The Stellar Mass-Size Evolution of = 7 to z = 0

The Stellar Mass-Size Evolution of = 7 to z = 0
The Stellar Mass-Size Evolution of
Galaxies From z = 7 to z = 0
Moein Mosleh
Cover design: Moein Mosleh
Published by: Uitgeverij BOXPress, ’s-Hertogenbosch
ISBN: 978-90-8891-642-7
ISBN 978-90-8891-642-7
9 789088 916427
The Stellar Mass-Size Evolution of
Galaxies From z = 7 to z = 0
PROEFSCHRIFT
ter verkrijging van
de graad van Doctor aan de Universiteit Leiden,
op gezag van de Rector Magnificus prof. mr. C. J. J. M. Stolker,
volgens besluit van het College voor Promoties
te verdedigen op woensdag 12 juni 2013
klokke 15.00 uur
door
Moein Mosleh
geboren te Shiraz, Iran
in 1980
Promotiecommisie
Promotor:
Prof. dr. M. Franx
Co-Promoter:
Overige leden:
Dr. R. J. Williams
Prof. dr. H. J. A. Rottgering
Prof. dr. K. Kuijken
Dr. J. Brinchmann
Prof. dr. J. Schaye
Dr. A. Bunker
Carnegie Observatories
University of Oxford
To Mom, Dad and Mahsan
“Adam’s sons are body limbs, to say;
For they’re created of the same clay.
Should one organ be troubled by pain,
Others would suffer severe strain.
Thou, careless of people’s suffering,
Deserve not the name, human being.”
Saadi Shirazi
Contents
1
2
3
Introduction
1.1 History . . . . . . . . . .
1.2 Galaxies at High Redshifts
1.3 Scaling Relations . . . . .
1.4 This Thesis . . . . . . . .
1.5 Conclusion and Outlook .
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The Evolution of the Mass-Size Relation to z = 3.5 for UV-Bright Galaxies
and Submillimeter Galaxies in the GOODS-NORTH Field
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 Description of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3 Sizes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3.1 Size Measurements . . . . . . . . . . . . . . . . . . . . . . . . .
2.3.2 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4 Stellar Mass estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.5 Subsamples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6.1 Size Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6.2 Stellar Mass-Size Relation . . . . . . . . . . . . . . . . . . . . .
2.6.3 Color-Surface Density . . . . . . . . . . . . . . . . . . . . . . .
2.6.4 Sizes of Submillimeter Galaxies . . . . . . . . . . . . . . . . . .
2.7 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.7.1 The growth of star-forming galaxies . . . . . . . . . . . . . . . .
2.7.2 Comparison to previous work . . . . . . . . . . . . . . . . . . .
2.7.3 Caveats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.9 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The Evolution of Mass-Size Relation for Lyman Break Galaxies From z
to z = 7
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Description of Data . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Sizes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.1 Size-Mass Evolution . . . . . . . . . . . . . . . . . . . . . .
3.4.2 Size Evolution at Fixed Mass . . . . . . . . . . . . . . . . . .
3.5 Summary And Discussion . . . . . . . . . . . . . . . . . . . . . . .
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ix
4
5
On the Robustness of z = 0 − 1 Galaxy Size Measurements
and Non-Parametric Fits
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . .
4.2 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3 Sizes at z = 0 . . . . . . . . . . . . . . . . . . . . . . .
4.3.1 Parametric Methods . . . . . . . . . . . . . . .
4.3.2 Non-Parametric Method . . . . . . . . . . . . .
4.3.3 Simulations (I) & (II) . . . . . . . . . . . . . . .
4.4 Stellar Mass-Size Relation At z = 0 . . . . . . . . . . .
4.5 Redshifting Galaxies to z = 1 . . . . . . . . . . . . . . .
4.5.1 Method . . . . . . . . . . . . . . . . . . . . . .
4.5.2 Comparing to Sizes at z = 0 . . . . . . . . . . .
4.5.3 Stellar Mass-Size Relation after Redshifting . . .
4.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . .
4.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . .
4.8 Acknowledgments . . . . . . . . . . . . . . . . . . . .
4.9 Appendix A . . . . . . . . . . . . . . . . . . . . . . . .
4.9.1 Failure of Single Sérsic Fitting at z = 0 . . . . .
4.10 Appendix B . . . . . . . . . . . . . . . . . . . . . . . .
4.10.1 High Redshift Simulations . . . . . . . . . . . .
Galaxy Zoo: Passive Red Spirals
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . .
5.2 Sample Selection and Data . . . . . . . . . . . . . .
5.2.1 Selection of Red Spiral Galaxies . . . . . . .
5.3 Star Formation in Red Spirals . . . . . . . . . . . . .
5.3.1 Dust Content . . . . . . . . . . . . . . . . .
5.3.2 Recent Star Formation History . . . . . . . .
5.4 The Effect of Environment . . . . . . . . . . . . . .
5.4.1 The Environments of Red Spirals . . . . . .
5.4.2 Environmental Dependence of Star Formation
5.5 The Impact of AGN . . . . . . . . . . . . . . . . . .
5.6 Bar Fractions in Red/Blue Spirals . . . . . . . . . .
5.7 Discussion . . . . . . . . . . . . . . . . . . . . . . .
5.7.1 Future Directions . . . . . . . . . . . . . . .
5.8 Summary and Conclusions . . . . . . . . . . . . . .
5.9 Appendix A: Sample of Data Tables . . . . . . . . .
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Nederlandse samenvatting
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Curriculum vitae
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Acknowledgement
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x
Introduction
1
1
Chapter 1 – Introduction
1.1
History
At the beginning of the twentieth century, the Milky Way Galaxy was believed to occupy
more or less the whole Universe. It was not until the 1920’s that the existence of galaxies
external to the Milky Way was established. Pioneering efforts by astronomers such as
Edwin Hubble proved that many of the nebulae objects observed at the time, were indeed galaxies outside our Milky Way. Many external galaxies were found and observed
afterwards. In order to address them in a convenient and easy way, astronomers classified these objects according to their structures and shapes, or in short, morphology. The
first classification scheme for galaxies was introduced by Hubble (1926) and has become
known as Hubble tuning fork. This system, which is still in use today breaks galaxies
into elliptical, lenticular, spiral, irregular. and each can be divided into subclasses based
on the existence of extra features such as bars. The differences between various types,
in fact, reflect the differences in their physical properties. Since then, astronomers have
attempted to quantify the physical properties of galaxies in detail.
Spiral galaxies were found to have different stellar populations than ellipticals. The
amount of gas and recent star formation of these galaxies are distinct from the ellipticals and they have bluer colors. The stellar populations of elliptical galaxies are old with
redder colors and they tend to be more massive than the spirals (Kauffmann et al. 2003,
Blanton et al. 2005). In general, observed quantities such as color, shape, luminosity, current star-formation rate, stellar and dynamical mass, circular velocity and velocity dispersion are the empirical properties for distinguishing galaxies and studying their underlying
physics. (See more in review by Blanton & Moustakas 2009)
The diversity of galaxy populations observed in the present-day Universe raised questions about the origin of these differences. Astronomers strive to discover the story of
formation and evolution of galaxies in theoretical and observational frameworks. The
theoretical framework established in the 1960-70’s (e.g., Eggen et al. 1962, Sandage et al.
1970, Press & Schechter 1974) describes the formation of galaxies from gravitational instability of density perturbations in the dark matter distribution and condensation of gas.
According to galaxy formation theory, as the dark matter halo collapses, shock heating
will cause the gas within that halo to cool. The cooling will eliminate the pressure of the
gas, however, in order to prevent the gas from ending up all at the center, some initial
angular momentum of gas (acquired via tidal torques in the early Universe) is required.
This helps to assemble the gas into a rotating disk (see e.g., Mo et al. 1998). However,
different models can use different assumptions for density profiles of the dark matter halos
and also for the initial dependence of the gas angular momentum on their dark matter
halos. It is also not clear whether the gas angular momentum can change with time or
how the star formation and feedback processes have an effect on changes of the structural
properties of galaxies, such as their sizes.
There are mainly two different scenarios for the formation of bulges of late-type galaxies: One assumes that they are formed through merging and the other process is based on
disk instabilities. The formation of the bulge through merging of two or more galaxies
requires accretion of cold gas later on to form a disk around the bulge. Consequently,
the bulge component can potentially have different stellar population properties in com2
1.2 Galaxies at High Redshifts
parison to the disk. In the disk-instability scenario, the low angular momentum material
near the center will finally transfer into the bulge. Nevertheless, many other assumptions
need to be taken into account (e.g., feedback processes) for a full understanding of the
formation and evolution of a typical late-type galaxy.
The formation of early-type galaxies is also not well understood. One scenario for the
formation of these galaxies is from mergers of galaxies. Based on simulations, mergers of
disk galaxies can reproduce similar properties of a typical elliptical galaxy (e.g., Hernquist
1992). Although this general model can predict simple properties of these galaxies, many
properties still do not agree with the observations.
Therefore, direct observations are essential to test galaxy formation models. These
observations should not only include complete samples of nearby galaxies, but also require large samples of galaxies at earlier stages of the Universe. As a result, identification
of the first and most distant galaxies started to become more important by the mid-1970’s
and still continues today. The frontier of distant galaxies moved to redshifts of z ∼ 1 − 4
in the 1990’s corresponding to lookback times of ∼ 7 − 12 Gyr. Thanks to deep and ultra
deep observations during the last decade, the samples of high redshift galaxies have substantially increased and the limit is now pushed further to z ∼ 10 (Bouwens et al. 2012).
1.2
Galaxies at High Redshifts
Observations of galaxies at high redshifts reveal that their properties are very different
compared to galaxies in the nearby Universe (e.g., Conselice & Arnold 2009, Ravindranath et al. 2006) and the Hubble sequence was not in place for most of the galaxies.
Therefore, looking back to a time when galaxies are observed to have different physical
properties is important for understanding galaxy evolution. This provides essential clues
for interpreting how galaxies assembled their stellar masses and structures with time.
There have been several novel techniques developed for identifying galaxies at high
redshifts (i.e., z & 1) over the last two decades. These methods rely on particular features
in galaxy spectral energy distributions. Multi-wavelength observations normally assist to
find these features. Although these techniques have been efficient for detecting high-z
galaxies, they are still suffering from incompleteness.
One of the first methods relies on the rest-frame UV color of galaxies. As the spectral
energy distribution of distant galaxies is shifted to longer wavelengths, their rest-frame
UV spectrum can be observed in optical filters. In addition, the flux short-ward of the Lyman limit is almost completely absorbed by neutral hydrogen in the intergalactic medium
(IGM). The combination of these two phenomenon helped isolate UV-bright star-forming
galaxies at z ∼ 3 in the UGR color-color diagram. These galaxies are called Lyman Break
Galaxies (LBGs) (Steidel et al. 1996). In order to detect galaxies at higher redshifts
(z & 4), this method was modified using redder sets of filters (e.g., Ouchi et al. 2004,
Bouwens et al. 2007, 2011). Based on the rest-frame UV selection, star-forming galaxies
at lower redshifts, 1.4 < z < 2.5, are also selected (BM/BX galaxies: Adelberger et al.
2004, Steidel et al. 2004). Although this technique has been successful in detecting high
3
Chapter 1 – Introduction
redshift star forming galaxies, this method misses passive or dusty star-forming galaxies
at these redshifts.
Using another spectral feature of galaxies in their optical rest-frame (Balmer/4000 Å
break), another technique was developed to isolate galaxies with negligible levels of star
formation at z & 2 (Franx et al. 2003). This technique benefits from using the observed
color of galaxies in the near infrared filters ( JVega − KVega > 2.3). These galaxies which
are called Distant Red Galaxies (DRGs) typically dominate the high stellar mass regime
of galaxies at z ∼ 2. The other method based on optical/near Infrared color is the so-called
BzK method developed by Daddi et al. (2004). This technique can isolate star-forming
and passive galaxies at 1.4 . z . 2.5.
Sub-millimetre galaxies (SMGs) (Smail et al. 1997, Hughes et al. 1998) are systems
at high redshift with a large amount of radiation in the far-IR due to their obscured starformation or AGN activity. They are very massive and luminous. However, their link to
galaxies in the local Universe is not yet understood. Another efficient method for identifying high-z galaxies is using narrowband filter to detect galaxies with large hydrogen
Lyα emission-line equivalent widths. These galaxies are normally faint and their relation
to the other populations of galaxies are yet to be well resolved.
Although the sample size of galaxies at high redshift is increasing they are still much
smaller than surveys of the local Universe such as the Sloan Digital Sky Survey (SDSS).
However, the properties of these high redshift galaxies provide important insight for understanding the formation and evolution of galaxies.
1.3
Scaling Relations
One of the key unsolved problems in astrophysics is to understand the formation and evolution of galaxies. There are many complementary approaches to study the evolution of
galaxies and infer how distant galaxies are connected to galaxies in the present day Universe. These canonical ways are either focused on the evolution of the luminosity/mass
functions of galaxies, the evolution of the star formation rate/stellar mass density, or the
evolution of the observed scaling relations of galaxies. For instance, the luminosity function describes the number density of galaxies within a small luminosity range. This can
constrain the overall abundances of galaxies at each epoch, therefore the evolution of
the luminosity function with redshift provides essential information for understanding the
evolution history of galaxies.
Galaxies show great diversity in their physical parameters, such as luminosity, stellar mass, size and rotational velocity. Interestingly, galaxies obey well-defined scaling
relations between some of these quantities. For instance, the relation between the luminosity and rotational velocity of spiral galaxies is know as a ‘Tully-Fisher’ relation (Tully
& Fisher 1977) which basically defines a correlation between dynamical mass and the
luminosity of galaxies. The relation between the velocity dispersion and luminosity of elliptical galaxies is known as a ‘Faber-Jackson’ relation (Faber & Jackson 1976) in which
accordingly, elliptical galaxies with larger velocity dispersions are brighter.
4
1.3 Scaling Relations
Figure 1.1 – The Stellar mass-size relation for late-type and early-type galaxies in the SDSS (top
panel) and the size dispersion as a function of the stellar mass(bottom panel) from study by Shen
et al. (2003)
It is essential to study the galaxy scaling relations over a wide range of redshifts. This
can help to determine how galaxies move along these relations with time and accordingly,
make it possible to test plausible model(s) for their evolution. In general, the slopes,
zero points and scatters of these scaling relations at different epochs are fundamentally
important to constrain models of galaxy formation.
