Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection
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79 ASTRONOMY AND ASTROPHYSICS↗
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Galaxy zoo builder: Morphological dependence of spiral galaxy pitch angle
ABSTRACT Spiral structure is ubiquitous in the Universe, and the pitch angle of arms in spiral galaxies provide an important observable in efforts to discriminate between different mechanisms of spiral arm formation and evolution. In this paper, we present a hierarchical Bayesian approach to galaxy pitch angle determination, using spiral arm data obtained through the Galaxy Builder citizen science project. We present a new approach to deal with the large variations in pitch angle between different arms in a single galaxy, which obtains full posterior distributions on parameters. We make use of our pitch angles to examine previously reported links between bulge and bar strength and pitch angle, finding no correlation in our data (with a caveat that we use observational proxies for both bulge size and bar strength which differ from other work). We test a recent model for spiral arm winding, which predicts uniformity of the cotangent of pitch angle between some unknown upper and lower limits, finding our observations are consistent with this model of transient and recurrent spiral pitch angle as long as the pitch angle at which most winding spirals dissipate or disappear is larger than 10°.
Lingard, Timothy↗
SDSS-IV MaNGA: The kinematic-morphology of galaxies on the mass versus star-formation relation in different environments
ABSTRACT We study the link between the kinematic-morphology of galaxies, as inferred from integral-field stellar kinematics, and their relation between mass and star formation rate. Our sample consists of ∼3200 galaxies with integral-field spectroscopic data from the MaNGA survey (Mapping Nearby Galaxies at Apache Point Observatory) with available determinations of their effective stellar angular momentum within the half-light radius $\lambda _{R_e}$. We find that for star-forming galaxies, namely along the star formation main sequence (SFMS), the $\lambda _{R_e}$ values remain large and almost unchanged over about two orders of magnitude in stellar mass, with the exception of the lowest masses $\mathcal {M}_{\star }\lesssim 2\times 10^{9} \, \mathcal {M}_{\odot }$, where $\lambda _{R_e}$ slightly decreases. The SFMS is dominated by spiral galaxies with small bulges. Below the SFMS, but above the characteristic stellar mass $\mathcal {M}_{\rm crit}\approx 2\times 10^{11} \, \mathcal {M}_{\odot }$, there is a sharp decrease in $\lambda _{R_e}$ with decreasing star formation rate (SFR): massive galaxies well below the SFMS are mainly slow-rotator early-type galaxies, namely genuinely spheroidal galaxies without discs. Below the SFMS and below $\mathcal {M}_{\rm crit}$ the decrease of $\lambda _{R_e}$ with decreasing SFR becomes modest or nearly absent: low-mass galaxies well below the SFMS, are fast-rotator early-type galaxies, and contain fast-rotating stellar discs like their star-forming counterparts. We also find a small but clear environmental dependence for the massive galaxies: in the mass range $10^{10.9}\!-\!10^{11.5} \, \mathcal {M}_{\odot }$, galaxies in rich groups or denser regions or classified as central galaxies have lower values of $\lambda _{R_e}$. While no environmental dependence is found for galaxies of lower mass. We discuss how the above results can be understood as due to the different star formation and mass assembly histories of galaxies with varying mass.
Wang, Bitao↗
Classifying Seyfert Galaxies with Deep Learning
The traditional classification for a subclass of the Seyfert galaxies is visual inspection or using a quantity defined as a flux ratio between the Balmer line and forbidden line. One algorithm of deep learning is the convolution neural network (CNN), which has shown successful classification results. We build a one-dimensional CNN model to distinguish Seyfert 1.9 spectra from Seyfert 2 galaxies. We find that our model can recognize Seyfert 1.9 and Seyfert 2 spectra with an accuracy of over 80% and pick out an additional Seyfert 1.9 sample that was missed by visual inspection. We use the new Seyfert 1.9 sample to improve the performance of our model and obtain a 91% precision of Seyfert 1.9. These results indicate that our model can pick out Seyfert 1.9 spectra among Seyfert 2 spectra. We decompose the Hα emission line of our Seyfert 1.9 galaxies by fitting two Gaussian components and derive the line width and flux. We find that the velocity distribution of the broad Hα component of the new Seyfert 1.9 sample has an extending tail toward the higher end, and the luminosity of the new Seyfert 1.9 sample is slightly weaker than the original Seyfert 1.9 sample. This result indicates that our model can pick out the sources that have a relatively weak broad Hα component. In addition, we check the distributions of the host galaxy morphology of our Seyfert 1.9 samples and find that the distribution of the host galaxy morphology is dominated by a large bulge galaxy. In the end, we present an online catalog of 1297 Seyfert 1.9 galaxies with measurements of the Hα emission line.
