I’ll resume my M31 posts soon (I hope), but I wanted to do a short post on the recent Zoogems HST observation of IC 3025 which is a dwarf elliptical in the Virgo cluster that was selected as part of the “post-starburst” galaxy sample. Thanks mostly to its membership in Virgo this galaxy is fairly well studied and even has multiple HST observations. Just for fun I tried to make a false color RGB image from three observations, with two in the IR through F160W and F110W filters, and the blue channel from the Zoogems observation in F475W.
IC 3025
False color composite from HST WFC3 IR images in F160W and F110W filters (proposal ID 11712, PI Blakeslee) and ACS/WFC F475W filter (proposal ID 15445, PI Keel).
This used a program named SWarp (author Bertin) to rescale and align the images and STIFF (also Bertin) to combine them, with some Photoshop work in a mostly futile attempt to get a more pleasing color balance and clean up some of the hot pixels. I don’t know exactly how STIFF maps counts to gray scale levels, but despite the odd color cast this picture may actually give a reasonably accurate rendering of the relative fluxes in each filter. The galaxy as a whole has a g-J color of about 1.3 mag (based on my measurements with APT and NED) and J-H ≈ 0.2 mag. per Jensen et al. (2015), so an orange or even green color in the body of the galaxy is not so unreasonable.
The blue(er) central region is notable and apparently real also. This is one of a distinct class of dwarf early type galaxies with blue centers, given the designation dE(bc) by Lisker et al. (2006). The blue centers are almost certainly due to recent star formation, as I’ll verify below.
There are 3 bright, unresolved clusters near the center with a number of others scattered around the body of the galaxy. By my measurements with the manual Aperture Photometry Tool the brightest of these has a g band (F475W) magnitude of 20.71 and J (110W) of 20.084, or g-J ≈ 0.62. The other two near the galaxy center are slightly fainter and considerably redder: g = 21.5 and 22.6 for the western and eastern flanking clusters, with g-J ≈ 1.2 for both. Jensen et al. (cited above) measure the distance modulus to be m-M = 31.42, which makes the F475W absolute magnitude of the central cluster equal to -10.71. Like the Zoogems target I discussed several months ago this would be quite luminous for a galactic globular cluster but is typical for a dwarf galaxy’s nuclear star cluster (Neumayer, Seth, and Boker 2020). This distance modulus, which corresponds to a luminosity distance of 19.2 Mpc, is considerably larger than the canonical distance to the Virgo cluster of m-M = 31.09 (per Jensen again). This is one of several lines of evidence that the galaxy is currently falling into the cluster.
Like the other galaxies in the Zoogems “post-starburst” sample the SDSS spectrum was incorrectly classified by the SDSS spectro pipeline as coming from a star, but this one has a correct redshift and has been used in science studies (for example in Lisker et al. cited above). From the reported position the fiber center was just west of the brightest central cluster and includes both that one and the cluster just to the west. The spectrum is very much typical of a post-starburst, with deep Balmer absorption and a shallow 4000Å break. I measure HδA = 7.24 ± 0.60Å and Dn4000 = 1.26 ± 0.0141this spectrum was analyzed in the JHU/MPA pipeline with nearly identical values and uncertainties, very similar values to the other two that I posted about last year. Finally, although it’s far from evident on visual inspection, there are firm (4-5 σ) detections of Hα and S[II] 6717, 6730 in emission. No other emission lines were detected.
IC 3025 – SDSS spectrum
I used my usual star formation history modeling code with the metal poor subset of the EMILES SSP library as described here, which produced the estimated star formation and mass growth histories:
IC 3025 – Star formation history and mass growth history modeled from SDSS spectrum
with a very good fit to the data except for a small region around 7500Å (which is often the case with the EMILES library):
IC 3025 – posterior predictive fit to spectrum from SFH model
My results can be compared fairly directly to an analysis by Lisker et al. (cited above), who performed some simple stellar population modeling on SDSS spectra with what appears to be their own unreleased code. They limited their populations to 3 discrete ages with the oldest fixed at 5 Gyr and the mass fractions and ages for the other 2 chosen from a finite set of possible values.
Perhaps surprisingly my results agree rather well with theirs. For VCC 21 (the Virgo Cluster Catalog designation for IC 3025) their best fit had about 9% of the total mass in young and intermediate age populations, with the young population chosen at 9 Myr age and 0.3% of mass and the intermediate population age of 509 Myr.
My models also show three broad periods of star formation with some lulls in between that can conveniently be divided into young, intermediate, and old populations. The youngest SSP models in my metal poor subset are 30 Myr, so of course there can’t be any truly young populations in the model. The peak in recent star formation was at ~70 Myr with a steep decline at the youngest lookback times. Around 1% of the present day stellar mass in the fiber footprint is in stars younger than 100 Myr, with just under 10% under 1 Gyr.
Based on the colors we can infer that the acceleration of star formation that began ~1 Gyr ago was limited to the central region and the presumed nuclear star cluster. The remainder of the galaxy and its cluster system must already have been quiescent by then.
Edit
I mentioned above my SFH models indicated there were firm detections of Hα and the [S II] doublet in emission. Although [N II] wasn’t detected at better than the 1σ level it’s still possible to make a strong line metallicity estimate from the posteriors. I also plot the marginal posterior for Hα luminosity below:
IC 3025
(L) Hα luminosity from SDSS spectrum
(R) log(O/H) estimated from [N II]/Hα and [S II]/Hα
Using Calzetti’s calibration of the Hα – SFR relation this implies a current day star formation rate ~10-4.5 M☉/yr. This should be considered an upper limit since we don’t know the ionizing source. Using Dopita’s calibration of the [N II]/Hα plus [S II]/Hα strong line metallicity estimator the upper limit to 12+log(O/H) is around 8, which is subsolar by almost an order of magnitude.