However, there are some difficulties to obtain accurate measurements for some of the
quantities used in these scaling relations. For instance, measuring the rotational velocity
or velocity dispersion of the faint galaxies at high redshifts requires deep spectroscopic
observations. Acquiring these quantities for a large sample of galaxies is a very time
consuming process. Moreover, as the galaxies get fainter, the robustness of these measurements normally reduces. Therefore, constraining the correlations between some of
these quantities becomes a difficult task for high redshift galaxies.
Among the scaling relations, the relation between the stellar mass and the size of
galaxies has considerable importance. The size of galaxies can be measured using singleband imaging (photometry). The stellar mass of the galaxies can also be measured robustly, thanks to the multi-wavelength photometry and stellar population synthesis modelling. Therefore, there is less difficulties to estimate these properties for a larger sample
of galaxies at high redshifts in comparison to some of the quantities mentioned above.
In addition, the stellar mass and size of galaxies are two important ingredients for characterizing galaxies and have important physical meanings. Studying these quantities at
different epochs will help investigate how the structures of the nearby galaxies have been
5
Chapter 1 – Introduction
Figure 1.2 – The relative distributions of the stellar mass and size of quiescent galaxies at z ∼ 2 and
in the local Universe. The arrows show the predictions of evolution of sizes for each model with
redshift. (Figure is taken From Bezanson et al. (2009).
formed and what were the properties of their progenitors at high redshifts. In brief, this
can help to constrain evolutionary scenarios of galaxy formation and evolution.
The stellar mass-size relation of galaxies in the present day Universe is pointed out
first in Kauffmann et al. (2003) and well characterized by Shen et al. (2003), using large
samples of galaxies in the Sloan Digital Sky Survey (SDSS). The top panel of Figure 1.1
shows the mass-size relation for late-type and early-type galaxies studied by Shen et al.
(2003). The relation is shown to be different for late-type and early-type galaxies. The
early-types have a steeper relation at high stellar mass. This reflects the different history
of formation and the stellar mass assembly for each kind of galaxy. The size dispersions
(bottom panel of Figure 1.1) also vary as a function of the stellar mass and the scatter
decreases for massive galaxies.
Pioneering studies on the sizes of galaxies at higher redshifts were carried out in the
1990’s (e.g., LBGs at z ∼ 3 by Giavalisco et al. (1996) or Lilly et al. (1998) for galaxies up
to z ∼ 1.) However, the results of different studies were not in agreement due to difficulties
in obtaining a large sample of galaxies at higher redshifts and the selection effects caused
by surface brightness limits. However, the study of the size-luminosity relation of galaxies
improved later, using deep ground and space based observations. These studies revealed
that the sizes of galaxies at earlier time were smaller compare to galaxies in the local
universe within a similar mass/luminosity range (e.g., Trujillo et al. 2006b, Zirm et al.
2007, van Dokkum et al. 2008). This means that sizes of massive galaxies within a given
stellar mass should have been increased up to a factor of ∼ 6 with time.
The process of size growth for galaxies can be different for each type and can vary at
6
1.4 This Thesis
each epoch. Star-forming galaxies at high redshifts (e.g., at z ∼ 2), have a larger fraction
of gas per stellar mass compare to their counterparts at low redshifts (e.g., Erb et al. 2006).
One plausible scenario for increasing sizes of these galaxies could be the accretion of gas
into the disk (cold accretion) and converting that into stars (e.g., Law et al. 2012).
Observations have also illustrated that early-type galaxies at high redshifts are significantly smaller. There are two main questions about these galaxies; first is how these
galaxies are formed at high redshift and second is to understand how they are connected
to their low redshift analogs. The formation of these compact quiescent galaxies at high
redshifts are yet to be understood. Nevertheless, there are several mechanisms proposed
to explain the growth of these quiescent galaxies with time, such as major mergers, minor
mergers or adiabatic expansion (e.g., Khochfar & Silk 2009, Naab et al. 2009, Bezanson
et al. 2009, Fan et al. 2008). These mechanisms can change the stellar mass and profiles
of galaxies in different way.
The observed stellar mass-size relation of these massive quiescent galaxies would help
to constrain these models. Equal-mass merging of gas-poor systems (major mergers),
could double sizes and stellar masses of these galaxies. Minor mergers, can increase the
size of spheroids more significantly than the stellar masses, because this process nearly
conserves the central densities and velocity dispersions. The puffing up scenario via adiabatic expansion, suggests the idea of expelling a large amount of material efficiently,
through some sort of feedbacks (e.g., quasar feedback); however, in this process, the
central density and velocity dispersion of a typical early-type galaxy will change. (see
Figure 1.2 for more details). In general, comparing observed scaling relations at different
redshifts (epochs) with results from simulations can help to verify different scenarios of
galaxy formation and evolution.
1.4
This Thesis
The uncertainties associated with the observed properties of galaxies can be further improved by additional observations using deeper data that covers larger area and welldefined complete samples. The multi-wavelength surveys are potent tools for these studies. Using the advantages of recent infrared galaxy surveys, with the aid of ancillary
optical and near infrared data, make it possible for observers to study the properties of
different kinds of galaxies at a wide range of redshifts and pushing the observational limits to the epoch of galaxy formation (z ∼ 10).
This thesis focuses on assessing how the structural properties such as the sizes and the
surface brightness profiles of galaxies change with time. In particular, we study the stellar
mass-size relation of galaxies from z = 7 to z = 0, using recent deep observations in the
near Infrared. Using deep optical and near-IR surveys, helped to characterize the spectral
energy distributions (SEDs) of galaxies at a wide range of redshifts, especially at the peak
of star-formation activity (z ∼ 2). Studying galaxy properties and the scaling relations at
different epochs can place important constrains on the underlying processes assumed for
galaxy mass and structural assembly (e.g., accretion of gas onto galaxies or minor/major
7
Chapter 1 – Introduction
mergers), feedback effects.
Chapter 2: In this chapter, we present the first study of galaxy size evolution using
a sample of objects with spectroscopic redshifts between z ∼ 0.5 − 3.5 in the GOODSNorth field. Most studies use photometric redshifts to measure the evolution of mass-size
relations with time. Using spectroscopic samples can remove some biases based on photometric studies. We further investigate the half-light radii of different types of UV-bright
star-forming galaxies at high redshifts; i.e., sizes of galaxies such as Lyman Break Galaxies, BM/BX galaxies and Lyman Break analog at z ∼ 1 are measured. In addition, we
compare the sizes of these galaxies with other types of star-forming galaxies, such as starforming BzK s and sub-millimeter galaxies (SMGs). The positions of these galaxies on
the mass-size plane may provide clues about their relation to other galaxy populations.
Chapter 3: The newly installed Wide Field Camera 3 (WFC3) camera on the Hubble
Space Telescope and the ultra-deep near-infrared imaging of the Hubble Ultra Deep Field
(HUDF) helped to identify numerous candidates of Lyman Break Galaxies (LBGs) to the
early stages of galaxy formation (e.g., out to z ∼ 8). Many studies have focused on the
evolution of the luminosity function, stellar mass and star-formation rates of the LBGs
at these high redshifts (e.g., Bouwens et al. 2011, Gonzalez et al. 2011). However, the
stellar mass-size relation of these galaxies at z & 4 were not addressed in great detail.
Therefore, in this chapter we take advantage of the ultra-deep WFC3/IR and IRAC observations in the HUDF and Early Release Science (ERS) field to study the stellar mass-size
relation of LBGs out to the redshift of z ∼ 7. At z & 4, the rest-frame optical light shifts to
mid-IR wavelengths, which is a problem in determining stellar masses. The Spitzer telescope provides very sensitive photometry at these wavelengths, but its large PSF can cause
blending problems. However, robust techniques have been developed to deblend nearby
objects and measure the stellar mass of high-z galaxies reliably (Labbé et al. 2006). In
addition, we have used the profile fitting technique (assuming Sérsic models) to measure
the sizes of these very high redshift galaxies, in a consistent way to the lower redshift
analysis. Therefore, we study the stellar mass-size relation of galaxies up to z ∼ 7.
Chapter 4: The stellar mass-size relation of galaxies in the present day Universe can
be used as a baseline for inferring the rate of galaxies size evolution with time. Therefore,
in this chapter we study the mass-size relation for a sample of galaxies at z = 0.01 − 0.02,
dividing the sample based on different common methods of classifications. We also examined different methods of size measurements of galaxies, including single Sérsic fits,
two-component Sérsic models and non-parametric method, in order to quantify the systematics associated in each method. Finally, to test the potential systematics of size measurements at high redshift, we further artificially redshifted our sample to z=1 and re-fit
the galaxies using single Sérsic profile fitting.
Chapter 5: It has been shown by many studies that the majority of galaxies follow
a color-morphology relation up to high redshifts. In the other words, the morphological
transformation and cessation of star-formation could be correlated. However, presence
8
1.5 Conclusion and Outlook
of a population of red or passive spiral galaxies (with a lack of ongoing star-formation)
which was first noticed by van den Bergh (1976) and Couch et al. (1998) appears to break
this relation. In this chapter we carefully selected face-on disk dominated spiral galaxies
(at z ∼ 0) from the Galaxy Zoo morphological catalogue (visually selected) to construct a
sample of truly passive disk galaxies. We attempt to investigate various physical processes
that shut down the star-formation of these red passive spiral galaxies while retaining their
spiral morphology. We study the dust properties and stellar populations of these galaxies
in comparison with blue face-on spiral galaxies. In addition we also examined the environmental properties of these galaxies and looked for AGN activity. We have also tried
to compare the fraction of objects with specific morphological features (such as bars) between red and blue face-on spirals.
1.5
Conclusion and Outlook
We provide some constraints on the galaxy formation and evolution models and also the
methods of measuring structural properties of galaxies at different redshifts. Our results
confirm previous studies of the mass-size relation at high redshift based on photometric
redshifts, and we showed that galaxies of similar mass were generally smaller in the past.
We also show that the stellar mass-size relation of Lyman-break galaxies persists, at least
to z ∼ 5. We find that the best fitting size evolution for galaxies with stellar masses
of log(M∗ /M ) ∼ 10. evolves as (1 + z)−1.20±0.11 . This evolution is very similar for the
galaxies with lower stellar masses of log(M∗ /M ) ∼ 9. This results is in agreement with
simple theoretical galaxy formation models at high redshifts.
We compared the sizes of UV-bright galaxies and Sub-mm galaxies and we found
that the median effective radius of the Sub-mm galaxies are consistent with the BM/BX
galaxies within the same stellar masses. We also confirmed that the star-forming galaxies
(at z ∼ 1 − 3) are significantly larger than quiescent galaxies at the same mass and redshift
by 0.45 ± 0.09 dex. We also confirmed the tight correlation between color and stellar mass
surface density of galaxies at high redshifts using our sample of galaxies with secure
redshifts. This demonstrate that galaxies with higher specific star-formation rates have
larger effective radii than the ones with lower specific star-formation rates.
A larger sample of galaxies with deeper observations at their rest-frame optical for
galaxies at z & 3 is required to robustly constrain many other properties of these galaxies. It would also be interesting to understand the role of environment and intergalactic
medium in shaping the morphologies or structural properties of galaxies. Comparing the
stellar mass/star-formation rate profiles of galaxies at different environment can provide
more clues on the galaxy evolution scenarios. Using larger spectroscopic samples of
galaxies at high redshifts will also help to constrain the galaxies evolution models.
We showed that the stellar-mass size relation of both nearby late-type and early-type
galaxies are steeper at high masses (∼ 3 − 4 × 1010 M ) and flatten at low stellar masses.
This relation is not sensitive to the precise definition of the sample classification based
on color, Sérsic index, morphology and specific star formation rate, with the exception of
9
Chapter 1 – Introduction
blue galaxies which follow a somewhat higher and steeper relation.
In this thesis we also investigated the systematics of different methods of size measurements for galaxies at low and high redshift. We show that nearby early-type galaxies
with stellar masses > 2 × 1010 M are not well fit with single Sérsic profiles. The nonparametric methods and two component fits give less biased measurements for the sizes
of these well-resolved galaxies. However, single Sérsic fit provide robust size estimates
for galaxies at high redshifts.
The results from studying face-on red spiral galaxies showed that these galaxies indeed have older stellar populations and they do not have large amount of dusts. Although
the findings show that these galaxies are common around or just inside the infalling regions of clusters, however, the environment alone cannot turn these galaxies red. Their
AGN luminosity is also not enough for the difference between them and blue spirals. The
fraction of red spiral galaxies with bar features is larger than blue ones and hence this suggests that the cessation of star-formation is strongly correlated with the bar instabilities in
spiral galaxies.
10
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12
2
The Evolution of the Mass-Size
Relation to z = 3.5 for UV-Bright
Galaxies and Submillimeter Galaxies
in the GOODS-NORTH Field
Moein Mosleh, Rik J. Williams, Marijn Franx, Mariska Kriek
The Astrophysical Journal, 2011, 727:5
13
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
Abstract
We study the evolution of the size-stellar mass relation for a large spectroscopic sample of galaxies
in the GOODS North field up to z ∼ 3.5. The sizes of the galaxies are measured from K s -band
images (corresponding to rest-frame optical/NIR) from the Subaru 8 m telescope. We reproduce
earlier results based on photometric redshifts that the sizes of galaxies at a given mass evolve with
redshift. Specifically, we compare sizes of UV-bright galaxies at a range of redshifts: Lymanbreak galaxies (LBGs) selected through the U-drop technique (z ∼ 2.5-3.5), BM/BX galaxies at
z ∼ 1.5-2.5, and GALEX LBGs at low redshift (z ∼ 0.6-1.5). The median sizes of these UV-bright
galaxies evolve as (1 + z)−1.11±0.13 between z ∼ 0.5 and 3.5. The UV-bright galaxies are significantly
larger than quiescent galaxies at the same mass and redshift by 0.45 ± 0.09 dex. We also verify
the correlation between color and stellar mass density of galaxies to high redshifts. The sizes of
submillimeter galaxies in the same field are measured and compared with BM/BX galaxies. We
find that the median half-light radius of SMGs is 2.90 ± 0.45 kpc, and there is little difference in
their size distribution to the UV-bright star-forming galaxies.
14
2.1 Introduction
2.1
Introduction
Recent studies provide evidence that sizes of galaxies at high redshifts were smaller in
comparison with galaxies of similar mass in the local universe (e.g., Daddi et al. 2005,
Trujillo et al. 2006a,b, Zirm et al. 2007, Toft et al. 2007, van Dokkum et al. 2008a, Franx
et al. 2008, Williams et al. 2010, Toft et al. 2009, Damjanov et al. 2009, Cimatti et al.
