stellar mass bin 1000 times. Kauffmann et al. 2004;Peng et al. 2010;Woo et al. 2013;Abraham et al. 2007). While this situation remains controversial at intermediate to high redshifts, the star formation of galaxies is found to be enhanced in a dense environment (e.g., Elbaz et al. 2007;Cooper et al. 2008), or to be not significant related to the environment (e.g., Darvish et al. 2016), or to be similar to the relation as in the local universe (e.g., Patel et al. 2009). ...
Several mechanisms for the transformation of blue star-forming to red quiescent galaxies have been proposed, and the green valley (GV) galaxies amid them are widely accepted in a transitional phase. Thus, comparing the morphological and environmental differences of the GV galaxies with early-type disks (ETDs; bulge dominated and having a disk) and late-type disks (LTDs; disk dominated) is suitable for distinguishing the corresponding quenching mechanisms. A large population of massive ( M * ≥ 10 ¹⁰ M ⊙ ) GV galaxies at 0.5 ≤ z ≤ 1.5 in 3D-HST/CANDELS is selected using extinction-corrected ( U – V ) rest color. After eliminating any possible active galactic nucleus candidates and considering the “mass-matching,” we finally construct two comparable samples of GV galaxies with either 319 ETD or 319 LTD galaxies. Compared to the LTD galaxies, it is found that the ETD galaxies possess higher concentration index and lower specific star formation rate, whereas the environments surrounding them are not different. This may suggest that the morphological quenching may dominate the star formation activity of massive GV galaxies rather than the environmental quenching. To quantify the correlation between the galaxy morphology and the star formation activity, we define a dimensionless morphology quenching efficiency Q mor and find that Q mor is not sensitive to the stellar mass and redshift. When the difference between the average star formation rate of ETD and LTD galaxies is about 0.7 M ⊙ yr ⁻¹ , the probability of Q mor ≳ 0.2 is higher than 90%, which implies that the degree of morphological quenching in GV galaxies might be described by Q mor ≳ 0.2.
... To describe the morphological properties of galaxies in our sample, we also perform our own non-parametric structural measurements using the MORPHEUS software. The MORPHEUS has been modified by Abraham et al. (2007) to accommodate new statistics and larger input images. The non-parametric parameters include the Gini coefficient (Gini) and the concentration index (C). ...
We investigate the differences in the stellar population properties, the structure, and the environment between massive compact star-forming galaxies (cSFGs) with or without active galactic nucleus (AGN) at $2<z<3$ in the five 3D-HST/CANDELS fields. In a sample of 221 massive cSFGs, we constitute the most complete AGN census so far, identifying 66 AGNs by the X-ray detection, the mid-infrared color criterion, and/or the SED fitting, while the rest (155) are non-AGNs. Further dividing these cSFGs into two redshift bins, i.e., $2<z<2.5$ and $2.5 \leq z<3$, we find that in each redshift bin the cSFGs with AGNs have similar distributions of the stellar mass, the specific star formation rate, and the ratio of $L_{\rm IR}$ to $L_{\rm UV}$ to those without AGNs. After having performed a two-dimensional surface brightness modeling for those cSFGs with X-ray-detected AGNs (37) to correct for the influence of the central point-like X-ray AGN on measuring the structural parameters of its host galaxy, we find that in each redshift bin the cSFGs with AGNs have comparable distributions of all concerned structural parameters, i.e., the Sersic index, the 20\%-light radius, the Gini coefficient, and the concentration index, to those without AGNs. With a gradual consumption of available gas and dust, the structure of cSFGs, indicated by the above structural parameters, seem to be slightly more concentrated with decreasing redshift. At $2<z<3$, the similar environment between cSFGs with and without AGNs suggests that their AGN activities are potentially triggered by internal secular processes, such as gravitational instabilities or/and dynamical friction.