I’m going to try to keep this one short. IC 976 is another post-starburst galaxy that was selected and recently observed by HST for the Zoogems project (proposal ID 15445, PI Keel). I took a shot at creating a color image by combining the ACS observation taken with the F475W filter (approximately equivalent to SDSS g band) with r and z band images from the Legacy Survey. Well that wasn’t too rewarding since this galaxy appears quite featureless.
IC 976 – RGB image created for Legacy Survey r and z band images + HST ACS F475W image from proposal ID 15445, PI W. Keel
Like the galaxy in the previous post the SDSS spectro pipeline misclassified this galaxy’s spectrum as a star with a recession velocity of ≈ 1200 km/sec. Unlike the galaxy in the previous post IC 976 is well known to have a post-starburst nuclear spectrum, and its correct heliocentric redshift of 0.00509 is listed in NED and confirmed with my own redshift estimation code. If that’s its Hubble flow redshift (doubtful) its distance would be about 21.8 Mpc (distance modulus m-M=31.7) and the 3″ SDSS fiber would cover 315 pc.
SDSS spectrum of IC 976 nucleus with best fit template overlay
Once again I ran my SFH modeling code on the SDSS spectrum, using only my metal rich PYPOPSTAR+EMILES ssp library, with results below:
Modeled star formation and mass growth histories of central region of IC 976 from SDSS spectrum 340044889930622976.
Despite the superficially similar spectra1this has a nearly identical HδA index of 8.1 ± 0.3 Å. this model favors an older (peak at 800 Myr lookback time), stronger, and shorter burst than the previous example. The model’s burst strength of ≈ 40 % of the present day stellar mass seems high, but the estimated total stellar mass within the fiber footprint is only ≈108.5 M☉, which is likely a small fraction of the galaxy’s total stellar mass. For a rough estimate of the total mass the SDSS g band Petrosian magnitude is listed as 13.6, making the absolute magnitude -18.1. With a solar g band absolute magnitude of 5.11 the galaxy’s luminosity is ≈ 109.3 L☉, and assuming a stellar mass to luminosity ratio around 1 the mass would therefore be ≈ 2×109 M☉. If the merger added a little over 108 M☉ to the system as implied by this model the mass ratio of the progenitors would be on the order of 20:1.
IC 976 was one of 7 post-starburst galaxies in an IFU based spectroscopic study by Pracy et al. (2012). This galaxy2designated “E+A 6” in the paper. had a very strong negative radial gradient in the Balmer absorption index, as did 5 of the 6 others in the study. They concluded that centrally concentrated starbursts fueled by minor mergers was the most likely cause of their present evolutionary state. The lack of any apparent tidal features in the available imaging of this galaxy likely reflects the age of the merger and mass ratio of the progenitors.
While browsing through the ADS listing of papers that cite Schawinski’s paper that I’ve been discussing for a while I came across this one by Haines et al. with the full title “Testing the modern merger hypothesis via the assembly of massive blue elliptical galaxies in the local Universe”. Besides being on the same theme of searching for post-starburst or “transitional” galaxies in the local universe that I’ve been pursuing for some time the paper was interesting because it made use of IFU based spectroscopic data that predates MaNGA. As it happens 4 of the 12 galaxies have observations in the final MaNGA release, providing an excellent opportunity to compare results from completely independent data sets.
The “modern merger hypothesis” that the authors tested relates to a topic I’ve discussed before, which is that N-body simulations show that strong, centrally concentrated starbursts are a possible outcome of major gas rich galaxy mergers around the time of coalescence. If some feedback process (an AGN or supernovae) rapidly quenches star formation there will ensue a period of time when the galaxy will be recognizable as post-starburst.
In a series of long and rather difficult (and influential judging by the number of citations) Hopkins and collaborators (2006, 2008a, 2008b) have made a case that major gas rich mergers with accompanying starbursts are in fact the major pathway to the formation of modern elliptical galaxies. They claim that their merger hypothesis accounts for a variety of phenomena, including the growth and evolution of supermassive black holes and quasars.
The specific aspect of the merger hypothesis this study tried to address was the prevalence of strong centrally concentrated starbursts in a sample of ellipticals in the process of forming as evidenced by visible disturbances consistent with recent mergers. The main tool they used was a suite of simple star formation history models with exponentially decaying star formation rate with single (also exponentially decaying) bursts on top of varying ages and decay time scales. They used these to predict just two quantities: Balmer absorption line strength measured by the average of the Lick HδA and HγA indexes, and the 4000Å break strength index Dn4000. For reference here is a screen grab of their model trajectories:
Predected trajectories in the Hδ – Dn4000 plane per Haines et al. (2015). Clipped from the electronic journal paper.