2008, Longhetti et al. 2007). These studies pose several questions about the evolution of
properties of galaxies and the build-up of galaxy stellar mass with time. Several physical
processes are proposed to explain the growth of galaxies with time, such as galaxy (major
or minor) mergers (e.g., Khochfar & Silk 2006, 2009, Bell et al. 2006, Naab et al. 2009),
gas accretion in outer regions, and star formation (e.g., Dekel et al. 2009, Elmegreen et al.
2008). However, each of these mechanisms will affect differently the growth of mass and
size of galaxies. For example, major dry mergers could produce descendants with larger
than observed stellar masses for early-type galaxies. Therefore, some authors (e.g., van
Dokkum et al. 2010, Bezanson et al. 2009, Naab et al. 2009, Hopkins et al. 2009) suggest
minor mergers and envelope growth by satellite accretion to be a more likely mechanism
for building up quiescent galaxies. In general, plausible models have to reproduce galaxy
sizes and stellar mass densities seen today and bring the high-redshift galaxies to the local
stellar mass-size relation. Therefore, exploring the observed evolution of galaxy sizes is
essential to constrain these galaxy formation and evolution models.
However, most of the size studies at high redshift were based on photometric redshifts. Although techniques to construct galaxy spectral energy distributions (SEDs) from
multiwavelength observations and photometric redshift measurements are improved over
the past few years, photometric redshifts still have worse uncertainties for star-forming
galaxies due to the lack of a strong 4000Å break. The large uncertainties and possible systematic biases due to the reliance on photometric redshifts can seriously affect the masses
and star formation rate measurements and thus the final results. Spectroscopic observations of high-redshift galaxies and making complete magnitude limited samples require
large amounts of observing time. Nevertheless, the advent of 8-10m class telescopes with
multi-object spectroscopy has brought about much larger high-z spectroscopic samples
than were previously available.
Spectroscopic redshifts are relatively easier to obtain for star-forming galaxies (compare to quiescent galaxies) due to emission lines. Previous results on the size evolution
of this population (with photometric redshifts) are interesting since some of the usual
mechanisms assumed for size growth, e.g., gas-poor (“dry”) mergers do not apply to gasrich starburst galaxies since substantial amounts of gas are required for these galaxies
to undergo significant star formation. Therefore, studies of the structure of star-forming
galaxies with secure redshifts can provide strong constraints on size evolution models.
The actively star-forming galaxies at high redshift consists of two main populations:
relatively unobscured UV-bright galaxies and dusty red starbursts, the most extreme of
which are detected as submillimetre galaxies (SMGs). The UV-bright galaxies are selected to have strong rest-frame UV. In the past few years, many simple photometric
techniques (e.g., “U-dropout”) were designed to select these galaxies at different redshift
ranges (e.g., Steidel et al. 2003, Adelberger et al. 2004).
15
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
The SMGs are among the most massive, luminous, and vigorously star-forming galaxies at high redshift that are heavily obscured by dust (e.g., Hughes et al. 1998, Smail et al.
2002, Chapman et al. 2003, 2005). The physical process driving these highly luminous
galaxies (star formation, active galactic nucleus (AGN), or combination of these two) is
still uncertain. The evolution of SMGs and their relation to the local galaxies are also not
yet understood: for instance, whether or not SMGs are the progenitors of local elliptical
galaxies (e.g., Blain et al. 2004, Swinbank et al. 2006, Tacconi et al. 2008). Their position
on the size-mass plane may therefore provide clues about their relation to other galaxy
populations.
To verify previous results based on photometric redshifts, here we study the mass and
size evolution of a large sample of UV-bright and SMGs in Great Observatories Origin
Deep Survey-North (GOODS-North) with secure spectroscopic redshifts. The structure
of this paper is as follows. In Section 2.2, we review the data. In Section 2.3 and 2.4,
we describe size and mass determinations of galaxies. Our selected subsamples are described in Section 2.5. Finally, in Section 2.6, we present our results and investigate the
size evolution and stellar mass-size relation for our samples. We summarize and discuss
our results in Section 2.7. The cosmological parameters adopted throughout this paper
are Ωm = 0.3, ΩΛ = 0.7, and H0 = 70 km s−1 Mpc−1 .
2.2
Description of Data
The sample of galaxies used here is based on the most complete spectroscopic catalog of
galaxies in the GOODS-North field (Giavalisco et al. 2004)) by Barger et al. (2008). This
catalog gives a compilation of all spectroscopic observations carried out in this field (e.g.,
Cowie et al. 2004, Reddy et al. 2006, Wirth et al. 2004, Cohen 2001, Cohen et al. 2000),
where each galaxy sample was selected in a different way. In addition, Barger et al. (2008)
performed spectroscopic observations for certain subsamples. The catalog includes 2907
sources including stars and is restricted to sources with K s,AB < 24.5 or F850LPAB < 26.
There are 2362 sources with z < 1.6 and 327 sources between z = 1.6 and 3.5. Most
redshifts for galaxies with z > 1.6 come from Reddy et al. (2006).
This catalog (Barger et al. 2008) comprises optical photometric data in the F435W,
F606W, F775W, and F850LP passbands taken from Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS; Giavalisco et al. 2004), and the U-band magnitude
is taken from Capak et al. (2004). The near-infrared K s -band magnitude measured from
WIRCam images from the Canada-France-Hawaii Telescope. Details of near-IR observations, data reduction and generating catalog are described more in Barger et al. (2008).
X-ray soft (0.5 − 2 KeV) and hard (2 − 8 KeV) luminosities are also provided for many
sources in the catalog. In Barger et al. (2008) sources with X-ray luminosities above 1042
ergs s−1 in either soft or hard band defined as AGNs. For a fraction of sources (∼ 36%)
near-ultraviolet (NUV) and far-ultraviolet (FUV) magnitudes from the UV imaging survey performed by GALEX mission were also provided. Note that sources indicated as
stars in the catalog are excluded from our analysis.
16
2.3 Sizes
2.3
2.3.1
Sizes
Size Measurements
Size determination in the observed near-infrared (rest-frame optical at high z) is more robust in tracing the distribution of stellar mass than the observed optical (rest-frame UV
at high z) since the sizes at rest-frame UV can be strongly affected by dust and star formation. Therefore, we use K s -band images from Subaru MOIRCS Deep Survey (MODS)
in the GOODS-North field (Kajisawa et al. 2006, Ouchi et al. 2007). The imaging observations are performed for J and K s bands over ∼ 112 arcmin2 area of the GOODS-N
field with a pixel scale of 0.12 arcsec. We used the images reduced by Bouwens et al.
(2008). The resulting FWHM of the K s images is ∼ 0.500 . The deepest data cover ∼ 28
arcmin2 reaching a 5σ of 25.4 AB mag in K s band while the other regions are ∼ 1.3 mag
shallower. More details of the images and data reduction can be found in Bouwens et al.
(2008).
Sizes of galaxies were estimated by using the GALFIT code (Peng et al. 2002) in
a similar procedure used by Trujillo et al. (2007) and Williams et al. (2010). For each
galaxy, a square postage stamp of 120 pixels (14.4”) around each galaxy was made, and
we use a mask to exclude neighboring galaxies from the fit. A range of Sérsic (1968)
profile models convolved with the point-spread function (PSF) of the image are fitted to
the K s images of galaxies. The convolved models for each object were compared with the
galaxy surface brightness distribution and the best-fit model determined using minimized
χ2 of the fit. The PSF used by GALFIT was taken from the median of the unsaturated
stars over the entire MOIRCS K s images. We perform a test to check the PSF of the
image by measuring sizes of a number of stars in the field listed in the Barger et al.
(2008) catalog. The derived sizes of all the stars are found to be 0.02 pixel (effectively
zero). Therefore, the PSF is a good approximation of a point source. We note that within
our K s -band images, there is a shallower region with seeing of 0.6800 . We followed a
similar procedure with an appropriate PSF (which is made from the median of stars in
this region) to measure sizes of galaxies in this region separately. We also verified that
the derived sizes of the shallower region are reliable by its appropriate PSF.
√
We determine the circularized effective radius re = ae (1 − ), from the half-light
radius along the semimajor axis ae and ellipticity () as output by GALFIT. This removes
the effects of ellipticity. We allowed the Sérsic index n (which measures the shape of the
surface brightness profile of galaxy) to vary between 0.5 and 5 and the effective radius
between 0.01 and 60 pixels (0.001200 and 7.200 ). Initial guesses for the effective radius
re , ellipticity, and position angle were taken from the SExtractor catalog, and magnitude
was taken from the original (Barger et al. 2008) catalog, and we set the Sérsic index to 2
initially.
Our results show that the median Sérsic index measured for all galaxies is 2.0 where
50% of measurements lies between 4.0 and 1.0. For galaxies with stellar masses between
1010 and 1011 M , the median Sérsic index is 2.4 where 50% lies between 4.6 and 1.2.
Due to possibility of color gradients, it is best to use the same rest-frame band for
measuring sizes of galaxies at all redshifts. However, only deep K imaging is available,
17
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
Figure 2.1 – Left panel: the points are the median of the relative difference between the recovered
and input sizes vs. magnitude based on our simulations. Right panel: the same comparison, but
for the relative difference between output and input Sérsic index. The error bars illustrate the 68%
scatter. The random uncertainties of recovered sizes and Sérsic index increase with magnitude.
so there is a possibility of systematic effects with redshift. Franx et al. (2008) show
that such systematic effects are small and will not significantly affect the results. As an
approximation, we corrected sizes to the rest-frame g band using star-forming galaxies
from studies of GOODS-Chandra Deep Field-South (CDF-South; Franx et al. 2008). We
derive the best linear fit to the median of the ratio of sizes in K band and rest-frame g band
as a function of redshift and apply this fit (re,k−band /re,g−band = 0.15z + 0.64) to galaxies
with z . 2 in our sample.
2.3.2
Simulations
To gauge the accuracy of the measured sizes and reliability of our results, we perform a
realistic simulation. About 8500 Sérsic profiles were generated with uniformly distributed
random parameters in the ranges of 19 < KAB < 25, 0.100 < re < 200 , 0.5 < n < 5 and
0 < < 0.8. The mock galaxies were then convolved with the PSF of the image. Finally,
we added these galaxies to 14.4” blank-sky postage stamps randomly taken from our K s band image. The structural parameters of the model galaxies were then measured in a
manner identical to that used for the actual images.
The results of these simulations are shown in Figures 2.1 and 2.2. The left panel of
Figure 2.1 shows that the scatter in the recovered sizes increases with magnitude. The
random uncertainties increase significantly after KAB = 23. However, the systematic
errors are very small (< 5%) even at the faintest magnitudes. Moreover, the simulation
shows that the systematic errors on recovery of the Sérsic index are also very small and
random uncertainties increase above K = 23 (right panel of Figure 2.1). From this result,
we limit the sample studied in this paper to galaxies with K ≤ 23 mag. We note that this
18
2.4 Stellar Mass estimates
limit is for the deeper region in our K-band images. Running a separate simulation for
the shallower region, we find that the derived sizes of galaxies with K < 22.7 mag are
reliable. Hence, we restricted the sample in this region to this slightly brighter magnitude
limit.
We have also explored how the recovery of size depends on the size itself. As shown
in Figure 2.2, the uncertainties in retrieving sizes depend on both magnitude and size.
Systematic offsets at all magnitudes appear to be negligible except for re > 1.8 arcsec
(which corresponds to 14.4 kpc at z ∼ 1) at the faintest magnitudes; however, galaxies
this large and faint have not been seen at any redshift.
The random uncertainties increase with size in all magnitude bins. For objects with
KAB ≤ 20 mag (top panel), the random uncertainties in size recovery are < 5%. However,
for galaxies with 21 < KAB < 22 the increasing of random uncertainties with sizes is
significant. The increase in random uncertainties at larger sizes could be due to decreasing
of surface brightness. However, since we are mainly concerned about the overall sample
properties, the lack of systematic errors is more important.
2.4
Stellar Mass estimates
The stellar masses of galaxies were measured with the Fitting and Assessment of Synthetic Templates (FAST) code (Kriek et al. 2009). All fluxes from Barger et al. (2008)
including four optical bands from ACS, the K s infrared and U band were used to find
the best-fit galaxy template SED to the broadband photometry using a χ2 minimization
procedure. The Bruzual & Charlot (2003) stellar population evolution models with exponentially declining star formation histories (with τ ranging from 107−10 yr) were used to
fit the SEDs. We use the Salpeter (1955) initial mass function (IMF) and solar metallicity
and the extinction AV was allowed to vary between 0 and 3. Redshifts of galaxies were
fixed to their spectroscopic redshift provided by Barger et al. (2008) catalog. Masses were
then shifted by −0.2 dex for consistency with the z ∼ 0 Sloan Digital Sky Survey (SDSS)
masses (which were calculated using a Kroupa 2001 IMF).
2.5
Subsamples
The ability to identify and study distant galaxies has improved dramatically during the last
two decades. Various selection criteria have been designed to select high-redshift galaxies
through their observed colors. In this paper, we use such criteria to select samples of UVbright galaxies in redshift ranges of 0.6 ≤ z ≤ 1.4, 1.4 ≤ z ≤ 2.5 and 2.7 ≤ z ≤ 3.5.
Our sample of Lyman-break galaxies (LBGs; 2.7 ≤ z ≤ 3.5) is taken from Reddy et al.
(2006). Their LBG candidates were originally preselected by the “C”, “D”, and “MD”
criteria which use regions of (Un − G) versus (G − R) color space (Steidel et al. 2003).
Limiting our sample to KAB ≤ 23, we were only able to include five LBGs in our analysis.
19
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
Figure 2.2 – Relative difference between the input and measured sizes of galaxies in our simulations
as a function of size for mock galaxies for galaxies with KAB ≤ 20 mag (top panel), 20 < KAB < 21
(middle panel), and 21 < KAB < 22 (lower panel). The relative errors between the input and
measured sizes of galaxies as a function of sizes depend on the magnitude.
20
2.5 Subsamples
Table 2.1 – Subsamples
Sample
BM/BX
LBG
SMG
sBzK
Redshift
1.4 < z < 2.7
2.7 < z < 3.5
0.5 < z < 3.
1.4 < z < 3.2
log(M∗ /M )
9.8 - 10.8
10.2 - 10.8
10.0 - 11.7
9.8 - 11.7
No. of Sources
41
5
14
70
Notes. Samples of star-forming galaxies studied in this paper.
