Structural Analysis of Galaxies from Image Decompositions

Size: px

Start display at page:

Download "Structural Analysis of Galaxies from Image Decompositions"

Tabitha Walton
5 years ago
Views:

1 Structural Analysis of Galaxies from Image Decompositions Concepts Dimitri Gadotti (ESO)

2 Initial Considerations 1. This topic in the context of the School is a very interesting complement Ho+ 11; CGS Athanassoula+ 13

A useful source is the 2013 Deconstructing Galaxies conference:

3 Initial Considerations 2. The field is evolving very rapidly in the last few years. A useful source is the 2013 Deconstructing Galaxies conference: GIM2D, GALFIT, BUDDA, SIGMA, MegaMorph, Galapagos, IMFIT, BDBar, GALFIDL, GASP2D

4 Initial Considerations 3. It is easy to press enter and start plotting the results. To do it right it is damn difficult! Why? Because: There are a number of details one might miss, and they can ruin the results. It is still a technique just leaving its infancy. There is a lot of subjective input. In this sense, from a mathematical viewpoint, there s no right answer, it always depends on one s input and goals. To go from the math to the physical meaning is the challenging step. Models are often inaccurate! One is fitting a large number of parameters! There is significant degeneracy between them.

5 Outline 1. Motivation 2. Modeling structural components 3. Input what components to fit fitting bars, nuclear point sources and disk breaks how to guess well input parameters 4. More examples and applications 5. Uncertainties and degeneracy 6. The nasty effects of dust 7. Fitting edge-on galaxies 8. Working with simulations

6 Motivation Where do we want to go and how do we get there Ho+ 11; CGS

7 Motivation Gadotti 09 Where do we want to go and how do we get there

8 Motivation Gadotti 09 Where do we want to go and how do we get there

9 Motivation Where do we want to go and how do we get there Ingredients: A galaxy image With good measures of background and PSF Input parameters Decide how many structural components to fit Critical step: ellipse fits are very helpful to get good first guesses A code That will create a model minimizing the reduced χ2:

) Apart from the geometrical properties, the light distribution of each component should be described too.

10 Models Galaxy structural components are usually modeled each as a series of concentric ellipses at a fixed position angle and axial ratio b/a. (Remember: ellipticity is 1 b/a.) Apart from the geometrical properties, the light distribution of each component should be described too. This can vary for the different components depending on the code used. Here this corresponds to BUDDA (de Souza, Gadotti & dos Anjos 04; Gadotti 08). nuclear point source bulge bar disk

11 Models The disk surface brightness radial profile can be described either by a single exponential or by a broken/double exponential (Freeman 70; see also Erwin+ 08). Disks with larger scale lengths have a flatter profile. μ r

12 Models The bulge and bar surface brightness radial profiles are described by a Sérsic function (Sérsic 63; see also Caon+ 93).

13 Models The Sérsic function A high Sérsic index n means a steep inner profile and a shallow tail at low surface brightness. There is relatively little difference in the profile shapes between profiles with high values of n (n>2). This has implications for (i) disk-like bulges (ii) measure uncertainties n=4: de Vaucouleurs 48 n=1: exponential n=0.5: Gaussian Graham & Driver 05

14 Models The Sérsic function Many ellipticals and classical bulges can be well fitted with a de Vaucouleurs (n=4) profile. However, these stellar systems show a range of Sérsic indices (e.g. Gadotti 09; Kormendy+ 09). Therefore, fixing n at any given value will lead to an overestimation (underestimation) of e.g. re if the true value of the bulge Sérsic index is less than (more than) the fixed value (Graham & Prieto 99). Fixing n=4 to fit ellipticals and classical bulges is wrong!

15 Models The Sérsic function The light distribution of bars can be well described with a Sérsic function. It can also reproduce the observed dichotomy between bars with flat and exponential profiles (Elmegreen & Elmegreen 85; Kim+, in prep.). Kim+, in prep.

16 Models Some times it is necessary to account for the presence of a nuclear point source, usually modeled with the PSF. We will stop at a maximum of 4 components for the moment, but more complex models are possible.

17 Input How many components does the galaxy have? Which components are these? A list of possible components include (and are not restricted to): 1. disk (thin/thick) 2. classical bulge 3. bar+box/peanut+barlens 4. spiral arms 5. inner disk 6. inner bar 7. inner spiral arms 8. lens(es) 9. nuclear ring 10. inner ring Each of these structural components has different (though in some 11. outer ring cases similar) formation histories and physical properties. The 12. stellar halo photometric bulge can actually be several of these, even 13. nuclear point source bulge can be any of the components simultaneously. A disk-like number 5 through 9 in the list above, or any combination of them.