This is a pretty standard calculation variations of which have been performed for decades, and this graph looks much like others I have seen in the literature. A fairly basic problem with it though is that position in the Balmer – D4000 plane doesn’t uniquely constrain even the recent stellar evolution. In astronomers’ parlance there is a “degeneracy”1the term refers to a situation in which multiple combinations of some parameters of interest produce effectively equivalent values of some observable(s), or of course the converse. The best known example is the “age-metallicity degeneracy,” which refers to the fact that an old metal poor population looks like a younger metal rich one in several respects such as broad band colors. between burst strength (if any) and burst age. This is a well known problem with the Balmer line strength index that was already recognized by Worthey and Ottaviani (1997), who developed these indexes. Adding a second index in the form of the 4000Å break strength doesn’t break the degeneracy: there are regions of the plane where bursting and non-bursting populations overlap, as can be seen clearly in the graphic above. This is actually a problem for any attempt to identify post-starburst galaxies. After correcting for emission most ordinary starforming galaxies have strong Balmer absorption lines, so using that index alone will certainly produce many false positives. On the other hand selection criteria like those used by Goto and many others before and after — selecting for both strong Balmer absorption and weak emission — will capture only a small interval in post-starburst galaxies’ life cycles.
Hδ line strength vs. 4000Å break index for a large (~380K) sample of SDSS galaxy spectra. Measurements from the MPA-JHU analysis pipeline downloaded from SDSS Skyserver
Let’s get to results. Some basic details of the sample are in the table below. Morphological classifications are from McIntosh et al. (2014) as given in this paper. The abbreviations are SPM: spherical post merger; pE: peculiar Elliptical. The two marked pE/SPM didn’t have a strong consensus among several professional classifiers. I list them in order of my own visual impression of degree of disturbance. I also list redshifts taken from the MaNGA catalog and Petrosian colors.
NED name
NYU ID
mangaid
plateifu
Morph
z
u-r
g-i
NGC 3921
541044
1-617445
10510-6103
SPM
0.019
1.97
0.86
MRK 385
719486
1-604970
8940-6102
pE/SPM
0.028
1.43
0.63
MRK 366
100917
1-603309
7993-1902
pE/SPM
0.027
1.59
0.79
NGC 1149
22318
1-37155
8154-6103
pE
0.029
2.29
1.11
Columns: (1) Common catalog designation (NED name). (2) NYU VAC ID. (3) MaNGA mangaid. (4) MaNGA plateifu. (5) Morphology (see text). (6) redshift from MaNGA DRP catalog. (7-8) Petrosian u-r and g-i colors from NYU VAC via the MaNGA DRP catalog.
The main prediction of the merger with accompanying centrally concentrated starburst hypothesis the paper tests is that the Balmer absorption index should be large and have a negative gradient with radius while the 4000Å break strength should be low with a positive gradient. The authors concluded that only one member of their sample — nyu541044 — clearly falls in the post-starburst region (marked as region 4 in the graph above) of the <Hδ, Hγ> – Dn4000 plane. The two pE/PM galaxies, both of which are in my sample, lie in the starforming region 1. They inferred from this that these galaxies are undergoing at most a weak burst. I’m going to mildly disagree with that conclusion.
Measured values for the specified indexes from Haines et al. (2015). Clipped from the electronic journal paper.
I have calculated the pseudo Lick index HδA and Dn4000 as part of my analysis “pipeline” since I started this hobby. I actually make these measurements in the initial maximum likelihood fitting step since they don’t depend on modeling except for small (usually) emission corrections. I don’t calculate an Hγ index, but its theoretical behavior is similar to Hδ. I’m trying here just to verify the approximate magnitude and radial trends of the chosen indexes. The two IFUs used in the Haines study had larger spatial coverage than these MaNGA observations (but much smaller wavelength coverage, which will become important). Instead of their strategy of binning in annuli I used my usual Voronoi binning strategy with a minimum target S/N. There were some oddities in the NYU estimates of effective radii so I chose to use distances from the IFU center in kpc for these plots. The distances assigned to the multiply binned spectra are the same as Cappelari’s published code produces; for single fiber spectra it’s just the position of the fiber center.
My measurements agree reasonably well with those of Haines et al. All three of the most disturbed galaxies have central Hδ indexes > 5Å with NGC 3921 (plateifu 10510-6103, nyu541044) having a larger central value and steeper gradient in the inner few kpc than the two pE/SPM galaxies. The fourth galaxy shows no obvious trend in either index with radius2The next several plots show trend lines for each galaxy computed by fitting simple loess curves to the data using the default parameters in ggplot2. These, and especially the confidence bands included in the plots, should not be taken seriously!. The central values where the S/N is highest are in good agreement.
Lets turn to the results of star formation history models, which I ran on all 4 data sets. First, here are 100Myr averaged star formation rate density and specific star formation rate versus distance:
Star formation rate density vs. distance from IFU center (kpc) for 4 disturbed early type galaxies.Specific star formation rate density vs. distance from IFU center (kpc) for 4 disturbed early type galaxies.
Three of these galaxies are clearly experiencing centrally concentrated episodes of star formation, and two are at or near starburst levels in specific star formation rate near their centers. As seen below two of these straddle my estimate of the “spatially resolved star forming main sequence” while the one presumed post-starburst galaxy reaches it in the central region.
Star formation rate density versus stellar mass density for 4 disturbed early type galaxies
As I’ve shown several times before there’s a reasonably tight linear relationship between modeled star formation rate and Hα luminosity density. The plot shows Hα luminosity density corrected for modeled stellar redenning, which certainly underestimates attenuation in emission regions. The modeled star formation rates are consistently above the Kennicut relation shown as the straight line as I’ve seen in every sample I’ve looked at.
Star formation rate density vs. Hα luminosity density for 4 disturbed early type galaxies
Finally, lets take a look at detailed star formation histories. Instead of my usual practice of plotting them all in a grid here I just display 2 binned star formation histories. One comprises the innermost 7 bins, which since the fibers are arranged in a hexagonal grid should form a regular hexagon around the IFU center. These range in “radius” from about 0.75 to 1.1 kpc in these four galaxies. The second is for an “annulus” in approximately the outer kpc of each IFU. The extent of the IFU footprints ranges from 3.1 to 5.9 kpc. I calculate these by summing the contributions in each SFH model contributing to the bins, not by running new models for binned spectra. Since the dithered fiber positions overlaps this overestimates the total mass in each bin, but I care about the shape and timing of events rather than the absolute values of star formation rate estimates.