At z ∼ 2, BM/BX galaxies also are taken from Reddy et al. (2006). The BM/BX criteria (Adelberger et al. 2004, Steidel et al. 2004) were designed to find actively star-forming
galaxies at redshifts 1.4 < z < 2.5 with similar SEDs to the LBGs. The selection criteria
are based on the observed UnGR colors of galaxies. Reddy et al. (2006) provided spectroscopic observations for candidates brighter than RAB = 25.5, photometrically selected
from Steidel et al. (2003, 2004). For this paper, 41 BM/BX galaxies to KAB = 23 are
selected from their sample with spectroscopic redshift z > 1.4.
Galaxies analogous to the LBGs at 0.6 ≤ z ≤ 1.4 (hereafter GALEX/LBGs) are selected with the GALEX/HST (FUV − NUV)AB versus (NUV − F435W)AB color-color diagram. Following the selection criteria used in Barger et al. (2008) and requiring z > 0.6,
we include 105 GALEX/LBGs with KAB ≤ 23.
In addition to the UV-bright galaxies in GOODS-N field, we also study sizes of the
SMGs as a population of star-forming galaxies at high redshifts. The subsample of SMGs
for our studies is drawn from Chapman et al. (2005) and Pope et al. (2006). The catalog of
SMGs provided by Pope et al. (2006) contains 35 candidates from GOODS-N field with
21 secure optical counterparts. Of these, only eight galaxies in our observed images have
spectroscopic redshifts. We further include six SMGs from the Chapman et al. (2005)
HDF-North study. Therefore, our final SMG sample studied here contains 14 sources
spanning 0.5 ≤ z ≤ 3.
Besides these two populations, star-forming galaxies at z > 1.4 can also be identified
using the BzK technique (Daddi et al. 2004). This technique is designed to cull galaxies
from K-selected samples. Star-forming BzK galaxies (sBzK) tend to be more massive and
have higher reddening than UV-selected galaxies. With this method, 70 sBzK galaxies at
z > 1.4 and KAB ≤ 23 are selected using the criteria (z − K) − (B − z) > −0.2. We further
use this sample to compare properties of star-forming galaxy populations at high redshifts.
The sBzK selection criteria can identify ∼ 90% of our BM/BX galaxies. The large overlap
is not surprising since both our UV-selected and sBzK samples consist of mostly massive
galaxies (due to the K magnitude limit). Table 2.1 lists samples of star-forming galaxies
used in this paper.
21
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
2.6
2.6.1
Results
Size Evolution
In Figure 2.3, we show the size distributions for UV-bright galaxies between 10 < log(M∗ /M ) <
11. The blue histogram shows the measured half-light radii of GALEX/LBGs at z ∼ 1
while the distribution of sizes measured for BM/BX galaxies (z ∼ 2) is shown as a green
histogram. It can be seen from this plot that UV-bright galaxies at z ∼ 2 are smaller compared to similar galaxies at z ∼ 1. Specifically, the median half-light radius of BM/BX
galaxies in this mass range is 2.68 ± 0.19 kpc significantly smaller than the median effective radii of GALEX/LBGs (4.42 ± 0.52 kpc). This means that sizes of UV-bright
galaxies evolve by a median factor of 0.60 ± 0.08 between z ∼ 2 and z ∼ 1. It is harder
to measure the evolution for z ∼ 3 to z ∼ 2, as we have four LBGs within mass range of
10 < log(M∗ /M ) < 11 at z ∼ 3 in our sample. The median half-light radius of these four
massive galaxies is 2.22 ± 0.61 kpc, 0.82 ± 0.23 smaller than z ∼ 2 BM/BX galaxies. We
perform a power-law fit on the size evolution and find re ∝ (1 + z)−1.11±0.13 over the range
0.6 . z . 3.5.
The size-redshift relation for star-forming galaxies with spectroscopic redshifts in the
GOODS-North field is shown in Figure 2.4. Galaxies are split into the four different
stellar mass bins shown in the figure. In each panel, the gray small symbols are normal
star-forming galaxies with spectroscopic redshifts selected to have specific star formation
rates log sSFR > −10. Color symbols represent our samples of UV-bright galaxies and
SMGs. LBGs (2.7 < z < 3.5) are shown as dark-green triangles, and BM/BX galaxies
(1.4 < z < 2.7) are plotted as green squares. GALEX/LBGs at relatively lower redshifts
(0.6 < z < 1.4) are plotted in different panels as blue stars. The black symbols at z ∼ 0
are star-forming galaxies from Guo et al. (2009) from SDSS.
As Figure 2.4 shows, sizes of UV-bright galaxies at a fixed stellar mass increase
toward lower redshifts. There is also a trend that the size evolution maybe stronger
for the most massive galaxies. For example, UV-bright galaxies with stellar masses
9 < log(M∗ /M ) < 10 evolve by a median factor of approximately 1.15 ± 0.25 from z ∼ 2
to z ∼ 0.8. However, galaxies with masses 10 < log(M∗ /M ) < 10.5 grow by a median
factor of approximately 1.82±0.25. At higher stellar mass bin (10.5 < log(M∗ /M ) < 11),
this evolution is even stronger: a factor of 2.05 ± 1.26 over the same redshift range. However, selection effects may influence this trend (especially in the low-mass bin) and more
complete samples are needed.
SMGs are also shown as pink diamonds in Figure 2.4; they are discussed further in
Section 2.6.4. Galaxies which have X-ray luminosities > 1042 ergs s−1 (i.e., potential
AGN hosts) are marked with open circles. These galaxies have sizes similar to the others.
Since AGN is point-like, one would expect galaxies with AGN emission to have smaller
half-light radii. Their “normal” rest-frame optical sizes are thus perhaps not strongly
influenced. Nonetheless, due to possible effects on the size and mass estimates, X-raydetected galaxies should be considered low-confidence points.
22
2.6 Results
Figure 2.3 – Size distribution of UV-bright galaxies with stellar mass 10 < log(M∗ /M ) < 11 at
z ∼ 1 (blue histogram) and z ∼ 2 (green histogram). The half-light radii of UV-bright galaxies
(GALEX(LBGs)) at z ∼ 1 are larger than BM/BX galaxies at z ∼ 2.
2.6.2
Stellar Mass-Size Relation
We now investigate how mass-size distribution of the UV-bright galaxies compares to
other galaxy populations. We further check if the relation between stellar mass and size
of these galaxies exists to high redshift.
The stellar mass-size distributions of our samples are shown in Figure 2.5. We have
divided our sample into three redshift bins: 0.5 < z < 1.5, 1.5 < z < 2.5, and 2.5 <
z < 3.5. UV-bright galaxies are color coded in the same way as in Figure 2.4. Solid and
dotted lines in each panel show the mass-size relation from Shen et al. (2003) for starforming galaxies and early-type galaxies at z ∼ 0, respectively. The gray symbols are the
K-selected sample of galaxies in CDF-South with stellar masses > 109.8 M (Franx et al.
2008). Comparing our results with the galaxies from CDF-S allows us to see where our
galaxies lie relative to a purely mass-selected sample. Brown solid lines in the middle of
each panel show the median effective radii in narrow mass bins for all galaxies in CDF-S.
As can be seen, at z ∼ 1 and z ∼ 2, UV-bright galaxies have larger effective radii compared
to all galaxies at a given stellar mass. For galaxies between 1010 and 1011 M , the median
sizes differ by a factor of 1.89 ± 0.23 and 1.12 ± 0.09 at z ∼ 1 and 2, respectively. As the
spectroscopic sample contains only four UV-bright galaxies in this mass range at z ∼ 3,
the difference with CDF-S is not well constrained at this redshift (1.27 ± 0.36).
We further investigate how the size-mass distribution of GOODS-N UV-bright galaxies compares to that of UV-bright galaxies in CDF-S. This would help to verify if the
23
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
Figure 2.4 – Evolution of sizes of galaxies as a function of redshift. Each panel shows the size evolution for a narrow stellar mass bin. The gray symbols are star-forming galaxies with spectroscopic
redshifts in GOODS-N field. Blue stars are GALEX/LBGs (z ∼ 1) while the green squares and
green triangles represent BM/BX galaxies (z ∼ 2) and LBGs (z ∼ 3), respectively. SMGs are also
shown as pink diamonds. Galaxies with X-ray luminosities more than 1042 ergs s−1 are marked by
open circles. Black symbols at z ∼ 0 are SDSS star-forming galaxies from Guo et al. (2009). As
this plot illustrates, the half light radii of UV-bright galaxies evolve with redshift and this evolution
is faster for high-mass galaxies.
24
2.6 Results
previously reported size-mass relation for a large photometric sample (Franx et al. 2008)
is consistent with our spectroscopic sample. We define analogs of the z ∼ 1, 2, and 3 LBGs
in CDF-S by their optical colors and magnitudes. Specifically, we selected the analogs of
the z ∼ 1 GALEX/LBGs by requiring (B − V) < 0.6 and R ≤ 23.8. This selection is based
on the locus of the GOODS-N GALEX/LBGs in this color-magnitude plane. The analogs
of BM/BX galaxies in CDF-S are similarly selected with R < 25.1 and (B − V) < 0.8 and
z phot = 1.5 − 2.5. We note that the R-band magnitude in both surveys is estimated by the
average values of V- and I-band magnitudes. We verified that the spectroscopic samples
are effectively selected by these criteria. In order to identify analogs of UV-bright objects
in CDF-S at z ∼ 2.5 − 3.5, we find the location of LBGs in GOODS-N on the color-color
(B − V) versus (V − I) diagram and apply the following criteria to the CDF-S galaxies: (1)
0.5 < (B− V) < 1.2 for (V − I) < 0.35 ; (2) (B− V) > 3 × (V − I) + 0.5 and (B− V) < 1.2 for
0.35 < (V − I) < 0.5. We note that these selection criteria do not impose a “U-drop out”
criteria, but do select galaxies with similar brightness and UV slope as the usual LBG
methods.
The comparison of size-mass distributions for UV-bright galaxies from both fields is
shown in Figure 2.6. In each panel, the color symbols are the median log effective radii
of UV-bright galaxies in narrow mass bins, with the blue and green symbols representing
UV-bright galaxies in GOODS-N and the brown symbols are the ones in CDF-S. The
error bars show the 1σ dispersion. UV-bright samples from both fields follow consistent
size-mass relation, further confirming that UV-bright galaxies are on average larger than
overall galaxies at a fixed stellar mass. We note that at high redshift (z ∼ 2.5 − 3.5) the
comparison is weak because of the limited number LBGs in GOODS-N.
The UV-bright galaxies show a weak stellar mass-size relation at z = 1 and z = 2 in
Figure 2.5. To quantify this relation, we fitted a power-law function of the form re ∝ M α
to the individual UV-bright galaxies in each redshift bin. The fitting results are plotted as
color dashed-dotted lines in Figure 2.6. At z ∼ 1, the size of GALEX/LBGs in GOODSN scales with stellar mass as re ∝ M 0.19±0.05 and the BM/BX galaxies at z ∼ 2 have
re ∝ M 0.30±0.06 . The uncertainties were estimated using bootstrap resampling. The results
are comparable to the relation for late-type galaxies at z ∼ 0 from Shen et al. (2003). They
found re ∝ M 0.15 for low-mass (log(M) < 10.6) late-type galaxies and steeper relation for
high-mass late-type galaxies (re ∝ M 0.4 ). In the highest redshift bin (z ∼ 3), we use
UV-bright galaxies from CDF-S to find the best fit (α = 0.32 ± 0.06). Table 2.2 lists the
best-fit power-law parameter to the mass-size relation of UV-bright galaxies. The slopes
of the mass-size relation at different redshift bins are consistent and there is no significant
evolution. Our results confirm the persistence of the size-mass relation for star-forming
galaxies up to high redshift.
It is worth checking whether or not other star-forming populations at high redshift
have the same size-mass relation. Therefore, we compare star-forming BzK galaxies
(sBzK) with BM/BX galaxies. The size distribution as a function of stellar mass is shown
in Figure 2.7 with the sBzK galaxies plotted as gray filled circles. The medians of log effective radii of sBzK galaxies are overplotted as red squares. BM/BX galaxies and SMGs
are marked with the green and pink circles, respectively, and the green dashed-dotted line
shows the mass-size relation for BM/BX galaxies. As one can see, the mass-size relation
25
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
Figure 2.5 – Stellar mass-size distribution for UV-bright galaxies in different redshift bins compared
to the galaxies from CDF-South (Franx et al. 2008) (gray dots). The color symbols represented
here are the same as Figure 2.4. The solid and dotted black lines are the size-mass relations for starforming and quiescent galaxies, respectively, at z ∼ 0 from Shen et al. (2003). The solid brown lines
show the median sizes in narrow mass bins for all galaxies from CDF-S. The UV bright galaxies
are in general larger than normal field galaxies at the same mass.
Figure 2.6 – Comparison of the stellar mass-size relation for the UV-bright galaxies from GOODSN field and CDF-South in three redshift bins. The black solid lines are the size-mass relation for
star-forming galaxies at z ∼ 0 from Shen et al. (2003). The color symbols are median of UV-bright
galaxies in narrow mass bins and the error bars show 1σ (68%) dispersion. The dashed-dotted lines
are the best power-law fits using re ∝ M α to the individual UV-bright galaxies. The dotted lines
are the median sizes in narrow mass bins for all galaxies from CDF-S (Same as Figure 2.5). This
plot shows that the derived half-light radii of UV-bright galaxies from both fields are in place and
agreement with each other up to z ∼ 3.
26
2.6 Results
Table 2.2 – Best Fits Power-law Parameter for the Stellar
Mass-Size Relation
Sample
GALEX/LBG
BM/BX
CDFs-UV Bright
sBzK
Redshift
0.6 < z < 1.4
1.4 < z < 2.7
2.5 < z < 3.5
1.4 < z < 3.2
α
0.19 ± 0.05
0.30 ± 0.06
0.32 ± 0.06
0.31 ± 0.09
Notes. Power-law parameter α is defined as re ∝ M α .
Figure 2.7 – Stellar mass-size relation for star-forming sBzK galaxies (gray circles). The BM/BX
galaxies and SMGs are marked with green and pink circles, respectively. The red squares are the
median for the mass-size relation of sBzK sample with 1σ dispersion. The green dashed-dotted line
is the best fit to the BM/BX galaxies. The sBzK galaxies have a similar size-mass relation to the
BM/BX galaxies. The solid line shows the mass-size relation for star-forming galaxies at z ∼ 0
from Shen et al. (2003).
27
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
Figure 2.8 – Left panel: the correlation between color (V606 − z850 ) and surface density for galaxies
in the redshift range of 0.5 < z < 1.5 and stellar masses 1010 < M/M < 1011 in GOODS-N
field. The blue stars are GALEX(LBGs) from GOODS-N and the brown circles are from CDF-S.