18 Input How many components does the galaxy have? Which components are these? How does one decide which components to fit? 1. Inspect the galaxy image 2. Inspect isophotal contours DS9/Analysis/Contours IRAF/IMEXAMINE: contour plot, type e, edit parameters with epar eimexam, default parameters usually work fine 3. Inspect surface brightness profiles 2D (IRAF/IMEXAMINE: radial profile, type r, edit parameters with epar rimexam ) Ellipse fits (IRAF/ELLIPSE) Radial cuts (IRAF/PVECTOR)

19 Input How many components does the galaxy have? Which components are these?

20 Input How many components does the galaxy have? Which components are these? R 18 g a la x y to ta l m o d e l bar b u lg e d is k -2 µ (m a g arcse c ) μ IC r g a la x y - m o d e l r (a rc se c ) 30

21 Input How many components does the galaxy have? Which components are these?

22 Input How many components does the galaxy have? Which components are these?

23 Input Do I need to include a central point source? A central point source can be: 1. A type 1 AGN (check NED) 2. A nuclear stellar cluster It alters significantly the bulge profile, in particular the bulge Sérsic index. As a rule, only add it if you are absolutely sure you need it. (This rule actually applies to all components!)

24 Input Do I need to include a central point source? Gadotti 08

25 Input Do I need to include a central point source? How can one be sure? Usually the point source creates a very steep inner profile, and, of course, results in a large Sérsic index. Gadotti 08

26 Input Fitting bars If your galaxy has a bar, you MUST model it! (Laurikainen+ 05; Gadotti 08). Otherwise, the resulting bulge model can be very wrong. Gadotti 08

27 Input Fitting bars If your galaxy has a bar, you MUST model it! (Laurikainen+ 05; Gadotti 08). Otherwise, the resulting bulge model can be very wrong. Gadotti 08

28 Input Fitting bars 2D fits are better than ellipse fits to measure bar axial ratios. Ellipse fits result in systematically less eccentric bars (by ~ 20%). Gadotti 08

29 Input Fitting bars The distribution of bar ellipticities obtained from 2D fits for nearly 300 local barred galaxies peaks at 0.6, indeed about 20% higher than the peaks found in studies based on ellipse fits (e.g. Marinova & Jogee 07; Menéndez-Delmestre+ 07; Barazza+ 08; Marinova+ 09). Gadotti 11

30 Input Fitting bars Residual images show dust lanes reaching very close to the center. Gadotti 08

31 Input Fitting bars Residual images also show nuclear spiral arms, excesses of light at the bar ends, and barlenses! (See talks by Athanassoula and by Laurikainen at the Deconstructing Galaxies meeting.) Gadotti 08

32 Input Fitting bars Gadotti 08

33 Input Fitting bars Athanassoula 92 Elongated structure inside the bar may be pointing out a region dominated by more eccentric orbits. And maybe we need more sophisticated bar models Gadotti 08

34 Input Fitting bars Gadotti 08: residual images show another structure within the bar, but this is only in the central region of the galaxy. This could be associated with an inner disc or a lens. Lia and Eija suggest that barlenses are box/peanuts seen at close to face-on projections. Gadotti 08

35 Input Fitting bars Gadotti 08

36 Input Fitting bars Gadotti 08

37 Input Slide by Nacho Trujillo Fitting disk breaks

38 Input Slide by Nacho Trujillo Fitting disk breaks

39 Input Fitting disk breaks Kim, Gadotti+ 14: structural analysis of 144 barred galaxies from S4G. Fits include disk breaks.