79 ASTRONOMY AND ASTROPHYSICS↗
Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging
There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or an investigation for maximizing their effectiveness. We carry out a comparison between several common machine learning methods for galaxy classification [Convolutional Neural Network (CNN), K-nearest neighbour, logistic regression, Support Vector Machine, Random Forest, and Neural Networks] by using Dark Energy Survey (DES) data combined with visual classifications from the Galaxy Zoo 1 project (GZ1). Our goal is to determine the optimal machine learning methods when using imaging data for galaxy classification. We show that CNN is the most successful method of these ten methods in our study. Using a sample of ~2800 galaxies with visual classification from GZ1, we reach an accuracy of ~0.99 for the morphological classification of ellipticals and spirals. The further investigation of the galaxies that have a different ML and visual classification but with high predicted probabilities in our CNN usually reveals the incorrect classification provided by GZ1. We further find the galaxies having a low probability of being either spirals or ellipticals are visually lenticulars (S0), demonstrating that supervised learning is able to rediscover that this class of galaxy is distinct from both ellipticals and spirals. We confirm that ~2.5 percent galaxies are misclassified by GZ1 in our study. After correcting these galaxies’ labels, we improve our CNN performance to an average accuracy of over 0.99 (accuracy of 0.994 is our best result).
79 ASTRONOMY AND ASTROPHYSICS↗
H i imaging of dwarf star-forming galaxies: masses, morphologies, and gas deficiencies
ABSTRACT The Giant Meter-wave Radio Telescope observations of the H i 21 cm-line emission from 13 nearby dwarf star-forming galaxies are presented. These galaxies are selected from the catalogues of Wolf−Rayet galaxies having very young (≤10 Myr) star formation. The ranges of star formation rates and stellar masses of the sample galaxies are 0.03–1.7 M⊙ yr−1 and 0.04–22.3 × 108 M⊙, respectively. The H i line emission is detected from 12 galaxies with peak column density >1 × 1021 cm−2. The 3σ H i column density sensitivities per channel width of 7 km s−1 for low (60 arcsec × 60 arcsec) resolution images are in the range 0.8–1.9 × 1019 cm−2. The H i channel images, moment images, global profiles, and mass surface density profiles are presented here. The average value of the peak H i mass surface density is estimated to be ∼2.5 M⊙ pc−2, which is significantly less compared to that in massive spiral galaxies. The scaling relations of $(M_{stars} + M_{\rm H\, I} + M_{\rm He})$versus Mdyn, gas fraction versus MB, $M_{\rm H\, I}$versus Mstars, H i-to-stellar mass ratio versus Mstars, and $M_{\rm H\, I}$versus $D_{\rm H\, I}$for the sample galaxies are estimated. These scaling relations can be used to constraint the key parameters in the galaxy evolution models. These galaxies are residing in group environment with galaxy density up to eight galaxy Mpc−3. An H i mass deficiency (with DEFH i > 0.3) is noticed in majority of galaxies for their optical diameters as compared to galaxies in field environments. Clear signatures of tidal interactions in these galaxies could be inferred using the H i images. Isolated H i clouds without known optical counterparts are seen in the vicinity of several galaxies. H i emission envelope is found to be having an offset from the optical envelope in several galaxies. Consistent with the previous studies on galaxy evolution in group environments, tidal interactions seem to play an important role in triggering recent star formation.
Jaiswal, S.↗
Galaxy Zoo DESI: Detailed morphology measurements for 8.7M galaxies in the DESI Legacy Imaging Surveys
ABSTRACT We present detailed morphology measurements for 8.67 million galaxies in the DESI Legacy Imaging Surveys (DECaLS, MzLS, and BASS, plus DES). These are automated measurements made by deep learning models trained on Galaxy Zoo volunteer votes. Our models typically predict the fraction of volunteers selecting each answer to within 5–10 per cent for every answer to every GZ question. The models are trained on newly collected votes for DESI-LS DR8 images as well as historical votes from GZ DECaLS. We also release the newly collected votes. Extending our morphology measurements outside of the previously released DECaLS/SDSS intersection increases our sky coverage by a factor of 4 (5000–19 000 deg2) and allows for full overlap with complementary surveys including ALFALFA and MaNGA.