The gray symbols are all galaxies from CDFS and the black triangles are galaxies from GOODS-N.
Right panel: the color (z850 − K) vs. surface density for galaxies at 1.5 < z < 2.5, as the green
squares are the BM/BX galaxies from GOODS-N and the brown circles are pseudo-BM/BX from
CDF-S. The plots indicate that blue galaxies having lower surface density.
for sBzK galaxies is comparable to the one for BM/BX galaxies. The average offset of
median half-light radii of sBzK galaxies to the BM/BX mass-size relation is 0.037 dex.
The effective radii of sBzK galaxies scale with stellar mass as re ∝ M 0.31±0.09 close to the
size-mass relation for UV-bright galaxies. This similarity could be due to the significant
overlap between the UV-selected galaxies and sBzK galaxies (e.g., Reddy et al. 2005).
We note that stellar masses can have significant uncertainties depending on the methods
used to calculate them. We verify that by using the stellar mass estimates from Reddy
et al. (2006) for UV-bright galaxies, the size-mass distribution of these galaxies covers
the same region in the size-mass plane (see, e.g., the middle panel of Figure 2.5). Hence,
this shows that our results are robust against using different estimates of stellar masses.
2.6.3
Color-Surface Density
One of the surprising results of Franx et al. (2008) was the tight correlation between
stellar mass surface density (M∗ /re2 ) and color of galaxies to z ∼ 3. They showed that
bluer galaxies have lower surface densities than red quiescent ones. They indicated that
the color of galaxies correlates more fundamentally with the stellar mass surface density
than the mass.
We show the tight relation between color and stellar mass surface density for both starforming and quiescent galaxies with M ∼ 1010 − 1011 in Figure 2.8. In the left panel, the
28
2.6 Results
Figure 2.9 – Top panel: histograms show the distribution of sizes of SMGs (solid line) and BM/BX
galaxies (dotted lines). The gray region indicates apparent effective radii below 0.1”(∼ 1 kpc at
z ∼ 2) which size measurements have large uncertainties. Lower panel: cumulative distribution
function for SMGs (pink diamonds) and BM/BX galaxies (green squares). As the plot shows, the
distributions of half-light radii of these two populations are comparable with SMGs being slightly
larger.
observed color (V606 − z850 ) is plotted versus the stellar mass surface density for galaxies
at redshift ∼ 1. The black and gray symbols are galaxies from GOODS-N and CDF-S
fields, respectively. The blue stars and brown circles indicate the GALEX (LBGs) and
their analogs from CDF-S, respectively. In the right panel, the relation between observed
(z850 -K) and surface density for galaxies at higher redshift ∼ 2 is illustrated , with BM/BX
galaxies in GOODS-N shown by green squares and their analogs in CDF-S as brown
circles. As can be seen in this figure, the blue star-forming galaxies have lower surface
density than red galaxies at both z ∼ 1 and z ∼ 2, though the correlation between color and
surface density is more tight at z ∼ 1 than z ∼ 2. In general, using sample of galaxies with
spectroscopic redshifts confirms that the color of galaxies tightly correlates with surface
density and this relation holds out to high redshifts.
29
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
2.6.4
Sizes of Submillimeter Galaxies
Since GOODS-N includes 14 SMGs with redshifts, we compare their masses and sizes to
the UV-selected galaxies at z ∼ 2. As Figure 2.4 illustrates, the optical rest-frame sizes of
the SMGs (pink diamonds) and UV-selected galaxies of similar mass are comparable. The
median half-light radius of all SMGs is 2.90 ± 0.45 kpc which is in good agreement with
the median optical rest-frame sizes of the BM/BX galaxies over the whole mass range
(2.68 ± 0.25 kpc). The median effective radius of SMGs with stellar masses of 1010 -1011
is 2.65 ± 0.56 which is similar to the BM/BX of at the same mass range (2.68 ± 0.19). The
errors are computed using bootstrap resampling.
We further compare the size distributions of SMGs and BM/BX galaxies in Figure
2.9. In the top panel, the histograms show the size distribution of BM/BX galaxies and
SMGs. In the bottom panel, the normalized cumulative distribution functions are shown
for both samples. As this plot shows, the size distributions of SMGs are comparable with
z ∼ 2 UV-bright galaxies and the SMGs follow the same size distribution as BM/BX
galaxies in the optical rest-frame with SMGs being slightly larger. According to a K-S
test, the probability that two distributions being the same is 72%, suggesting no significant
difference between the rest-frame optical sizes of the SMGs and UV-bright galaxies.
2.7
2.7.1
Discussion
The growth of star-forming galaxies
We study the size evolution of galaxies with spectroscopic redshifts between z ∼ 0.5
and 3.5. Our results are summarized in Figure 2.10. As this plot illustrates, at each
epoch, the median sizes of UV-bright galaxies (color squares) with stellar masses 10 <
log(M∗ /M ) < 11 are larger (by a median factor of 0.45 ± 0.09) than quiescent galaxies
in a similar mass range selected from CDF-S (red circles). The red triangle is the median
sizes of quiescent galaxies studied in (van Dokkum et al. 2008, VD08 hearafter) with a
median stellar mass of 1.7 × 1011 M and median redshift of 2.3. Table 2.3 lists the median
half-light radii for UV-bright and quiescent galaxies seen in Figure 2.10. The growth of
UV-bright galaxies with time is also illustrated in this figure. The dashed line shows that
UV-bright galaxies scaled up their sizes toward lower redshifts as (1 + z)−1.11±0.13 .
Previous studies (Franx et al. 2008, Kauffmann et al. 2003) have reported that there
is a correlation between color and stellar mass surface density of galaxies at both low
and high redshifts. However, the results based on photometric redshifts can be uncertain
especially for star-forming galaxies. By means of our large sample of galaxies with secure
redshifts, we have confirmed that the tight correlation between color and stellar mass
surface density of galaxies that holds out to high redshifts; as the stellar mass densities of
blue star-forming galaxies are smaller than those of red quiescent ones. This verifies that
the galaxies with higher specific star formation rate are larger than the ones with lower
specific star formation rates.
We have also explored the stellar mass-size distribution for galaxies in our sample. We
have confirmed that there is a relation between stellar mass and size for UV-bright galaxies
30
2.7 Discussion
Figure 2.10 – Median sizes of UV-bright galaxies (squares) as a function of redshifts for galaxies
with stellar masses 1010 < M/M < 1011 in GOODS-N field. The red filled circles are quiescent
galaxies from CDF-S study with similar mass range and the red triangle is the quiescent sample
from van Dokkum et al. (2008) with median stellar masses of 1.7 × 1011 M . The dashed line shows
the best-fitting size evolution to the UV-bright galaxies (re ∝ (1 + z)−1.11±0.13 ). The plot indicates
that the UV-selected galaxies are larger than quiescent galaxies and their sizes evolve with redshift.
31
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
at 0.5 < z < 3.5. The relations are consistent for both spectroscopic and photometric
redshift samples. Our results verify that there is no significant evolution of the slope of
the size-mass relation to redshift ∼ 3.5. The evolution of the relation from z = 1 to
z = 0 is not well established, as it is not straight forward to select LBGs at z ∼ 0. Some
authors find evolution (e.g., Franx et al. 2008, Williams et al. 2010) in the stellar mass-size
relation; however, Barden et al. (2005) have reported that the stellar mass-size relation for
disk galaxies remains constant from z ∼ 1 to the present. Selection effects likely play a
role. Comparing to the theoretical work, the size evolution predicted by Somerville et al.
(2008) is somewhat stronger than the evolution we measured here.
Star-forming galaxies at high redshifts can be identified by means of different methods of sample selection and can be assigned as different populations of galaxies (e.g.,
submillimeter or sBzK) and therefore studied separately. However, many of these galaxy
populations may overlap, hence it is worth checking out if they have comparable properties. We, therefore, compare sizes of UV-bright galaxies to other types of star-forming
galaxy populations at high redshift, i.e., sBzK galaxies and SMGs. We show that these
two populations have comparable sizes to the UV-bright galaxies. This suggests that, in
general, star-forming galaxies have larger sizes than quiescent ones without regard to their
type. However, sample selection might alter the results. We return to this possibility later,
in Section 2.7.3.
2.7.2
Comparison to previous work
The strong growth of both star-forming and quiescent galaxies has been shown by several
authors (Trujillo et al. 2006b, Franx et al. 2008, Williams et al. 2010, Toft et al. 2007).
The size growth of star-forming galaxies studied here going as (1+z)α , where α = −1.11±
0.13, agrees well compared to previous studies where the size evolves with α ∼ −1. For
example, Bouwens et al. (2006) found α = −1.1 ± 0.3 for a sample of luminosity-selected
dropout galaxies between z ∼ 6 and z ∼ 2.5, while Dahlen et al. (2007) found α =
−1.10 ± 0.07 for luminosity-selected disk galaxies over the range z ∼ 1.1-2.2. Williams
et al. (2010) also found a similar slope for star-forming galaxies in UDS at z ∼ 0.5-2.
The similarity between sizes of UV-bright galaxies and star-forming BzK galaxies is
also shown in our study. The two populations are also compared by Overzier et al. (2010).
They showed that rest-frame optical sizes of sBzK galaxies are somewhat larger than UVselected galaxies. Since BzK galaxies are K-selected and thus tend to represent massive
galaxies, it is not surprising that they appear larger. Hence, the sizes must be corrected
for differing stellar masses for an accurate comparison to be made.
Our results also show that the SMGs have a median half-light radius of 2.90 ± 0.45
kpc comparable to the rest-frame optical sizes of the BM/BX galaxies. The result is in
agreement with a recent study by Swinbank et al. (2010) where they use deep HST I and
H-band imaging and show that the rest-frame optical sizes of the SMGs and UV-bright
galaxies in GOODS-N are comparable. The typical half-light radius of the SMGs in the
H-band (rest-frame optical) measured by Swinbank et al. (2010) is 2.8 ± 0.4 which is
consistent with our measurements (see also Targett et al. 2010 for more comparison.).
Almaini et al. (2005) also compared sizes of SMGs with LBGs at rest-frame optical and
32
2.7 Discussion
Table 2.3 – Median Sizes of Different Samples
Sample
GALEX/LBG
BM/BX
LBG
CDFS
CDFS
CDFS
Quiescent(CDFS)
Quiescent(CDFS)
Quiescent(VD08)
SMG
Redshift
0.6 < z < 1.4
1.4 < z < 2.7
2.7 < z < 3.5
0.5 < z < 1.5
1.5 < z < 2.5
2.5 < z < 3.5
0.5 < z < 1.5
1.5 < z < 2
2 < z < 2.5
0.5 < z < 3.
Median Size (kpc)
4.42 ± 0.52
2.68 ± 0.19
2.22 ± 0.61
2.33 ± 0.1
2.40 ± 0.13
1.73 ± 0.18
1.32 ± 0.07
1.12 ± 0.32
0.9 ± 0.21
2.90 ± 0.45
Median(log(M∗ /M )
10.2 ± 0.3
10.4 ± 0.2
10.6 ± 0.2
10.4 ± 0.3
10.4 ± 0.3
10.4 ± 0.3
10.5 ± 0.3
10.7 ± 0.2
11.23
10.8 ± 0.5
Notes. The median sizes are for galaxies with stellar masses between 1010 and 1011 M .
This mass limit is not applied to the quiescent (van Dokkum et al. 2008, , VD08) and SMG
galaxies. The CDFS samples contain both star-forming and quiescent galaxies at the same
mass range in CDF-S.
found no clear difference between sizes of the SMGs and LBGs. It is worth noting that
SMGs have larger median stellar masses compared to BM/BX galaxies (also mentioned in
Swinbank et al. 2010). This suggests higher stellar mass densities for SMGs compared to
UV bright galaxies. However, the similarity in sizes between these two galaxy populations
at high z does not by itself allow conclusive connections to be drawn between the two
populations. The SMGs that are faint or lacking emission lines could be missing from our
spectroscopic sample and they may have dramatically different mass or size properties.
Therefore, selection effect could bias these results. Spectroscopic observation in nearIR might help to solve this problem; e.g., Kriek et al. (2009a) find a median size of
2.8 kpc for a small sample of near-IR spectroscopically confirmed star-forming galaxies
at z ∼ 2.3. Indeed, our measured size evolution is consistent with their spectroscopic
sample; however, near-IR spectroscopy over a large redshift range is needed to definitively
quantify the size evolution.
2.7.3
Caveats
With this large spectroscopic sample of high-redshift galaxies, we have removed an important source of uncertainty in the stellar mass-size relation and verified the results from
larger samples based on photometric redshifts. However, the spectroscopic catalog we
used in this study consists of many different spectroscopic surveys which made it inhomogeneous. Galaxies in this catalog are mostly relatively unobscured star-forming
galaxies with emission lines, comparing these to quiescent galaxies can still be a problem
because spectroscopy of high-redshift red galaxies is difficult. Therefore, using a larger
and homogeneous sample of high-redshift galaxies with secure redshift will allow greatly
33
Chapter 2 – The Evolution of the Mass-Size Relation to z = 3.5 in GOODS-N Field
improved constraints on their evolution. New ground and space-based IR multi-object
spectrographs (WFC3 grism, MMIRS, MOSFIRE) will allow investigations of more complete samples of galaxies and study the correlation between galaxy properties at higher
redshifts. Dust-obscured starbursts are also likely to be missed in our UV-bright sample,
hence NIR spectroscopy will also permit studies of this important population.
2.8
Summary
We have performed the first size evolution study of UV-bright galaxies with secure redshifts in the GOODS-North field. We derive half-light radii of galaxies at a wide range
of redshifts (up to z ∼ 3.5). Using sample of galaxies with secure redshifts, we have
quantified the size evolution of galaxies without the potential uncertainty of photometric
redshifts and confirm the previous studies that galaxies of similar mass were generally
smaller at past and their sizes evolve with redshift. Specifically, we find that:
• UV-bright galaxies evolve strongly as (1 + z)−1.11±0.13 confirming previous studies
based on photometric redshifts (e.g., Trujillo et al. 2006b, 2007, Franx et al. 2008,
Williams et al. 2010).
• UV-bright galaxies are significantly larger than quiescent galaxies. At the same
mass, the median difference is 0.45 ± 0.09 dex.
• The LBG, BM/BX, and GALEX/LBG samples show smooth evolution with redshift, indicating that these techniques indeed select similar UV-bright galaxies at
different redshifts.
• The SMGs have half-light radii similar to UV-bright galaxies of the same mass.