40 Input Fitting disk breaks So, what happens if disk breaks are not accounted for? Kim+ 14

41 Input Fitting disk breaks So, what happens if disk breaks are not accounted for? Erwin & Gadotti 12

42 Input Fitting disk breaks Disk scale length and central surface brightness can be wrongly estimated. Kim+ 14

43 Input Fitting disk breaks Disk scale length and central surface brightness can be wrongly estimated. Kim+ 14

44 Input Fitting disk breaks This affects to some extent B/T, D/T and Bar/T. Kim+ 14

45 Input An example of a bad fit Gadotti 08

46 Input How to estimate good first guesses for all parameters? x0,y0: brightest pixel. E.g., IRAF/IMEXAMINE: type a near the center of the galaxy

47 Input 8.3 mag -2 PA and ε are easy: can get them directly from ellipse fits for all components µ (mag arcsec ) How to estimate good first guesses for all parameters? 25 re E 4 mag -2 µ (mag arcsec ) re h n=2 µe-µ0=4 15 S0 n=1 µe-µ0= mag 25 re h early S re h late S n=0.55 µe-µ0= µ (mag arcsec ) Bar: μe, re, n and LBar n=3 µe-µ0=6.2 bulge bar disk total 20 Disk: μ0 and h Bulge: μe, re and n n=4 µe-µ0=8.3 seeing! 15 n=1 µe-µ0= mag 25 re,bar 2 LBar early SB 4 6 r (kpc) 8 re,bar 2 LBar late SB 4 6 r (kpc) 8

48 Input 8.3 mag -2 µ (mag arcsec ) How to estimate good first guesses for all parameters? 15 n=4 µe-µ0=8.3 seeing! re -2 4 mag 15 µ (mag arcsec ) n=3 µe-µ0=6.2 bulge bar disk total E re n=2 µe-µ0= mag 25 h S0 n=1 µe-µ0=1.8

49 0 seeing! 8.3 µ (mag arcsec -2 e bar disk Input total e 0 20 estimate good first guesses for all parameters? How to 25 re E 4 mag -2 µ (mag arcsec ) h n=2 µe-µ0=4 15 S0 n=1 µe-µ0= mag 25 re 15-2 µ (mag arcsec ) re h early S re h n=0.55 µe-µ0=0.8 n=1 µe-µ0= mag 25 DAGAL School Marseille 2014 LBar late S LBar

50 4 mag -2 µ (mag arcsec e 0 e 0 Input 20 estimate good first guesses for all parameters? How to 1 mag 25 re h re h late S n=0.55 µe-µ0= µ (mag arcsec ) early S n=1 µe-µ0= mag 25 re,bar 2 LBar early SB 4 6 r (kpc) 8 re,bar 2 LBar late SB 4 6 r (kpc) 8

51 Input How to estimate good first guesses for all parameters? Boxiness: the c coefficient here: Very important for bars Athanassoula+ 90 Also for some early-type galaxies and bulges (e.g. Fornax A, ESO510-G13) c=2: perfect ellipse c>2: boxy ellipse c<2: disky ellipse a bar

52 Input How to estimate good first guesses for all parameters? Boxiness: the c coefficient here: Very important for bars Athanassoula+ 90 Kim+, in prep. Also for some early-type galaxies and bulges (e.g. Fornax A, ESO510-G13)

53 Input How to estimate good first guesses for all parameters? Boxiness: the c coefficient here: Very important for bars Athanassoula+ 90 Also for some early-type galaxies and bulges (e.g. Fornax A, ESO510-G13) Distribution of boxiness for nearly 300 local barred galaxies Definitely important to fit c! Gadotti 11

54 Input How to estimate good first guesses for all parameters? Athanassoula+ 90 Similar results found using 144 barred galaxies from S4G Kim+, in prep.

55 Input How to estimate good first guesses for all parameters? Central point source: Same FWHM as seeing. Peak intensity: Again can be measured with IRAF/IMEXAMINE, but need to subtract estimates for the central intensities of all other components.

56 Input Other necessary input parameters Image size in pixels Pixel size Seeing FWHM + Moffat β parameter Better than a Gaussian to account for atmospheric turbulence (Trujillo+ 01) is canonical value Very important to measure accurately! Affects significantly the bulge Sérsic index. Background Also, very important to measure accurately! Affects significantly the disk scale length. Best to include background in the fitted image but not as a free parameter. Gain, read-out noise, number of combined frames

57 More Examples and Applications Gadotti 09

58 More Examples and Applications Gadotti 09

More Examples and Applications Disk-like bulges, classical bulges and elliptical galaxies are clearly isolated in this diagram, indicating that the

59 More Examples and Applications Disk-like bulges, classical bulges and elliptical galaxies are clearly isolated in this diagram, indicating that the separation is not artificial, but has solid physical grounds. A section with composite bulges can also be seen between classical and disklike bulges. Gadotti 09