Astronomy & Astrophysics↗
Gems of the Galaxy Zoos—A Wide-ranging Hubble Space Telescope Gap-filler Program*
We describe the Gems of the Galaxy Zoos (Zoo Gems) project, a gap-filler project using short windows in the Hubble Space Telescope's schedule. As with previous snapshot programs, targets are taken from a pool based on position; we combine objects selected by volunteers in both the Galaxy Zoo and Radio Galaxy Zoo citizen-science projects. Zoo Gems uses exposures with the Advanced Camera for Surveys to address a broad range of topics in galaxy morphology, interstellar-medium content, host galaxies of active galactic nuclei, and galaxy evolution. Science cases include studying galaxy interactions, backlit dust in galaxies, post-starburst systems, rings and peculiar spiral patterns, outliers from the usual color–morphology relation, Green Pea compact starburst systems, double radio sources with spiral host galaxies, and extended emission-line regions around active galactic nuclei. For many of these science categories, final selection of targets from a larger list used public input via a voting process. Highlights to date include the prevalence of tightly wound spiral structure in blue, apparently early-type galaxies, a nearly complete Einstein ring from a group lens, redder components at lower surface brightness surrounding compact Green Pea starbursts, and high-probability examples of spiral galaxies hosting large double radio sources.
79 ASTRONOMY AND ASTROPHYSICS↗
Pushing automated morphological classifications to their limits with the Dark Energy Survey
ABSTRACT We present morphological classifications of ∼27 million galaxies from the Dark Energy Survey (DES) Data Release 1 (DR1) using a supervised deep learning algorithm. The classification scheme separates: (a) early-type galaxies (ETGs) from late-type galaxies (LTGs); and (b) face-on galaxies from edge-on. Our convolutional neural networks (CNNs) are trained on a small subset of DES objects with previously known classifications. These typically have mr ≲ 17.7 mag; we model fainter objects to mr < 21.5 mag by simulating what the brighter objects with well-determined classifications would look like if they were at higher redshifts. The CNNs reach 97 per cent accuracy to mr < 21.5 on their training sets, suggesting that they are able to recover features more accurately than the human eye. We then used the trained CNNs to classify the vast majority of the other DES images. The final catalogue comprises five independent CNN predictions for each classification scheme, helping to determine if the CNN predictions are robust or not. We obtain secure classifications for ∼87 per cent and 73 per cent of the catalogue for the ETG versus LTG and edge-on versus face-on models, respectively. Combining the two classifications (a) and (b) helps to increase the purity of the ETG sample and to identify edge-on lenticular galaxies (as ETGs with high ellipticity). Where a comparison is possible, our classifications correlate very well with Sérsic index (n), ellipticity (ϵ), and spectral type, even for the fainter galaxies. This is the largest multiband catalogue of automated galaxy morphologies to date.
79 ASTRONOMY AND ASTROPHYSICS↗
Decoding the star forming properties of gas-rich galaxy pairs
Here we extend the analysis of Bok et al. (2020) in which the H i content of isolated galaxies from the AMIGA (Analysis of the interstellar Medium in Isolated GAlaxies) sample and selected paired galaxies from ALFALFA (Arecibo Legacy Fast ALFA) were examined as a potential driver of galaxy location on the WISE (Wide-field Infrared Survey Explorer) mid-infrared SFR–M * sequence. By further characterizing the isolated and pair galaxy samples, i.e. in terms of optical galaxy morphology, a more detailed and quantitative description of local galaxy environment by way of the local number density (η) and tidal strength (Q) parameters, star formation efficiency (SFE HI ), and H i integrated profile asymmetries, we present plausible pathways for the broadening of the pair sample H i deficiency distribution towards both high and low deficiencies compared to the narrower isolated galaxy sample distribution (i.e. σ PAIRS = 0.34 versus σ AMIGA = 0.28). We associate the gas-rich tail of the pair deficiency distribution with the highest Q values, large profile asymmetries, and low SFEs. From this, we infer that merger activity is enhancing gas supplies, as well as disrupting the efficiency of star formation, via strong gravitational torques. The gas-poor wing of the deficiency distribution appears to be populated with galaxies in denser environments (with larger η values on average), more akin to groups. Despite our gas-rich selection criterion, there is a small population of early-type galaxies in the pair sample, which primarily fall in the positive deficiency wing of the distribution. These results suggest that a combination of a denser galaxy environment, early-type morphology, and higher stellar mass is contributing to the broadening of the deficiency distribution towards larger deficiencies.