2.9
Acknowledgments
We thank anonymous referee for helpful comments and suggestions. We thank Rychard
Bouwens for providing us K-band images. M.M. is supported by the Marie Curie Initial
Training Network ELIXIR (Early unIverse eXploration with nIRspec), grant agreemnet
PITN-GA-2008-214227 (form the European Commission). R.J.W. acknowledges support
from the Nederlandse Onderzoekschool voor Astronomie (NOVA) and NSF grant AST0707417.
34
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37
3
The Evolution of Mass-Size Relation
for Lyman Break Galaxies From z = 1
to z = 7
Moein Mosleh, Rik J. Williams, Marijn Franx, Valentino Gonzalez, Rychard J.
Bouwens, Pascal Oesch, Ivo Labbe, Garth D. Illingworth, and Michele Trenti
The Astrophysical Journal Letters, 2012, 756:L12
39
Chapter 3 – The Evolution of Mass-size Relation From z = 1 to z = 7
Abstract
For the first time, we study the evolution of the stellar mass-size relation for star-forming galaxies
from z ∼ 4 to z ∼ 7 from Hubble-WFC3/IR camera observations of the HUDF and Early Release
Science field. The sizes are measured by determining the best-fit model to galaxy images in the restframe 2100 Å with the stellar masses estimated from spectral energy distribution fitting to rest-frame
optical (from Spitzer/IRAC) and UV fluxes. We show that the stellar mass-size relation of Lyman
break galaxies (LBGs) persists, at least to z ∼ 5, and the median size of LBGs at a given stellar mass
increases toward lower redshifts. For galaxies with stellar masses of 9.5 < log(M∗ /M ) < 10.4 sizes
evolve as (1 + z)−1.20±0.11 . This evolution is very similar for galaxies with lower stellar masses of
8.6 < log(M∗ /M ) < 9.5 which is re ∝ (1 + z)−1.18±0.10 , in agreement with simple theoretical galaxy
formation models at high z. Our results are consistent with previous measurements of the LBGs
mass-size relation at lower redshifts (z ∼ 1 − 3).
40
3.1 Introduction
3.1
Introduction
The size of a galaxy is a fundamental and important parameter to measure. Over the
past decade, observations have revealed that sizes of galaxies at a given stellar mass were
smaller at higher redshifts and change significantly with redshift. It has been shown that
the sizes of galaxies correlate with their stellar masses and that this correlation exists at
least up to z ∼ 3 (e.g., Franx et al. 2008, Williams et al. 2010, Mosleh et al. 2011, Law
et al. 2012).
There are many proposed scenarios to explain the physical processes of galaxy assembly that plausibly reproduce the observable stellar mass and size of galaxies at different
redshifts (e.g., galaxy minor or major mergers; Khochfar & Silk 2006, 2009, Bell et al.
2006, Naab et al. 2009) or gas accretion in outer regions and star formation (Dekel et al.
2009, Elmegreen et al. 2008). Accurate measurements of both stellar masses and sizes of
galaxies over a wide redshift range are fundamentally important to constrain these galaxy
formation models.
To extend the mass-size relation of galaxies to the highest redshifts, we exploit the
Lyman break galaxies (LBGs) which are star-forming galaxies with strong rest-frame UV
emission and could be selected by photometric dropout techniques (e.g., Steidel et al.
2003, Adelberger et al. 2004). These galaxies can be identified out to very high redshifts
(e.g., z ∼ 8; Oesch et al. 2012, Yan et al. 2011) and thus provide insight into the early
evolution of the mass-size relation.
Morphological studies of LBGs (z ∼ 2 − 6) in rest-frame UV have shown that these
galaxies are mostly compact sources however, multiple core LBGs have also been found
(e.g., Ravindranath et al. 2006, Law et al. 2007, Conselice & Arnold 2009). Analyzing
their size and structure could help to interpret the dominant mechanism for galaxy growth.
The new Wide Field Camera 3 (WFC3) onboard the Hubble Space Telescope (HST) can
provide sizes of high-z galaxies in longer rest-frame wavelengths than Advanced Camera
for Survey (ACS).
Size studies of galaxies at redshifts z > 4 using profile fitting techniques are rare
(Oesch et al. 2010). Here for the first time, we investigate the mass-size relation of
dropout galaxies up to the very early stages of galaxy formation, using the advantages
of wide-area HST surveys and high spatial resolution of WFC3. We measure the sizes of
LBGs at approximately the same rest-frame wavelength at different redshifts, minimizing
the effects of morphological K-correction. We utilize observations of both Hubble Ultra
Deep Field (HUDF) and the deep wide-area Early Release Science (ERS) field to study
the mass-size relation of the largest sample of LBGs at z ∼ 4 − 7 so far. The cosmological
parameters adopted throughout this Letter are Ωm = 0.3, ΩΛ = 0.7, and H0 = 70 km s−1
M pc−1 .
41
Chapter 3 – The Evolution of Mass-size Relation From z = 1 to z = 7
3.2
Description of Data
The sample of dropout sources at z ∼ 4 − 7 used here is based on recent HST-WFC3/IR
observations over the HUDF and ERS field (see Bouwens et al. 2011, Oesch et al. 2010b,
González et al. 2010). Our sample of dropout galaxies is taken from Bouwens et al.
(2011) and González et al. (2011). Their candidates are selected by utilizing color criteria
(Lyman break technique) for selecting B-, V-, i- and z- dropouts similar to those used
in Oesch et al. (2010b) and Bouwens et al. (2007, 2011). Their sample consists of 679
objects at z ∼ 4 − 6 in ERS field and 345 dropouts at z ∼ 4 − 7 in HUDF.
For all candidate galaxies in this Letter we use the stellar masses measured by González
et al. (2011). These authors used FAST (Kriek et al. 2009) to fit template galaxy spectral energy distributions to photometry in ACS, WFC3/IR, and IRAC [3.6] and [4.5] filters. They used Bruzual & Charlot (2003) stellar population evolution models with constant star formation histories and assumed a Salpeter (1955) initial mass function (IMF;
0.1 − 100M ) and 0.2 Z solar metallicity. Reliable deblended IRAC fluxes and photometry in different bands (with different point-spread functions, PSFs) were obtained by
using a source-fitting algorithm described in Labbé et al. (2006) (see also González et al.
2010).
The photometric deblending for the IRAC imaging does not properly work for objects
in crowded regions due to the large PSF of IRAC bands; due to this, the number of sources
with reliable mass estimates is reduced to 60% (see also González et al. 2011). The stellar
masses are corrected to a Kroupa (2001) IMF by a reduction of 0.2 dex (see Marchesini
et al. 2009). These are consistent with the Sloan Digital Sky Survey (SDSS) masses.
The near-IR images used in this study are taken from the full two-year WFC3/IR
HUDF (Y105 , J125 , H160 ;(Bouwens et al. 2011, Oesch et al. 2010b) ) and ERS (Y098 , J125 ,
H160 ; (Bouwens et al. 2011)) data. The data set covers ∼ 4.7 arcmin2 in the HUDF and
∼ 40 arcmin2 in the ERS (in GOODS-South) field with a pixel scale of 0.0600 and a PSF
FWHM of ∼ 0.1700 in the H-band. We also use very deep images of the HUDF field
obtained with the ACS (Beckwith et al. 2006) and deep GOODS ACS/WFC data over the
GOODS field (Giavalisco et al. 2004) with a pixel scale of 0.0300 and a PSF FWHM of
∼ 0.1000 . The reduction of these data is described in Bouwens et al. (2011), and references
there in.
As explained in the next section, we use sizes of objects in the band closest to the
rest-frame 2100Å. Therefore, in addition to reliable stellar mass cut, we restrict our size
measurements to objects with sufficient signal-to-noise ratio (S/N) in their size measurement band. Hence, we use H160 < 28.5 in HUDF and H160 < 26.2 AB mag in ERS field
(corresponding to 10σ in 0.500 apertures) for i-dropouts and z-dropouts, J125 < 28.5 in
HUDF and J125 < 26.5 AB mag in ERS for V-dropouts and Y105 < 28.3 in HUDF and
Y098 < 26.4 AB mag in ERS for B-dropouts. Our simulations (see Section 3.3) show that
systematic uncertainties on size estimates are small up to these magnitudes. Moreover,
objects with poor S/N (< 5σ) are not included in our analysis. Thus, the final sample
consists of 156 B-dropouts (z ∼ 4), 45 V-dropouts (z ∼ 5), 13 i-dropouts (z ∼ 6), and 4
z-dropouts (z ∼ 7).
42
3.3 Sizes
Figure 3.1 – From left to right, H-band postage stamps (600 × 600 ), best-fit models from GALFIT,
residual images and mask maps are shown for a z-dropout candidate (top row), and an i-dropout
candidate (bottom row). The quality of the fits can be seen from the residual images.
3.3
Sizes
Our size measurements are performed in a similar way as in Mosleh et al. (2011). PSFconvolved Sérsic models are fit to all galaxies using the GALFIT version 3 package (Peng
et al. 2010). We measure sizes in filters described in the previous section.
GALFIT requires an accurate PSF of the image to convolve the Sérsic profile models
in order to find the best (χ2 minimized) fit. For the HUDF WFC3/IR images we use a PSF
created using TinyTim (Krist 1995). Although, we prefer using empirically determined
PSFs (from stars), in the HUDF there are not enough stars to create a sufficiently lownoise PSF for deconvolution. We note that our test shows that sizes measured using
non-saturated star as a PSF give results which are consistent with those based on TinyTim
created PSFs. For the ACS images in the HUDF we use non-saturated stars in the field
to make a median-stacked PSF. In the ERS field, we use a median-stacked PSF using
non-saturated stars in the field for all optical and near-IR bands (ACS and WFC3/IR).
GALFIT measures the half-light radius along the semimajor axis, a, and the axis
ratio, b/a,
√ of each galaxy. We determine the circularized effective radius of the galaxies
(re = a b/a) to remove the effects of ellipticity. We fix the Sérsic index to 2.5 where
GALFIT fails to return reliable measurements; i.e., for objects with large uncertainties in
their output parameters. Size determination for all objects while fixing the Sérsic index to
2.5 reveals that this will not introduce systematics in our size study. Fixing Sérsic index
to 1.5 or 3 gives similar size estimates as for n = 2.5. In Figure 3.1 we show from left
to right, postage stamps in the H band, best-fit models from GALFIT, residual images,
and mask maps for a z-dropout (top row) and an i-dropout (bottom row) in the HUDF.
43
Chapter 3 – The Evolution of Mass-size Relation From z = 1 to z = 7
Figure 3.2 – Comparison of sizes of dropout candidates measured in different filters with S/N> 10
in both the HUDF and ERS. Each color represents a different sample of dropout candidates. The
correlation between estimated sizes in different bands is an indication of the reliability of our size
measurements. The small offsets between sizes in different bands maybe due to color gradients in
the galaxies. The objects with large offsets from the one-to-one relation have generally a clumpy
structure or multiple cores.
The low-level residuals shows that our best-fit models closely match the observed galaxy
images.
We first test the accuracy of our measurements by comparing the effective radii, re ,
measured at different wavelengths. A comparison of the sizes of our dropout candidates is
shown in Figure 3.2. Each dropout sample is represented by a different color: B-dropouts
are black, V-dropouts are green, and i-dropouts are blue. We note that ACS has a much
smaller PSF and finer pixel scale, and it is known to produce highly reliable size measurements from previous studies. The correlation between estimated sizes in different bands,
is an indicator of the size measurements reliability. Since color gradients and clumpy star
formation may introduce additional re scatter between bands, these comparisons essentially show an “upper limit” to the intrinsic uncertainties.
In addition, we have performed realistic simulations on both the HUDF and ERS
fields analogous to Mosleh et al. (2011), by adding model galaxies to the images and
measuring their parameters in the same way as for real objects. From the simulations, the
relative difference between the recovered and input sizes versus magnitude shows that the
systematic uncertainties on the recovered sizes are very small (< 10%) down to S/N ratio
of 10 (corresponding to H160 < 28.5 in the HUDF and H160 < 26.2 in the ERS).
Finally, in order to minimize the effects of morphological K-correction, we use sizes
of each object in the WFC3/IR or ACS band that is closest to the rest-frame 2100Å. Therefore in this study the Y105 -band images are used for B-dropouts, J125 images are used for
V-dropouts and H160 -band images for i and z-dropouts.
44
3.4 Results
3.4
3.4.1
Results
Size-Mass Evolution
The size and stellar mass estimates of our dropout candidates allow us to investigate the
mass-size relation and its evolution. Figure 3.3 shows the mass-size relation for four
redshift bin from z = 4 to z = 7. There is a clear relation out to z ∼ 5 and a hint at z ∼ 6 for
galaxies with log(M∗ /M ) > 8.6. In each panel, color points represent the distributions of
candidates in the mass-size plane. Objects with S/N < 2σ in the IRAC [3.6] channel, are
indicated by open symbols, and those with higher S/N (i.e., more reliable stellar mass) are
shown as filled circles. The pink stars indicate the median sizes of galaxies in different
stellar mass bins down to our estimated stellar mass limit. The dot-dashed line in each
panel represents the mass-size relation for late-type galaxies (i.e., n < 2.5) in the local
universe from Shen et al. (2003) and the dashed line represents the best-fit stellar masssize relation for UV-bright galaxies at z ∼ 2 from Mosleh et al. (2011). According to our
simulations, sizes below the dotted lines (corresponding to apparent radii of 0.0500 ) have
large uncertainties and can be conservatively thought of as upper limits.
The stellar mass-size relation for z ∼ 4 and z ∼ 5 is characterized by re ∝ M α with
α = 0.14 ± 0.06 and 0.17 ± 0.07, respectively. These are significantly different from zero.
We note that the correlation coefficients are 0.22 at z ∼ 4 and 0.37 at z ∼ 5. At z ∼ 6, there
might be a hint of a mass-size relation, but there are too few galaxies in our sample at this
redshift to either confirm or rule out a relation. We note that the size and stellar mass of
these galaxies need not to be correlated as the sizes are measured in the rest-frame UV
and the stellar masses in optical rest-frame. Nonetheless, the results show the persistence
of the mass-size relation for star-forming galaxies up to very high redshifts. We also note
that the fraction of contaminants in our dropout samples is relatively small (< 11%)(see
Bouwens et al. (2011, 2007) for more details) and hence unlikely biased the relations.
The black diamond in the lower left panel of Figure 3.3 shows the position in the
mass-size relation of an i-dropout galaxy (S BM03#1 in HUDF) from Eyles et al. (2005).