60 More Examples and Applications How the mass-size relation of bulges and ellipticals compare? log (size) = alpha log (mass) bars: α=0.21 disks: α=0.33 disk-like: α=0.20 classical: α=0.30 ellipticals: α=0.38 (±0.02) Gadotti 09

61 More Examples and Applications The mass-size relation of disk-like bulges is different from that of classical bulges by 5σ The mass-size relation of classical bulges is different from that of ellipticals by 4σ The only pair of components with similar mass-size relations are disk-like bulges and bars bars: α=0.21 disks: α=0.33 pseudo: α=0.20 (±0.02) classical: α=0.30 ellipticals: α=0.38 Gadotti 09

62 More Examples and Applications At the high-mass end, classical bulges are not just ellipticals surrounded by disks bars: α=0.21 disks: α=0.33 pseudo: α=0.20 (±0.02) classical: α=0.30 ellipticals: α=0.38 (See also papers by Laurikainen, Simard, and Graham.) Gadotti 09

36% in disks ~ 3% in disk-like bulges ~ 4% in bars ~ 32%

63 More Examples and Applications The stellar mass budget at redshift zero for galaxies with stellar mass > 1010 MSun ~ 36% in disks ~ 3% in disk-like bulges ~ 4% in bars ~ 32% in elliptical galaxies ~ 25% in classical bulges Gadotti 09

64 Uncertainties and Degeneracy In BUDDA, 1σ uncertainties are calculated by varying each parameter individually until change in χ2 reaches the appropriate threshold. Uncertainties are usually around 10 20%. But this does note account for uncertainties in models and degeneracies (or coupling) between the various parameters and uncertainties.

65 Uncertainties and Degeneracy Variations in input parameters can some times increase uncertainties. Bulge parameters (particularly n) are less stable.

$disk galaxies, but also in a significant fraction of early-type$ galaxies.

66 The Nasty Effects of Dust Dust is present in copious amounts in most disk galaxies, but also in a significant fraction of early-type galaxies. In the latter, it is usually interpreted as a sign of a merger event. How does dust affect image decompositions? ESO VISTA VVV Survey

67 The Nasty Effects of Dust NGC 2768 (SDSS)

68 The Nasty Effects of Dust NGC 2768 (HST, Judy Schmidt)

69 The Nasty Effects of Dust Fornax A ( Taken from Bob and Pats farm in average seeing, Michael Sidonio). Ripples agree with merger scenario (Bosma+ 85).

70 The Nasty Effects of Dust Fornax A (HST)

71 The Nasty Effects of Dust BUDDA decomposition of a Ks SOFI NTT image reveals inner disk component (Beletsky, Gadotti+ 11). Residuals after a bulge+agn model only

72 The Nasty Effects of Dust Accounting for the disk reveals a nuclear, gaseous spiral-like structure, as well as a nuclear disk. Residuals after a bulge+agn+disk model Beletsky+ 11

73 The Nasty Effects of Dust Modeling the gaseous spiral arms can reproduce nuclear undulations in geometric radial profiles. Beletsky+ 11

74 The Nasty Effects of Dust VLT/SINFONI data reveal that the nuclear disk may be a kinematically decoupled core, and produces a sigma drop. Nowak+ 08 discuss the possibility of a distinct, younger stellar population there. This is a very nice illustration of the power of image decomposition and residual images in unveiling hidden structural components. Beletsky+ 11

75 The Nasty Effects of Dust A number of studies have addressed the effects of dust attenuation in the measurements of structural parameters of bulges and disks separately (e.g. Kylafis & Bahcall 87; Byun+ 94; Pierini+ 04; Möllenhoff+ 06; Driver+ 07). These studies suggest that dust effects depend on: 1. Wavelength 2. Galaxy inclination 3. Star/dust geometry In general, in the B band, dust can significantly affect:. disk scale length (resulting in an overestimation of up to 50%). central surface brightness, (dimming of up to 1.5 mag) But what is the effect of dust in a decomposition, when both bulge and disk parameters are measured simultaneously?

76 The Nasty Effects of Dust In Gadotti+ 10 we have used SKIRT, a 3D Monte Carlo radiative transfer code (Baes+ 03, 05), to create artificial, dusty galaxies. Typical galaxy parameters were drawn from Hunt+ 04 and Gadotti 09. Stellar population age defines spectral energy distribution.