The next 4 plots display the results. Lookback time is logarithmically scaled with the same range and ticks for each SFH. Vertical scales are linear and differ for each graph. The graphs are in the same order as the basic information table above. As I’ve written before these models “want” to have smoothly varying mass per time bin which has the unfortunate effect of producing jumps in the apparent SFR when the bin widths change. In the BaSTI isochrone based SSP models these occur at 100 Myr, 1 Gyr, and 4 Gyr and can sometimes be quite prominent.
With caveats out of the way the one clear post-starburst in the sample had (per the model) a powerful and short starburst at ≈300 Myr lookback time, with a small amount continuing to the present (this can’t be seen at the scale of the graph, but ongoing star formation is ~1 M☉/yr). The total mass contribution from the burst and subsequent star formation is around 15%.
The two apparent ongoing starbursts have later bursts of star formation that are slightly weaker in terms of total mass contribution and peak star formation rate, but still quite significant. All three of the starburst/post-starburst galaxies appear to have had two major waves of late time (last ~2 Gyr or less) star formation. As I’ve written before in merger simulations the progenitors usually complete a few orbits before coalescence, with some enhanced star formation around each perigalactic passage. I hesitate to take these models that literally.
Turning finally to the last and least disturbed galaxy, NGC 1149, despite the bursty appearance of the SFH there’s no evidence for a major starburst in the cosmologically recent past. Whether an older starburst can be detected in this kind of modeling approach needs investigating.
One last set of graphs that may be useful. These show cumulative star formation histories — basically the cumulative sum of mass contributions starting from the oldest time bin. This is similar to a mass growth history which is a popular visualization. In my calculation of the latter the contributions are to the present day stellar mass, so an allowance for mass loss and remnant mass is made3these come from the source of the SSP models and are themselves models. Probably they are somewhat better than guesses. These things are basically black boxes to users.. The graphs are for the central regions only. Note the major virtue of these is that the contributions of major episodes of star formation can be estimated at a glance.
Cumulative star formation histories for central regions of 4 disturbed early type galaxies
To wrap up this part of the post 3 of these galaxies are compatible with the “modern merger hypothesis,” that is they have experienced centrally concentrated but spatially wide spread starbursts. The reason two of them don’t have post-starburst characteristics in the Hδ – D4000 plane is their starbursts are still underway. The current burst of star formation contributes about 5-10% of the mass in the central regions of these two. How much more is available is unknown (at least to me until I get around to finding out if there are HI mass estimates available).
Future plans: I’ve completed model runs on the 24 “post-starburst” galaxies in the MaNGA ancillary program dedicated to them. I may have something to say about them. I also may have something to say about one of the Zoogems targets that I had a small part in selecting.
As I mentioned two posts ago there are 24 of these galaxies in the final MaNGA data release, a remarkable 11% of the full sample. I ran my SFH model code on all of these along with the prerequisite redshift offset routine1I actually completed these some time ago. I just haven’t had time to do much analysis or write about them. SDSS thumbnails of the sample are shown below. As expected none of these have significant spiral structure visible at SDSS resolution, but at least a few are noticeably disturbed.
SDSS thumbnail images of Schawinski et al.’s blue early type galaxies in MaNGA final data release (SDSS DR17)
I’m just going to discuss a few topics in this post. I’ll save a more detailed discussion for when I’ve completed analysis of the ancillary post-starburst sample, which is underway now. First, here are velocity fields calculated for the stacked RSS data, with a signal to noise cutoff of 3, the same as I used for my analysis of rotation curves of disk galaxies. Note in the graphic below the ordering is different from the image thumbnails.
Line of sight velocity fields of Schawinski et al.’s blue early type galaxies in the final MaNGA data release
By my count (based entirely on visual inspection) all but 2 of these exhibit large scale rotation, with perhaps 15 or 16 classifiable as regular rotators with the remainder containing multiple velocity components including a couple with (perhaps) kinematically distinct cores. The preponderance of rotating systems surprised me at first, but according to a review by Cappellari (2016) large scale rotation is predominant at least at lower stellar masses (Schawinski et al. characterized their sample as being “low to intermediate mass” among early type galaxies). The velocity fields indicate that many of these contain stellar disks, perhaps embedded in large bulges. That’s still consistent with classification as “early type galaxies.” Apparently the original Galaxy Zoo classification page used the term “elliptical” as the early type galaxy choice, but in the data release paper by Lintott et al. (2011) there’s a statement that the “elliptical” class should comprise ellipticals, S0’s, and perhaps Sa’s from Hubble’s classification scheme.
Depending on how my effort to do non-parametric line of sight velocity modeling goes I may return to examine the kinematics of this sample in more detail, in particular to look for evidence of gas and stellar kinematic decoupling.
Turning to the recent star formation history this sample runs the gamut from large scale starbursts to passively evolving as seen in the plot of (100 Myr averaged) star formation rate versus stellar mass density for all analyzed binned spectra (of which there were 1525 in the full sample). For reference the straight line is my estimate of the center of the local “spatially resolved star formation main sequence.” This is just a weighted least squares fit to the sample of 20 non-barred spirals with star forming BPT diagnostics that I discussed some time ago. My SFMS relation has the same slope as estimated by Bluck but is offset higher by about 0.7 dex, which probably just reflects the very different methods used to estimate star formation rates. The contour lines are the densest part of the relationship from the passively evolving Coma cluster sample that I also discussed in that post. The majority of the blue etg sample falls in the green valley, consistent with Schawinski et al.’s observation that only about 1/2 of the sample showed evidence for ongoing star formation.