This object has a robust spectroscopic redshift (z = 5.83) and a stellar mass of a few times
1010 M . The size estimate for this object is consistent with the median size estimate of
i-dropouts in our higher mass bin.
3.4.2
Size Evolution at Fixed Mass
Comparing the median sizes of LBGs for a given stellar mass at different epochs, illustrates the evolution of galaxies effective radii at fixed stellar masses with redshift.
This size evolution is shown in Figure 3.4. Galaxies are split into two stellar mass bins:
9.5 < log(M∗ /M ) < 10.4 (shown in the left panels) and 8.6 < log(M∗ /M ) < 9.5 (shown
in the right panels). For the objects in the lower redshift range (i.e., z ∼ 1 − 3), we used
sizes measured for UV-bright galaxies in the same stellar mass range from our previous
studies by Mosleh et al. (2011). In order to measure the size evolution consistently we use
similar technique described in Newman et al. (2012) to normalize sizes of galaxies with
re ∝ M 0.30 to stellar mass of 109.7 M (left panels) and 109 M (right panels). In the bottom
45
Chapter 3 – The Evolution of Mass-size Relation From z = 1 to z = 7
Figure 3.3 – Mass-size relation for dropout galaxies in different redshift bins. The filled circles
indicate sizes for galaxies with reliable stellar masses (> 2σ detection in IRAC[3.6]). The pink large
stars are the median of sizes from GALFIT in different stellar mass bins with the errors calculated
by bootstraping. The black diamond in the lower left panel is an i-dropout galaxy at z ∼ 6 with
a stellar mass of a few times 1010 M from Eyles et al. (2005). The dashed and dot-dashed lines
show the mass-size relation for UV-bright galaxies at z ∼ 2 from Mosleh et al. (2011) and for latetype galaxies at z ∼ 0 from Shen et al. (2003), respectively. The dotted lines correspond to our
size measurement limits. Typical errors of the points are shown in the lower right of each panel.
This plot shows that mass-size relation holds out to z ∼ 5, and possibly beyond for galaxies with
log(M∗ /M ) > 8.6. Sizes decrease toward higher redshift.
46
3.4 Results
Figure 3.4 – Redshift evolution of the sizes of dropout galaxies in two stellar mass ranges:
log(M∗ /M ) ∼ 9.5 − 10.4 (left panels) and log(M∗ /M ) ∼ 8.6 − 9.5 (right panels). The lower
panels show the distribution of sizes for all sources in our analysis and the sizes of UV-bright galaxies at z ∼ 1 − 3 within the same mass range from Mosleh et al. (2011). The best power-law fits
to these data points are shown as solid lines. The red points are from Oesch et al. (2010) for a
luminosity-selected sample. The black and yellow stars are the sizes derived by stacking galaxies
in the same stellar mass range. The black diamonds in the top panels indicate median size of local
late-type galaxies from Shen et al. (2003).
47
Chapter 3 – The Evolution of Mass-size Relation From z = 1 to z = 7
panels, blue and green points represent normalized half-light radii of dropout objects as a
function of redshift.
We fit a simple power law of the form (1 + z)−m to the observed points (bottom panels
of Figure 3.4); the best fits are shown as solid lines. In the high stellar mass bin, galaxy
sizes are found to evolve as (1 + z)−1.20±0.11 , and for galaxies with lower stellar masses the
size evolves as (1 + z)−1.18±0.10 .
In the top panels of Figure 3.4, blue and green solid circles represent the median
effective radii of dropouts from this study, and the solid squares are median sizes in lower
redshift bins. The red points are the mean galaxy sizes from Oesch et al. (2010) for two
different luminosity ranges: (0.3 − 1)L∗ z=3 in the left panel and (0.12 − 0.3)L∗ z=3 in the
right panel.
The filled yellow and open black stars in the top panels are sizes based on stacking
galaxies from fixed stellar mass ranges for our two fields. For stacking, we used the
central positions of objects determined by GALFIT and replaced contaminated pixels
from neighboring sources with sky background values. We then used GALFIT to measure
the half-light radii of our final stacked images. As shown by, e.g., Hathi et al. (2008a) and
Oesch et al. (2010), stacking can reproduce reliable average surface brightness profiles.
Thus, the agreement between the median points and results of stacking suggests that we
are not systematically missing light in the extended wings of galaxies and that on average
our size estimates are robust.
3.5
Summary And Discussion
For the first time, we have studied the stellar mass-size relation of LBGs out to z ∼ 7 using
ultradeep WFC3/IR observations in the HUDF and ERS fields. We have shown that the
mass-size relation of star-forming galaxies persists to very high redshifts, and that at fixed
stellar mass, the sizes of galaxies increase significantly toward later cosmic time. The
observed size growth of LBGs studied here – re ∝ (1 + z)−1.20±0.11 for galaxies with stellar
mass of 109.5 -1010.4 M – is in agreement with previous stellar mass-size studies at z . 3
(e.g., Dahlen et al. 2007, Mosleh et al. 2011, Nagy et al. 2011, Law et al. 2012). It is also
consistent with the size evolution estimated by other studies based on luminosity-selected
samples (e.g., Ferguson et al. 2004, Bouwens et al. 2004, 2006, Hathi et al. 2008b, Oesch
et al. 2010).
The redshift dependence of the size evolutions is very similar for both high and low
stellar masses. Therefore, the galaxy size evolution might be written as a separable function of mass and redshift and this would be in agreement with simple models of galaxy
formation developed for high-redshift systems (see Wyithe & Loeb 2011). However, our
sample is not stellar mass complete; hence using deeper samples in future is needed for
further investigations.
In Figure 3.5, we compare our estimated size-redshift relation for LBGs with those
in Law et al. (2012) (blue triangles) and Dahlen et al. (2007) (open squares). The sizes
are normalized to a stellar mass of 1010 M . The size estimates from different studies are
48
3.5 Summary And Discussion
Figure 3.5 – Comparison of sizes of UV-bright galaxies measured by different authors. In order to
have a consistent comparison, sizes are normalized using re ∝ M 0.30 for a stellar mass of 1010 M .
The solid line is the best fit from our analysis (re ∝ (1 + z)−1.20±0.11 ). The dotted lines represent the
original (not normalized) size measurement. The black solid diamond is the median size of latetype galaxies at z ∼ 0 for stellar masses around 1010 M from Shen et al. (2003), with the measured
dispersion shown as error bar. The sizes of UV-bright galaxies at fixed stellar mass increases rapidly
toward later cosmic time. However, the sizes measured for local late-type galaxies are smaller than
the sizes of UV-bright galaxies at z ∼ 1. These samples most likely comprise intrinsically different
galaxies.
49
Chapter 3 – The Evolution of Mass-size Relation From z = 1 to z = 7
consistent with the best fit found in this study (m = 1.20 ± 0.11, solid line). This suggests
that LBGs may evolve into UV-bright galaxies at z ∼ 1. At z ∼ 6 these galaxies are
extremely compact: re ∼ 0.8 kpc, at stellar mass of 1010 M . However, they grow by a
factor of about 6 to z ∼ 0.85. The z ∼ 6 galaxies have a mass size relation close to those of
the compact quiescent galaxies at z ∼ 2; for example, the normalized size (re /(M/1010 )0.3
) of a sample of quiescent galaxies at z ∼ 2 studied by Szomoru et al. (2012) is ∼ 0.6 kpc.
The scarcity of observed LBGs between z ∼ 0 and z . 1, complicates the interpretation of the evolution of their stellar mass-size relation to the present time. The median
size measured for local late-type (i.e., n < 2.5) SDSS galaxies by Shen et al. (2003) at the
same stellar mass (black solid diamond in Figures 3.4 and 3.5, corrected to the rest-frame
UV using the analysis by Gil de Paz et al. (2007), Azzollini et al. (2009), and D. Szomoru
2012, private communication) is smaller than the size of z ∼ 1 UV-bright galaxies. We
note that the SDSS late-type sample is most likely a different galaxy population than the
UV-bright sources we study at z & 1 and is therefore not relevant for direct comparison. Overzier et al. (2010) studied 30 local Lyman break analogs (z < 0.3), however this
sample was selected to have a surface brightness limit and is therefore not characteristic
of star-forming galaxies in the nearby universe. In addition, there is some evidence that
the evolution of the stellar mass-size relation for star-forming galaxies is slower between
z = 1 and z = 0 (e.g., Barden et al. 2005). This needs further investigation using homogeneously selected sample in future.
This work was funded in part by the Marie Curie Initial Training Network ELIXIR of
the European Commission under contract PITN-GA-2008-214227.
50
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52
4
On the Robustness of z = 0 − 1
Galaxy Size Measurements Through
Model and Non-Parametric Fits
Moein Mosleh, Rik J. Williams, Marijn Franx
Submitted to The Astrophysical Journal, 2013
53
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
Abstract
We present the size-stellar mass relations of nearby (z = 0.01 − 0.02) SDSS galaxies, for samples
selected by color, morphology, Sérsic index n, and specific star formation rate. Several commonlyemployed size measurement techniques are used, including single Sérsic fits, two-component Sérsic
models and a non-parametric method. Through simple simulations we show that the non-parametric
and two-component Sérsic methods provide the most robust effective radius measurements, while
those based on single Sérsic profiles are often overestimates, especially for massive red/early-type
galaxies. Using our robust sizes, we show that for all sub-samples, the mass-size relations are shallow at low stellar masses and steepen above ∼ 3 − 4 × 1010 M . The mass-size relations for galaxies
classified as late-type, low-n, and star-forming are consistent with each other, while blue galaxies
follow a somewhat steeper relation. The mass-size relations of early-type, high-n, red, and quiescent galaxies all agree with each other but are somewhat steeper at the high-mass end than previous
results. To test potential systematics at high redshift, we artificially redshifted our sample (including
surface brightness dimming and degraded resolution) to z = 1 and re-fit the galaxies using single
Sérsic profiles. The sizes of these galaxies before and after redshifting are consistent, and we conclude that systematic effects in sizes and the size-mass relation at z ∼ 1 are negligible. Interestingly,
since the poorer physical resolution at high redshift washes out bright galaxy substructures, singleSérsic fitting appears to provide more reliable and unbiased effective radius measurements at high z
than for nearby, well-resolved galaxies.
54
4.1 Introduction
4.1
Introduction
Correlations among galaxy physical parameters such as stellar mass, luminosity, size,
velocity dispersion, and their evolution with cosmic time are crucial for understanding
the formation and evolution of galaxies and imposing constraints on theoretical models of their structural assembly. Morphological scaling relations such as the relation
between size and surface brightness, the correlation between size and luminosity (Kormendy 1985), and the relation between the effective radius and stellar mass (Shen et al.
2003, hereafter S03), vary for different types of galaxies. The differences between surface brightness profiles and sizes of galaxies are the products of the different physical
processes governing their formation and evolution. Precise measurements of these galaxy
properties at low and high redshifts thus provide strong constraints on models of galaxy
formation and evolution.
Among these relations is the observed correlation between half-light radius (size) and
stellar mass, which is shown for the local Universe (S03) and persists up to very high
redshifts (e.g., Daddi et al. 2005, Trujillo et al. 2006b, Franx et al. 2008, Buitrago et al.
2008, Cimatti et al. 2008, van der Wel et al. 2008, Williams et al. 2010, Dutton et al. 2011,
Law et al. 2012, Mosleh et al. 2011, 2012). These authors also pointed out that sizes of
galaxies at fixed stellar mass decrease as the redshift increases, i.e., galaxies were smaller
in the past. For instance, massive quiescent galaxies at z ∼ 2 are about a factor of ∼ 6
smaller than their counterparts at z ∼ 0 (e.g., Daddi et al. 2005, van Dokkum et al. 2008).
Understanding the mechanism of the size evolution and how galaxies reach the mass-size
relation at z = 0 requires measuring these properties, especially sizes, very robustly in
different redshift ranges.
One of the main concerns is the accuracy of galaxy size determination at high redshifts. Galaxies at higher redshifts are at larger distances and therefore are dimmer and
have smaller apparent angular sizes. The low surface brightness envelopes of galaxies
could fade away due to cosmological dimming and could have lower signal to noise ratios (S/N), hence, may potentially bring systematics on their real size measurements. For
example, the outer parts of early-type galaxies normally fade away gradually into the
background sky noise, and it is very hard to define precise edges for these types of galaxies. Underestimating the sizes of these galaxies at high redshifts could have an effect on
the inferred rate of size evolution (Mancini et al. 2010).
There are several possible approaches to test the smallness of galaxies at high redshifts. Recently, Szomoru et al. (2010) used deep observations with the Wide Field Camera 3 (WFC3) instrument on board the Hubble Space Telescope (HST) to measure the size
of a massive quiescent galaxy at z ∼ 2 based on a new approach (correcting the best-fit
Sérsic profile of the galaxy with the residual of the fit) to confirm the compactness of this
massive galaxy at this redshift.
The other method in order to check the effects of cosmological redshift on the size/shape
measurements is to artificially transform nearby galaxies to higher redshifts. Comparing
derived parameters before and after redshifting provides a test for biases that may be
introduced by degraded resolution and cosmological surface brightness dimming. This
technique has been used in the past for different purposes, for instance assessing mor55
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
phologies at higher redshifts (e.g., Petty et al. 2009, Conselice et al. 2011, van den Bergh
et al. 2002, Lisker et al. 2006, Giavalisco et al. 1996). Recently, Barden et al. (2008)
used a set of ∼ 100 local galaxies to study the cosmological redshifting effect on size and
shape of galaxies at 0.1 < z < 1.1. They created new images from the best-fit single
Sérsic models of their input images, and then redshifted them to show that there is not any
systematics on the size and morphological parameters. However, nearby galaxies have
signs of different sub-structures and low surface brightness features. Generating simulated galaxies with a comparable range of properties of galaxies and adding them into the
blank sky background images is a practical test. However, these mock objects are simple
cases compare to real objects and could be assumed as a lower limit on the systematics
(e.g., Trujillo et al. 2006b).
It is also a common practice to measure the surface brightness profile of galaxies at
high-z single component Sérsic profile fitting. Therefore, it is assumed that for a consistent comparison of sizes at low and high-z, the profiles of nearby galaxies also should be
measured with the same method. However, as mentioned earlier, galaxies often consist
of multiple components (e.g., bars, bulges, compact cores, spiral arms, etc,). In the local
Universe, these sub-components are well-resolved and distinguishable in the photometric
analysis of their structures. Therefore their surface brightness profiles may deviate from a
single component model. It has been shown that using extra components in fitting surface
brightness profiles of nearby galaxies better describes the underlying stellar distributions
than using canonical single Sérsic profile fitting (e.g., for Elliptical galaxies: Ferrarese
et al. 1994, Lauer et al. 1995, Graham et al. 2003, Huang et al. 2012, also see references
therein). Some authors have also shown that using single component Sérsic profile fitting
for nearby galaxies with more than one component might systematically bias sizes and
morphological parameters (e.g., Meert et al. 2012, Bernardi et al. 2012).