79 ASTRONOMY AND ASTROPHYSICS↗
Spatially resolved properties of supernova host galaxies in SDSS-IV MaNGA
We crossmatch galaxies from Mapping Nearby Galaxies at Apache Point Observatory with the Open Supernova Catalog, obtaining a total of 132 SNe within MaNGA bundle. These 132 SNe can be classified into 67 Type Ia and 65 Type CC. We study the global and local properties of supernova host galaxies statistically. Type Ia SNe are distributed in both star-forming galaxies and quiescent galaxies, while Type CC SNe are all distributed along the star-forming main sequence. As the stellar mass increases, the Type Ia/CC number ratio increases. We find: (1) there is no obvious difference in the interaction possibilities and environments between Type Ia SN hosts and a control sample of galaxies with similar stellar mass and SFR distributions, except that Type Ia SNe tend to appear in galaxies which are more bulge-dominated than their controls. For Type CC SNe, there is no difference between their hosts and the control galaxies in galaxy morphology, interaction possibilities as well as environments; (2) compared to galaxy centers, the SN locations have smaller velocity dispersion, lower metallicity, and younger stellar population. This is a natural result of radius gradients for all these parameters. In conclusion, the SN location and its symmetrical position relative to the galaxy center, as well as regions with similar effective radii have very similar [Mg/Fe], gas-phase metallicity, gas velocity dispersion and stellar population age.
79 ASTRONOMY AND ASTROPHYSICS↗
A study on the statistical significance of mutual information between morphology of a galaxy and its large-scale environment
ABSTRACT A non-zero mutual information between morphology of a galaxy and its large-scale environment is known to exist in Sloan Digital Sky Survey (SDSS) upto a few tens of Mpc. It is important to test the statistical significance of these mutual information if any. We propose three different methods to test the statistical significance of these non-zero mutual information and apply them to SDSS and Millennium run simulation. We randomize the morphological information of SDSS galaxies without affecting their spatial distribution and compare the mutual information in the original and randomized data sets. We also divide the galaxy distribution into smaller subcubes and randomly shuffle them many times keeping the morphological information of galaxies intact. We compare the mutual information in the original SDSS data and its shuffled realizations for different shuffling lengths. Using a t-test, we find that a small but statistically significant (at $99.9{{\ \rm per\ cent}}$ confidence level) mutual information between morphology and environment exists upto the entire length-scale probed. We also conduct another experiment using mock data sets from a semi-analytic galaxy catalogue where we assign morphology to galaxies in a controlled manner based on the density at their locations. The experiment clearly demonstrates that mutual information can effectively capture the physical correlations between morphology and environment. Our analysis suggests that physical association between morphology and environment may extend to much larger length-scales than currently believed, and the information theoretic framework presented here can serve as a sensitive and useful probe of the assembly bias and large-scale environmental dependence of galaxy properties.
Sarkar, Suman↗
SDSS-IV MaNGA: when is morphology imprinted on galaxies?
ABSTRACT It remains an open question as to how long ago the morphology that we see in a present-day galaxy was typically imprinted. Studies of galaxy populations at different redshifts reveal that the balance of morphologies has changed over time, but such snapshots cannot uncover the typical time-scales over which individual galaxies undergo morphological transformation, nor which are the progenitors of today’s galaxies of different types. However, these studies also show a strong link between morphology and star formation rate (SFR) over a large range in redshift, which offers an alternative probe of morphological transformation. We therefore derive the evolution in SFR and stellar mass of a sample of 4342 galaxies in the SDSS-IV MaNGA survey through a stellar population ‘fossil record’ approach, and show that the average evolution of the population shows good agreement with known behaviour from previous studies. Although the correlation between a galaxy’s contemporaneous morphology and SFR is strong over a large range of lookback times, we find that a galaxy’s present-day morphology only correlates with its relatively recent ($\sim \! 2\, \textrm {Gyr}$) star formation history. We therefore find strong evidence that morphological transitions to galaxies’ current appearance occurred on time-scales as short as a few billion years.