77 The Nasty Effects of Dust Dust model is a mixture of graphite, silicate and polycyclic aromatic hydrocarbon dust grains. Physical processes include absorption, multiple anisotropic scattering and thermal re-emission. The V band face-on optical depth defines the total dust mass: κv is the extinction coefficient at the center of the V band model. We considered models with τ = 0, 0.2, 0.5, 1, 2, 4, 6 and 8, and inclination angles of 0, 30, 45 and 80 degrees. And then we run BUDDA on them

78 The Nasty Effects of Dust Gadotti+ 10

79 The Nasty Effects of Dust Gadotti+ 10

80 The Nasty Effects of Dust Gadotti+ 10

81 The Nasty Effects of Dust Gadotti+ 10

82 The Nasty Effects of Dust These results show that the disk luminosity distribution is strongly constrained by its outer parts, which contain a much larger number of pixels, where dust effects are relatively small. This produces an excess of light in the central regions of the galaxy, which is taken care of by making the bulge component less important. Because disk-like bulges are smaller, their galaxies suffer more strongly from dust effects. Gadotti+ 10

83 The Nasty Effects of Dust In summary, there is a complex interplay between the bulge and disk models, the latter being less flexible to accommodate dust effects, resulting in: 1. Disk scale lengths are overestimated 2. Bulge effective radii and Sérsic indices are underestimated 3. The attenuation in the integrated disk luminosity is underestimated, whereas the corresponding attenuation for the bulge is overestimated 4. All this results in B/D being underestimated Bulge parameters are the most affected and the B/T ratio can be underestimated by a factor 2. Effects can be significant even at low inclinations and dust opacities. Further, effects can be stronger in galaxies with small, disk-like bulges. To derive accurate bulge parameters is difficult.

84 Edge-on Galaxies NGC 3314 (HST) One is dissecting ghosts we can see through galaxies, there are projection effects, significantly strengthened in the case of edge-on galaxies.

85 Edge-on Galaxies Dust effects are of course also enhanced. NGC 891: 2MASS JHKs composite

86 Edge-on Galaxies Identifying components is even less straightforward. The COBE Project, DIRBE, NASA

87 Edge-on Galaxies Identifying components is even less straightforward. NGC 4251: SDSS gri composite

88 Edge-on Galaxies NGC 4251: SDSS i band (Gadotti+, in prep.) Identifying components is even less straightforward.

89 Edge-on Galaxies Gadotti & Sánchez-Janssen 12 Ellipse fits blend different components very strongly. Major/minor axes cuts might be more helpful. The Sombrero galaxy

90 Edge-on Galaxies Disk surface brightness distribution has to be modeled differently, and scale height is an extra parameter to fit (van der Kruit & Searle 81). One can guess z0 by cutting a profile perpendicular to the disk at R ~ h.

91 Edge-on Galaxies Gadotti & Erwin, in prep.

Simulations To compare results from real and simulated galaxies is a very instructive practice. E.g., one can see if simulations are reproducing observations. (Ongoing work with Lia and Taehyun Kim.

92 Simulations To compare results from real and simulated galaxies is a very instructive practice. E.g., one can see if simulations are reproducing observations. (Ongoing work with Lia and Taehyun Kim.) Cosmological hydrodynamical simulations (Aquarius; Springel+ 08) rendered with SUNRISE (Jonsson 06; Jonsson+ 10). SUNRISE is a Monte Carlo radiative transfer code, producing images from the simulations, as if they were real observations: with dust, PSF, noise etc. Scannapieco, Gadotti+ 10

93 Simulations The simulations aimed at reproducing Milky Way like galaxies. Haloes have no neighbor exceeding half of their mass within 1.4 Mpc Dark Matter particle: M Gas particle: M Same softening for all particles: kpc Final halo masses: M Spin parameter: Gadget-3: stochastic star formation, metal-dependent cooling, chemical enrichment, feedback from Type II and Type Ia SNe, multiphase gas model (for details see Scannapieco+ 09)

94 Simulations Some simulations show realistic bulges and bars, except for bulge effective radius. Scannapieco+ 10

95 Simulations D/T ratios measured photometrically alleviate disagreement between simulations and observations, as compared to kinematically measured D/T. Scannapieco+ 10

The growth of supermassive black holes in bulges and elliptical galaxies

The growth of supermassive black holes in bulges and elliptical galaxies in collaboration with Guinevere Kauffmann Max Planck Institute for Astrophysics Outline Work with two main observables: 1. M Bulge