“Spatially resolved” star formation rate density versus stellar mass density for 24 blue early type galaxies in final MaNGA data release. Contour lines are corresponding values for 33 passively evolving Coma cluster galaxies.
Most of the points offset the most on the high side of the SFMS come from just two galaxies: MRK 888, which I’ve discussed in the last few posts, and SDSS J014143.18+134032.8 (this is apparently not in any “classical” catalog). The legacy survey cutout below clearly shows an extended tidal tail that’s a certain sign of a relatively recent merger.
SDSS J014143.18+134032.8, a disturbed, star-bursting blue early type galaxy
I just want to take a quick look at this one: below are maps of the star formation rate density and SSFR as well as scatterplots of the same against distance from the IFU center. As with MRK 888 ongoing star formation is widespread with a peak near the center, a classic case of a merger fueled starburst. In this galaxy star formation peaks in a ring somewhat outside the nucleus. The ring can be seen clearly in the SDSS cutout and must consist of HII regions.
SDSS J014143.18+134032.8 (mangaid 1-41541; plateifu 8095-1902)
Star formation rate density and specific star formation rate – maps and scatterplots against radius in kpc.
Schawinski et al. briefly discuss the possibility that their blue ETG’s could be progenitors of E+A (aka K+A) galaxies. This galaxy and MRK 888 are plausible candidates — if star formation shut off rapidly they would certainly exhibit strong Balmer absorption for a time after emission lines disappeared since they already do. Other members of this sample are already fading towards the red sequence, and if they ever qualified as “post-starburst” it must have been in the past.
I plan to look at star formation histories in more detail after I’ve completed model runs on the MaNGA post-starburst sample.
The first iteration of Galaxy Zoo led to several collections of distinct objects, including a sample of 215 “blue early type galaxies” published in Schawinski et al. (2009)1which inexplicably and consistently says there were 204 objects while the catalog published in Vizier contains 215.I found this an interesting group of galaxies, partly because of a possible link to post-starburst (K+A) galaxies that was discussed in the original paper. The authors discuss at some length the likelihood that these are results of mergers in the cosmologically recent past, with at least one of the progenitors being gas rich. Many (at least 25% and possibly more than half) were found to be currently starforming and the rest likely to have only recently ceased forming stars as inferred from their blue colors.
The ongoing Zoogems program has 12 of Schawinski’s blue ETGs on its target list, of which 6 have been observed so far as of mid-January 2022. Somewhat surprisingly there are 24 in the final MaNGA release, over 11% of the sample!
Taking a look at the 6 with HST observations I would say none of these are typical ellipticals. Five show some degree of spiral structure although in 4 it’s embedded in a more diffuse body. One appears to me to be an S0 with both inner and outer rings — this is in agreement with the one published morphological classification I’ve found. All of the others appear more disky than ellipsoidal to me, although this is just my possibly flawed qualitative judgment. At least two are visibly disturbed. One (CGCG 315-014) is connected to a nearby galaxy with a long tidal tail as seen in the Legacy Survey thumbnail below. Markarian 888, which will be the subject of the rest of this post, has shells that extend well past the main body of the galaxy and prominent, centrally concentrated dust lanes.
CGCG 315-014 Legacy Survey Thumbnail
So far it’s the only Zoogems blue etg target with a MaNGA observation (two others on the target list are in MaNGA but of course there’s no guarantee they will ever be observed). As is often the case the IFU could have been larger — this was observed with a 37 fiber bundle giving 111 dithered spectra in the RSS file.
MRK 888 SDSS thumbnail with MaNGA IFU footprint
As always the first step in analyzing these data is to estimate redshift offsets for each spectrum, and from there we get a velocity field, which in this case shows a rapid rotator with a fairly symmetrical radial velocity pattern.
Mrk 888 (MaNGA plateifu 9894-3703) velocity field
Visual inspection suggests the line of sight velocity distribution is consistent with a rotating thin disk, so I fed the data to my Gaussian process based rotation modeling code, with results summarized below. In fact the model does an excellent job of accounting for the data, with residuals (not shown) from the model fit (top right) in a range of ±15 km/sec. One unusual feature of the velocity field is the rotation velocity turns over at somewhat less than one effective radius. Whether the rotation curve declines smoothly outside the IFU footprint or is kinematically disconnected from the outer parts of the galaxy is of course unknowable at this time.
Gaussian process rotation model results
I also ran my usual star formation history modeling code on the data binned to 97 spectra. First, here are some summary results. The stellar mass density declines roughly exponentially, which is consistent with a disky morphology:
Model estimate of stellar mass density vs. radius
Next are maps of the estimated Hα luminosity density and, on the right, the BPT classification from the [O III]/Hβ vs. [N II]/Hα diagnostic. The contours are elliptical with major axes closely aligned to the rotation axis (the posterior mean for the angle is the dashed line in the velocity field plot above). Again, the emission appears to arise in a disk.
The proper interpretation of the “composite” BPT classification is something I think I’ve written about in the past. It was originally suggested to indicate a mix of AGN and stellar ionization, but here it arises in a thin ring of weak but detectable emission just outside the star forming region. If it’s truly composite it’s likely to arise from a mix of weak star formation and ionization by hot evolved stars. In any case there’s no evidence for an AGN in the optical data.