Peterken, Thomas↗
The dark side of galaxy stellar populations – I. The stellar-to-halo mass relation and the velocity dispersion–halo mass relation
The growth and properties of galaxies are thought to be closely connected to the ones of their host dark matter haloes. Despite the importance of this so-called galaxy–halo connection, the potential role of dark matter haloes in regulating observed galaxy properties remains yet to be fully understood. In this work, we derive the ages, metallicites, and [Mg/Fe] abundances from optical spectra from the Sloan Digital Sky Survey of nearby central galaxies, and study them in terms of their host haloes. We investigate how the scatter in the stellar-to-halo mass relation and the velocity dispersion–halo mass relation correlates with these stellar population parameters. In addition, we also study the differences when distinguishing between different galaxy morphologies and environments. We find that the ages and chemical enrichment of galaxies are not fully determined by their stellar masses or velocity dispersion, but also depend on the mass of the host haloes. Our findings suggest that the velocity dispersion is the best proxy of the stellar population parameters with halo mass playing a secondary yet noticeable role. Furthermore, we interpret that the origin of the correlation between the scatter of these relations and the ages and metallicities might be related to different halo formation times.
79 ASTRONOMY AND ASTROPHYSICS↗
Self-supervised Representation Learning for Astronomical Images
Sky surveys are the largest data generators in astronomy, making automated tools for extracting meaningful scientific information an absolute necessity. We show that, without the need for labels, self-supervised learning recovers representations of sky survey images that are semantically useful for a variety of scientific tasks. These representations can be directly used as features, or fine-tuned, to outperform supervised methods trained only on labeled data. We apply a contrastive learning framework on multiband galaxy photometry from the Sloan Digital Sky Survey (SDSS), to learn image representations. We then use them for galaxy morphology classification and fine-tune them for photometric redshift estimation, using labels from the Galaxy Zoo 2 data set and SDSS spectroscopy. In both downstream tasks, using the same learned representations, we outperform the supervised state-of-the-art results, and we show that our approach can achieve the accuracy of supervised models while using 2-4 times fewer labels for training. The codes, trained models, and data can be found at https://portal.nersc.gov/project/dasrepo/self-supervised-learning-sdss.
79 ASTRONOMY AND ASTROPHYSICS↗
Aging of galaxies along the morphological sequence, marked by bulge growth and disk quenching
Aims: We revisit the color bimodality of galaxies using the extensive EFIGI morphological classification of nearby galaxies. Methods: The galaxy profiles from the Sloan Digital Sky Survey (SDSS) gri images were decomposed as a bulge and a disk by controlled profile modeling with the Euclid SourceXtractor++ software. The spectral energy distributions from our resulting gri SDSS photometry complemented with Galaxy Evolution Explorer (GALEX) NUV photometry were fitted with the ZPEG software and PEGASE.2 templates in order to estimate the stellar masses and specific star formation rates (sSFR) of whole galaxies as well as their bulge and disk components. Results: The absolute NUV-r color versus stellar mass diagram shows a continuous relationship between the present sSFR of galaxies and their stellar mass, which spans all morphological types of the Hubble sequence monotonously. Irregular galaxies to intermediate-type Sab spirals make up the “Blue Cloud” across 4 orders of magnitude in stellar mass but a narrow range of sSFR. This mass build-up of spiral galaxies requires major mergers, in agreement with their frequently perturbed isophotes. At high mass, the Blue Cloud leads to the “Green Plain”, dominated by S0a and Sa early-type spirals. It was formerly called the “Green Valley”, due to its low density, but we rename it because of its wide stretch and nearly flat density over ~2 mag in NUV-r color (hence sSFR), despite a limited range of stellar mass (1 order of magnitude). The Green Plain links up the “Red Sequence”, containing all lenticular and elliptical galaxies with a 2 order of magnitude mass interval, and systematically higher masses for the ellipticals. We confirm that the Green Plain cannot be studied using u - r optical colors because it is overlayed by the Red Sequence, hence NUV data are necessary. Galaxies across the Green Plain undergo a marked growth by a factor 2 to 3 in their bulge-to-total mass ratio and a systematic profile change from pseudo to classical bulges, as well as a significant reddening due to star formation fading in their disks. The Green Plain is also characterized by a maximum stellar mass of 10 11.7 M ⊙ beyond which only elliptical galaxies exist, hence supporting the scenario of ellipticals partly forming by major mergers of massive disk galaxies. Conclusions: The EFIGI attributes indicate that dynamical processes (spiral arms and isophote distortions) contribute to the scatter of the Main Sequence of star-forming galaxies (Blue Cloud), via the enhancement of star formation (flocculence, HII regions). The significant bulge growth across the Green Plain confirms that it is a transition region, and excludes a predominantly quick transit due to rapid quenching. The high frequency of bars for all spirals as well as the stronger spiral arms and flocculence in the knee of the Green Plain suggest that internal dynamics, likely triggered by flybys or (mainly minor) mergers, may be the key to the bulge growth of massive disk galaxies, which is a marker of the aging of galaxies from star forming to quiescence. The Hubble sequence can then be considered as an inverse sequence of galaxy physical evolution.