(L) Hα luminosity density (R) BPT classification from [O III]/Hβ vs {N II]/Hα diagnostic
Next are maps of the modeled (100 Myr average) star formation rate density and specific star formation rate, and in the second row scatter plots of the same estimates against radius in kpc. The trends with radius are somewhat unusual, especially for SSFR which in a normal disk galaxy typically increases with radius even if the highest total star formation rates are centrally concentrated. Highly centrally concentrated star formation in the aftermath of mergers is predicted by some simulations.
(TL) star formation rate density; (TR) specific star formation rate; (bottom row) scatter plots vs. radius
A couple more graphs will round out my discussion of summary model estimates. As I’ve shown several times before there’s a pretty tight linear relationship between modeled SFR density and estimated Hα luminosity density. In this plot Hα is corrected for modeled stellar attenuation, which is expected always to underestimate the attenuation in emission line emitting regions. That, and the fact that Hα emission and the model star formation rate estimates probe order of magnitude different time scales probably account for the systematic offset from the standard calibration given by the straight line.
Model star formation rate density vs. Hα luminosity density corrected for stellar attenuation. Straight line is calibration from Calzetti (2012).
And, once again I show a map of the modeled optical depth of stellar attenuation. The region of highest optical depth nicely tracks the visible dust (the HST image at the top is rotated about 90º from the SDSS image). Outside the dusty region there appears to be a shallow gradient, which might indicate that the nearer side is to the northeast.
Map of modeled optical depth of stellar attenuation
Finally here are plots of the model star formation history for all spectra ordered by distance from the IFU center. In the inner 1.5 kpc or so there’s some recent burstiness with possibly a very recent acceleration of star formation. For reasons I’ve discussed recently I don’t take either the timing or magnitude of bursts of star formation too seriously, but the behavior of the models is consistent with a recent revival of star formation due presumably to a merger, for which there are multiple lines of evidence.
model star fomation histories for all spectra
With 24 of these galaxies and another 31 from the compilation of Melnick and dePropris and the post-starburst ancillary program in the final release of MaNGA these samples satisfy my criteria of being manageably sized for my computing resources while large enough to say something about the groups. So, when time permits I plan to take a look. I already have the data in hand.
The final release of SDSS MaNGA went public back in early December as promised, and I’ve spent the last month or so of my hobby time looking for manageable sized samples of interesting galaxies. One sample I looked at out of curiosity was the Zoogems target list, which is an HST gap filler imaging program with about 300 galaxies selected (mostly) by Galaxy Zoo volunteers. It turns out there are 11 targets with MaNGA data, of which 5 have been observed by HST so far.
SDSS thumbnail images of Zoogems targets with MaNGA data
As can be seen from the thumbnails above this is a pretty diverse lot, with several in progress mergers and merger remnants, some normal looking spirals at least two of which were from Masters’ red spirals sample, and 3 of Schawinski’s blue early type galaxies. Only one of those 3 has HST imaging so far (number 8 in the thumbnails above), although there are a surprising 24 blue ellipticals in the final MaNGA release out of 215 in Schawinski’s original sample.
Of the 5 Zoogems galaxies that have been observed so far the one that caught my eye as deserving an early look was number 3 in the top row, NGC 810, an apparent elliptical with an unusual dust lane that’s almost perfectly aligned with the minor axis. There are also hints of shells indicating a likely merger sometime in the past.
NGC 810
HST ACS, proposal id 15445, PI Keel
The MaNGA data, which is new in DR17, only covers the central part of the galaxy with the companion just photobombing the edge. A larger IFU would have been nice for this observation, but the data quality is better than average in terms of nominal signal to noise. I was able to use all 183 fiber/position combinations in the RSS file without binning.
NGC 810 – plateifu 9514-6101 – MaNGA IFU footprint
The first step in the analysis process after loading the data is to estimate redshift offsets from the system redshift for each spectrum, and from that it’s straightforward to calculate a velocity field, which in this galaxy looks like1this is actually from the data cube:
NGC 810 (plateifu 9514-6101) – losvd estimated from cube
It turns out the redshift assigned to this system was that of the companion galaxy, which was the only SDSS spectroscopic target in the immediate vicinity and is evidently blueshifted by ~350 km/sec from the target. What’s more interesting though2interesting enough that I made a couple posts on the Galaxy Zoo talk forum, which I rarely do anymore. is the apparent rapidly rotating disk that’s aligned with and somewhat thicker than the dust lane. There may also be overall prolate rotation outside the disk although the presence of the companion makes it hard to tell based solely on visual inspection. In hopes of separating out multiple velocity components I returned to the non-parametric line of sight velocity distribution models that I wrote some posts about last year. Unlike the ones I practiced on previously this galaxy has non-negligible amounts of emission, at least in the central region, so I just temporarily masked the regions around the emission lines that I fit. That results in a pure stellar velocity distribution. The results were a bit surprising:
NGC 810 (plateifu 9514-6101)
(L) velocity field estimated from RSS file
(M) stellar velocity offsets
(R) net stellar velocity
In the left pane above is the velocity field from the RSS data, with the system redshift adjusted to the IFU center. For the LOSVD models I set the adopted redshift of each spectrum to the system redshift plus the offset calculated previously. Now I had hoped to be able to cleanly separate the contribution of the companion from that of the main galaxy, which so far I haven’t been able to do. But what I did find that was unexpected is that the average stellar velocities in the disk partially offset the original measurements (middle pane), so the net stellar velocity field shows a much more slowly rotating stellar disk.