79 ASTRONOMY AND ASTROPHYSICS↗
Spectral evidence of solar neighborhood analogs in CALIFA galaxies
We introduce a novel nonparametric method to find solar neighborhood analogs (SNAs) in extragalactic integral field spectroscopic surveys. The main ansatz is that the physical properties of the solar neighborhood (SN) should be encoded in its optical stellar spectrum. We assume that our best estimate of such a spectrum is the one extracted from the analysis performed by the Code for Stellar properties Heuristic Assignment (CoSHA) from the MaStar stellar library. It follows that finding SNAs in other galaxies consist in matching, in a χ 2 sense, the SN reference spectrum across the optical extent of the observed galaxies. We applied this procedure to a selection of CALIFA galaxies, by requiring a close to face-on projection, relative isolation, and non-active galactic nucleus. We explore how the local and global properties of the SNAs (stellar age, metallicity, dust extinction, mass-to-light ratio, stellar surface mass density, star-formation density, and galactocentric distance) and their corresponding host galaxies (morphological type, total stellar mass, star-formation rate, and effective radius) compared with those of the SN and the Milky Way (MW). We find that SNAs are located preferentially in S(B)a–S(B)c galaxies, in a ring-like structure, which radii seem to scale with the galaxy size. Despite the known sources of systematics and errors, most properties present a considerable agreement with the literature on the SN. We conclude that the solar neighborhood is relatively common in our sample of SNAs. Our results warrant a systematic exploration of correlations among the physical properties of the SNAs and their host galaxies. We reckon that our method should inform current models of the galactic habitable zone in our MW and other galaxies.
79 ASTRONOMY AND ASTROPHYSICS↗
Repainting the colour–mass diagrams by unearthing the green mountain: dust-rich S0 galaxies in the colour–(galaxy stellar mass) diagram, and the colour–(black hole mass) relations for dust-poor versus dust-rich galaxies
ABSTRACT Lenticular galaxies are notoriously misclassified as elliptical galaxies and, as such, a (disc inclination)-dependent correction for dust is often not applied to the magnitudes of dusty lenticular galaxies. This results in overly red galaxy colours, impacting their distribution in the colour–magnitude diagram. It is revealed how this has led to an underpopulation of the ‘green valley’ by hiding a ‘green mountain’ of massive dust-rich lenticular galaxies – known to be built from gas-rich major mergers – within the ‘red sequence’ of colour–(stellar mass) diagrams. Correcting for dust, a ‘green mountain’ appears at M*,gal ∼ 1011 M⊙, along with signs of an extension to lower masses producing a ‘green range’ or ‘green ridge’ on the green side of the ‘red sequence’ and ‘blue cloud.’ The ‘red sequence’ is shown to be comprised of two components: a red plateau defined by elliptical galaxies with a near-constant colour and by lower-mass dust-poor lenticular galaxies, which are mostly a primordial population but may include faded/transformed spiral galaxies. The presence of the quasi-triangular-shaped galaxy evolution sequence, previously called the ‘Triangal’, is revealed in the galaxy colour–(stellar mass) diagram. It tracks the speciation of galaxies and their associated migration through the diagram. The connection of the ‘Triangal’ to previous galaxy morphology sequences (Fork, Trident, and Comb) is also shown herein. Finally, the colour–(black hole mass) diagram is revisited, revealing how the dust correction generates a blue–green sequence for the spiral and dust-rich lenticular galaxies that is offset from a green–red sequence defined by the dust-poor lenticular and elliptical galaxies.
Graham, Alister W. (ORCID:0000000264969414)↗