As I’ve written before I use a set of 15 eigenspectra from a principal components analysis of some tens of thousands of SDSS spectra that I performed some years ago for redshift offset estimation. Those galaxies were of all types and include systems both with and without significant emission. The redshift estimation routine just does straightforward template matching and returns a single value for the best fitting offset. Since the templates encode information about both emission and absorption lines that estimate could be most applicable to the ionized gas, stars, or some combination. In this case it’s possible emission lines were driving the original fits, implying the gas and stars in the disk are kinematically decoupled. I have not verified that though.
Another issue I noticed is that the stellar velocity field from the official MaNGA Data Analysis Pipeline looks rather different from mine, with barely a hint of a kinematically distinct disk. This wasn’t really evident in the Marvin webpage, which makes some really unfortunate choices for color palettes. So here is the same data rendered with a more nearly perceptually uniform rainbow palette3I know data visualization experts frown on rainbows, but I think they’re OK for things like velocities or redshifts:
NGC 810 (plateifu 9514-6101)
Stellar velocity field per MaNGA DAP
I decided to re-run my LOSVD modeling code on the RSS data, this time setting the redshift offset to 0 for each fiber, so this is now measuring velocities relative to the overall system velocity. I also used a larger convolution kernel (25 vs. 21 in the first set of runs). The map of the average velocity offsets is:
NGC 810 (plateifu 9514-6101)
Stellar losvd from nonparametric model
Although not a perfect match this is somewhat closer to the DAP map. I suspect what’s happening here is that there really are at least two, and more likely 3 distinct kinematic components. I haven’t read the DAP release paper in a while and don’t know exactly how they estimate stellar velocities, but in any case their model just returns a single value for visualization purposes. To see the (possible) complexity of the actual data here are the results for a single fiber with the largest positive velocity offset in the map above. Again, I don’t know how much of the structure in the posterior distribution of the convolution kernel is real, but it’s evident there’s more complexity than is captured in the first two moments shown in the middle and right panes.
NGC 810 – sample nonparametric losvd
Besides the kinematic modeling I did run star formation history models on the full RSS data set using the same tools as in recent posts. I’m not going to discuss them in detail, but some summary maps are worth showing. In the graphic below these are, from top left, stellar mass density, Hα luminosity density uncorrected for attenuation, SFR density (as usual 100Myr average), and stellar dust attenuation.
There’s no sign of a disk in the stellar mass map, which faithfully follows the distribution of light. A disk is visible in Hα and the small amount of recent starformation is also confined to a disk and nuclear region. In the fourth pane I show the modeled stellar dust attenuation, mostly just to demonstrate that this component of the model does capture something of reality.
NGC 810 – a sampling of quantities derived from star formation history models
Getting back briefly to the first paragraph, there are 8 post-starburst galaxies from the catalog of Melnick and de Propris and 24 from an ancillary program to observe post-starburst galaxies from various sources that was added for DR17. There’s just one galaxy from the former catalog in the latter set, so that makes 31 total, an easily manageable number. There are also 24 of Schawinski’s blue ellipticals. Of course there are many disk galaxies, far too many for me to look at.
I decided to try a set of models for one galaxy – NGC 4889 (with MaNGA plateifu 8479-12701), which had the highest overall velocity dispersion of the Coma sample I’ve been discussing in the last several posts. It also has some evidence for multiple kinematic components which isn’t too much of a surprise since it’s one of the central cD galaxies in Coma. The SSP model spectra fed to the SFH models were preconvolved with the element wise means of the LOSVD convolution kernels from the velocity distribution modeling exercise. Again, this is an expedient to avoid what could otherwise be prohibitively computationally expensive. The models I ran were the same as described back in this post — these ignore emission but do model dust attenuation with the usual modified Calzetti attenuation relation.
To get quickly to the results, here are model star formation histories compared to the previous runs that used the full model in its current form. Usually I like these plots of results from all spectra in an IFU, but in this one all 381 spectra met my S/N criterion, so the plot is pretty crowded. You really need to see it live on a 4K monitor to see the details.
NGC 4889 (MaNGA plateifu 8479-12701)
Model star formation histories for all spectra, runs with non-parametric LOSVD vs. single gaussian stellar velocity dispersions
Well it’s pretty hard to see but differences in model SFH’s are mostly in the youngest age bins, which are very poorly constrained anyway in these presumably passively evolving galaxies. Here’s a closer look at a single model run that had the largest difference in estimated stellar mass density (more on this right below) of about 0.19 dex:
NGC 4889 (MaNGA plateifu 8479-12701)
Model mass growth histories for a single spectrum – runs with non-parametric LOSVD vs. single Gaussian stellar velocity dispersion
So, the difference in star formation histories was slower mass build up between about 12-5 Gyr look back times in the second run, which was responsible for the lower current day stellar mass density. How this resulted from the choice of LOSVD is not at all obvious.
Let’s look at a few summary results. First, the model stellar mass surface densities:
NGC 4889 (MaNGA plateifu 8479-12701)
Model ΣM* – runs with non-parametric LOSVD vs. single Gaussian stellar velocity dispersion
These fall on an almost exactly one to one relation with a few hands full of outliers. Oddly these are mostly in the higher signal to noise area of the IFU (i.e. near the center).
Results for star formation rate density and specific star formation rate are even more consistent between runs, with essentially no differences larger than the nominal 1 σ error bars.
NGC 4889 (MaNGA plateifu 8479-12701)
Model Σsfr – runs with non-parametric LOSVD vs. single Gaussian stellar velocity dispersionNGC 4889 (MaNGA plateifu 8479-12701)
Model SSFR – runs with non-parametric LOSVD vs. single Gaussian stellar velocity dispersion
One problem I encountered was that I had to re-run some models either for technical reasons or because of obvious convergence failures. I suspect there could have been some convergence issues in both sets of runs and am slightly worried that could be the source of the few differences in summary measures seen. Oddly, there were almost no suspicious convergence diagnostics in either set of runs (once the latter were run to satisfactory conclusion), and Stan is quite aggressive about reporting possible convergence issues.
Anyway, modeling kinematics remains an interesting topic to me, but it seems somewhat decoupled from modeling star formation histories. Right now I’m waiting for the final SDSS data release to decide what projects I want to tackle.
I’m going to end with a couple of asides. First, I recognize that all of these error bars are overoptimistic, maybe by a lot. The main reason, I think, is that I treat the flux values as independent which they clearly are not1 this is pretty standard practice however, which effectively results in overestimating the sample size. One possible partial solution is to allow the flux uncertainties to vary from their nominal values by, for example, a factor > 1. This would involve adding as few as one parameter to the models, which is something I’ve actually tried in the past. I may relook at that.
One interesting feature of the previous two graphs is the rather obvious systematic trend with radius of both SFR density and specific star formation rate, as shown more directly below taken from the first set of model runs:
NGC 4889 (MaNGA plateifu 8479-12701)
ΣSFR and SSFR vs. distance from IFU center
Are these real trends? I don’t know, but I don’t see an obvious reason why they might be spurious features of the models. In normal star forming galaxies I encounter trends with radius in both directions and sometimes no trend at all.
As a final and related aside there was a paper by Sedgwick et al. that showed up on arxiv not long ago that presented estimates of star formation rates of early type galaxies from observations of core collapse supernovae carefully matched to host galaxies with high confidence morphological classifications. To oversimplify their conclusions they found that typically massive ellipticals might have specific star formation rates ∼ 10-11 / yr, which is somewhat higher than usually supposed. As I mentioned in my last post my models will always have some contribution from young stars and I typically get central estimates of SSFR > ∼ 10-11.5 even in galaxies with no hint of emission (as is the case with this Coma sample). This particular galaxy has a total stellar mass within the IFU of ∼ 1011.5 M⊙ , so it could be forming stars at a rate of ∼ 1 M⊙ / yr.
Well, I think I have one more post to write before the SDSS DR17 release.
A while back I completed LOSVD models for 3348 spectra in the 33 Coma Cluster galaxies I chose for an initial sample. I want to look briefly at a couple summary statistics from the models. For each sample in the posterior I calculate first and second moments of the velocity distribution, and from those I calculate means and standard deviations of velocity offsets and velocity dispersions. Recall from the earlierposts that wavelengths are in the spectrum rest frame with peculiar velocities estimated by fitting a set of eigenspectra to the data. The first plot below is the mean velocity offset with errorbars ± 1 standard deviation versus the signal to noise in each spectrum. The horizontal line is the overall median of 5.25 km/sec. This is less than 1/10th the width of a wavelength bin and, I think, consistent with the absolute wavelength calibration accuracy claimed by the MaNGA team. From an eyeball analysis there doesn’t appear to be any trend in the mean with S/N, but the dispersion in estimates increases as the data quality gets worse. This seems unlikely to be a real problem. Two outliers cut off from the graph had mean velocity offsets of ≈ 200 km/sec, which is only 3 wavelength bins.
Mean velocity offset and standard deviation of mean vs. spectrum S/N for 33 passively evolving Coma Cluster galaxies. Solid horizontal line is median offset.
Possibly more concerning is that the mean velocity dispersion also shows a systematic trend with S/N:
Mean velocity dispersion and standard deviation of mean vs. spectrum S/N for 33 passively evolving Coma Cluster galaxies.
Of course there is a wide range of velocity dispersions since there’s a range of galaxy masses in this sample, but each galaxy shows a similar trend. This matters because, of course, S/N correlates strongly with distance from the nucleus which is usually the IFU center and this in turn leads to potentially spurious correlations with distance.
MaNGA spectrum S/N vs. distance from IFU center in kpc. — 33 passively evolving Coma Cluster galaxies
For example here are results for the cD galaxy NGC 4889 with MaNGA plateifu 8479-12701. This has the highest overall velocity dispersion in the sample by a fair margin as seen in the plots above. Plotting the estimated velocity dispersion against distance from the IFU center shows an apparent systematic increase1the trendline is just a “loess” smooth fit to mislead the eye and shouldn’t be interpreted as any kind of analysis:
NGC 4889 (MaNGA plateifu 8479-12701) – mean velocity dispersion vs. radius per nonparametric LOSVD fit.
Now this could be a real trend: my recollection is the outskirts of cD galaxies have essentially the velocity dispersion of the clusters they live in, which is taken as strong evidence that they grow by cannibalism. But the IFU only covers the inner part of this galaxy and in any case the confounding effect of the correlation between S/N and modeled velocity dispersion prevents any conclusion. Just for comparison here is the same relation using the single gaussian estimates from the preliminary maximum likelihood fits:
NGC 4889 (MaNGA plateifu 8479-12701) – velocity dispersion vs. radius per maximum likelihood fit.
So, if we’re interested in kinematics or dynamics some regularization with an informative prior seems advisable. What’s not so clear is whether this matters in SFH modeling, which as I’ve said many times is what most interests me. There’s one way to find out…