Therefore, in this paper, we first investigate the biases associated with estimating sizes
of nearby galaxies using single Sérsic profile fitting and its effect in their comparison to
galaxies at high redshifts. These effects will also be tested against various types of galaxies (e.g., classifications according to their morphology, color, star-formation rate). We will
explore the possible dependence of the systematics of sizes on the galaxies classifications
and test alternate (two-component and nonparametric) methods.
We also artificially redshift real images of nearby galaxies (z ∼ 0) to z = 1 in order
to investigate the uncertainties of parameter measurements. We will use the resolution
of HST WFC3 instrument, since images from this instrument are now being widely used
for studying galaxy structures at high redshifts (Oesch et al. 2010, Szomoru et al. 2012,
Patel et al. 2012, Newman et al. 2012, Mosleh et al. 2012, van de Sande et al. 2012,
etc.). Moreover, for the sake of better statistics, we use a large sample of nearby galaxies
(∼ 1000 objects).
Finally, we will use our robust size measurements to study the correlation of size and
stellar masses of our nearby galaxies. Galaxies can be selected or classified by means
of different methods or criteria, such as morphology, color and star-formation rate. We
investigate the mass-size relation for different types of nearby galaxies at a wide range
of stellar masses and test whether the selection criteria could affect the mass-size relations. These relations provide a baseline for further studies at high redshifts. We will also
56
4.2 Data
compare the mass-size relations of galaxies after artificially redshifting them to z = 1 and
examine if the robustness of galaxies mass-size relations at high redshifts.
We explain our sample used in this study in section 4.2. The size determination methods and their systematic offsets at z ∼ 0 are explored in section 4.3. The stellar mass-size
relations of nearby galaxies are studied in section 4.4. We describe the artificially redshifting procedure of galaxies to z = 1 and their sizes compare to z = 0 in section 4.5. We
discuss our results in section 4.6. The cosmological parameters adopted throughout this
paper are Ωm = 0.3, ΩΛ = 0.7 and H0 = 70 km s−1 M pc−1 .
4.2
Data
The sample of galaxies we use for this study is selected from the MPA-JHU SDSS DR7
(Kauffmann et al. 2003, Salim et al. 2007) which have spectroscopic redshifts for SDSS
DR7 galaxies (Abazajian et al. 2009) galaxies. The surface brightness limit for our sample
is µ50 ≤ 23 mag arcsec2 with magnitude limit of r ≤ 17.77. We initially select galaxies to
have spectroscopic redshifts within 0.01 < z < 0.02 and stellar masses of log(M∗ /M ) ≥
9. As we intend further to artificially redshift galaxies to z = 1, the imposed redshift limits
are to avoid selecting galaxies where the SDSS PSF is broader than the WFC3 PSF at z =
1 (and providing sufficient sampling at high-z, see Barden et al. 2008, for more details),
and also to avoid objects with very large apparent sizes. To reduce processing time, we
further select about 1000 galaxies randomly from this sub-sample (about one-third of
galaxies in this mass and redshift range). We use SDSS r-band images for measuring
their sizes at this low-z.
We classify our sample into different sub-samples based on their color, morphology
and specific star-formation rate (sSFR). The left panel of Figure 4.1 shows the distributions of all galaxies on color-magnitude diagram. The color and absolute magnitude are
based on the New York University Value-Added Galaxy Catalog (NYU-VAGC Blanton
et al. 2005). Parallel to the red sequence distribution, we define the following line to
separate galaxies into red and blue ones:
(g − r) = 0.68 − 0.032(Mr + 20)
(4.1)
In order to classify galaxies based on their morphology, we used the Galaxy Zoo
catalog (GZ1) (Lintott et al. 2011) which is a morphological catalog of visually classified
SDSS galaxies. We classify galaxies into early-types and late-types based on debiasing
fraction of the votes for each galaxy being dominant (see Lintott et al. (2011) for more
details). We note that the classification are only available for ∼ 94% of our sample. The
color magnitude distributions of these early-types and late-types are shown in middle
panel of Figure 4.1. Early-type galaxies are indicated as red symbols and late-type ones
as blue.
Galaxies can also be selected by means of their specific star-formation rate (sSFR)
(Brinchmann et al. 2004). In the right panel of Figure 4.1, the distributions of sSFRs and
stellar masses of galaxies are shown. We define the Log(sS FR) = −11 as a separating
57
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
Figure 4.1 – Left: The color-magnitude diagram of our sample. The solid line shows the separating
cut to define red and blue galaxies. Middle: The same as left panel but galaxies are color-coded
according to their morphological classifications, i.e. Early-type galaxies as red points and Latetype galaxies as blue points. The morphological classification is based on the Galaxy Zoo Catalog
(GZ1). Right: Distribution of galaxies specific star-formation rate (SSFR) as a function of their
stellar mass; the solid line represents the separation cut at log(sS FR) = −11.
cut to split our sample into star-forming and non star-forming ones. In summary, we
divide our galaxies by four criteria: (1) Morphology based on Galaxy Zoo visual galaxy
classifications (2) Color (3) Specific star formation rate (sSFR) (4) Sérsic indices (based
on smoothed profiles of galaxies at low-z, see Appendix B).
We also need to take into account the effects of sample selections on the completeness.
We follow S03 to apply volume corrections to our sample (Vmax method). We give each
galaxy a weight which is proportional to the inverse of the maximum volume out to which
it can be observed. However, as our sample is limited to redshift ranges of z = 0.01−0.02,
all galaxies have equal weights and hence our sample is not biased by stellar mass incompleteness down to 109 M . It is worth noting that the fraction of galaxies which were not
morphologically classified by Galaxy Zoo is ∼ 6% on average and hence the effects are
negligible.
4.3
Sizes at z = 0
As mentioned earlier, the well-resolved profiles of some of nearby galaxies could exhibit non-Sérsic structures. Consequently, this raises questions about the effects of these
structures on measurements of nearby galaxy sizes (i.e., half-light radii) with singlecomponent, analytical models. In the following, we employ several methods to measure sizes of our z = 0.01 − 0.02 galaxies. These methods can be separated into two main
categories: ‘parametric’ i.e., measuring the half-light radius of galaxies using best-fit twodimensional analytical models and ‘non-parametric’ from their observed one-dimensional
light profiles and measuring their total fluxes as described below.
58
4.3 Sizes at z = 0
4.3.1
Parametric Methods
To quantify the structural properties of galaxies with parametric methods, we use the
GALFIT v3 modeling software (Peng et al. 2010). GALFIT measures the shape and
size of each galaxy by finding a best-fit parametric model of its two-dimensional surface brightness profile. It generates a range of profile models which are convolved with
the PSF of the galaxy image and determines the best-fit model by comparing models to
galaxy light profile and minimizing the χ2 of the fit. GALFIT can fit one or more analytical functions such as Sérsic (Sérsic 1963, Sersic 1968), de Vaucouleurs (de Vaucouleurs
1948), etc., to a galaxy light profile.
In the following we outline the procedure for using GALFIT and measuring galaxies
structural parameters from Sérsic models. We first created a postage stamp for each galaxy
from SDSS (r-band) imaging frames (2048 × 1448 pixels and pixel scale of 0.39600 ). The
postage stamp should be large enough to contains enough background sky pixels. We
initially set our postage stamps to have widths of at least 1800 pixels. However, as our
galaxies have large apparent angular sizes and they might be located on different positions
on SDSS frames, the postage stamp sizes varies a bit for each galaxy. Nevertheless,
our defined box-size value creates a postage stamp for each galaxy & 10 times larger
than apparent galaxy sizes. These are sufficient for leaving the sky background as a free
parameter during fitting procedure.
In order to detect and mask neighboring objects, we use SExtractor (Bertin & Arnouts
1996). For SDSS r-band images, we use the following SExtractor configuration parameters for detecting sources: DET ECT _MINAREA = 10, DET ECT _T HRES H = 1.5
and ANALYS IS _T HRES H = 1.5 and DEBLEND_MINCONT = 0.095. In addition,
we further smoothed out the mask map created by SExtractor to reduce plausible bias
of sky background estimations by contribution from undetected low flux regions around
nearby sources. We also provide the initial parameters for GALFIT, such as half-light
radius, magnitude, position angle and axis ratio derived from SExtractor and initially set
the Sérsic index to value of 2.
The SDSS photo pipeline generates a synthesized PSF image at the central position of
each galaxy using a published tool of Read Atlas Images 1 . We use this code and extracted
PSF images in r-band SDSS for each galaxy, separately. The PSF images required by
GALFIT to convolve model images during fitting procedure.
4.3.1.1
Single Component Sérsic Profiles
Our first adopted parametric model for describing the galaxies surface brightness is the
one component Sérsic model. Single component Sérsic profiles are widely used for determining galaxy structures and properties, especially for high redshifts galaxies. The Sérsic
function describes the surface brightness of a galaxy at radius r as
1/n
Σ(r) = Σe e−bn [(r/re )
1
−1]
(4.2)
http://www.sdss.org/dr7/products/images/read_psf.html
59
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
where re is the half-light radius and Σe is the surface brightness at re . The shape of the
galaxy profile is determined by the Sérsic index n, and the value of bn is coupled to n (see
for more details in Graham & Driver 2005).
4.3.1.2
Two-Component Sérsic Profiles
Although the single Sérsic profile describes the surface brightness of galaxies over a large
dynamic range remarkably well (e.g., Kormendy et al. 2009), the departure from the simple models can be used for diagnosing the formation of the galaxies. Specifically, nearby
elliptical galaxies tend to show either ‘extra light’ or ‘missing-light’ in their central regions, depending on their luminosity and different empirical functions (e.g., “core-Sérsic
” or “Nuker” law) have been used and suggested to parametrize these distinct components (Ferrarese et al. 1994, Lauer et al. 2007, 1995, Graham et al. 2003, Côté et al. 2006,
Hopkins et al. 2009b). However, as our sample consists of wide ranges of luminosities
and morphologies, we use double Sérsic profiles which allow a variety of possible inner
and outer profiles for each object (see Turner et al. 2012). Our adopted multi-component
model is described as:
1/n1
Σ(r) = Σe1 e−bn1 [(r/re1 )
−1]
1/n2
+ Σe2 e−bn2 [(r/re2 )
−1]
(4.3)
To compute effective radii, we first analytically reconstructed the sum of the deconvolved circularized surface brightness profiles of two components from the best-fit parameters and then computed their total fluxes and consequently their half-light radii.
4.3.2
Non-Parametric Method
We test the results from these analytical models against an independent non-parametric
method. The non-parametric technique do not rely on the previous assumptions about
the structure of galaxies. It benefits from the galaxy observed curve of growth. In brief,
the observed intensity profile of a typical galaxy is measured through elliptical isophotal
fitting and from that, the growth curve of galaxy fluxes is determined. This provides the
radius at which the flux reaches to half of the total value.
In details, in order to measure the half-light radius of galaxies from this method, we
need to integrate the fluxes of galaxies at different radii and find the radius at which the
flux reaches half their values. For this purpose, we first extract the observed surface
brightness profile of galaxies using the IRAF task ELLIPSE (Jedrzejewski 1987). This
procedure measures fluxes in isophotal ellipses over the galaxy image and therefore can
make it possible to generate one-dimensional surface brightness profile of a galaxy.
The accuracy of this method depends on the precise measurements of galaxies total
fluxes. Therefore we measure the fluxes out to ∼ 400 arcsec from the galaxies center.
However, the surface brightness of galaxies is low at the outer parts and hence it is very
difficult to define the exact edges of galaxies. Therefore, for measuring the fluxes in the
outer parts, we extrapolate the total light of galaxies beyond their petroR90 radius (i.e.,
a radius containing 90% of the petrosian flux derived from SDSS DR7). This is done
60
4.3 Sizes at z = 0
by fitting one-dimensional Sérsic profiles to these outer regions. By integrating the light
profiles estimated from our best-fit models to infinity, the total fluxes in the outer regions
are estimated. Moreover, in this way, we also estimate the sky background for each galaxy
as sky value is left as a free parameter during the fitting procedure. Then for each galaxy,
we integrate fluxes at different radii up to radius smaller than petroR90 from the fluxes
measured by ellipse fitting and add them to the fluxes estimated in the outer region. This
gives the total fluxes of galaxies and hence leading to extract the radii at which contains
half of the total fluxes, i.e., their non-parametric half-light radii. We note that for about
less than 7% of the galaxies, the one dimensional fitting to the outer parts using petroR90
are not converged. Hence we used petroR50 which is radius contains 50% of the flux
within petrosian magnitude. In order to check if the results depend on the choice of
radius for the rest of the sample, we repeated the procedure by fitting the outer parts of
galaxies starting at smaller radii of i.e., petroR50. The results were perfectly consistent
for all galaxies. We note that we fixed the ellipticity (E) and the position angle (P.A.) of
the ellipse isophotes to the values obtained from the best-fit of single Sérsic parametric
method.
The sizes derived from non-parametric method are also needed to be corrected for
point spread function
(PSF) broadening and therefore we use the following relation acp
cording: R = (r1/2 )2 − (rPS F )2 , where r1/2 and rPS F are the derived non-parametric halflight and PSF size, respectively. This correction is only important for very small galaxies
(. 1 kpc). √It is also worth noting that that all sizes derived in this paper are circularized, using ab, in which a is the semimajor axis and b/a is the axis ratio. This removes
the effects of ellipticity (e.g., Trujillo et al. 2006b, Franx et al. 2008, Williams et al. 2010).
4.3.3
Simulations (I) & (II)
We perform simulations for testing our methods and procedures as follows. The first one
is designed to test the reliability of the single component Sérsic method and the nonparametric method for galaxies at z = 0. For that, we first generated single Sérsic mock
galaxies with random properties (magnitude, re, b/a) in similar range of values for real
galaxies. We then add them into the empty regions of the r-band SDSS images and
perform our fits, using single Sérsic profiles and the non-parametric method. The results
are shown in Figure 4.2. In the left panel, the comparison between input and output sizes
are shown using parametric method and the Sérsic indices are compared in the middle
panel. The output sizes derived by using the non-parametric method are also compared to
their original sizes in the right panel of Figure 4.2. The sizes of galaxies can be recovered
without any systematics with median differences less than 2% for both methods. There
are also no systematic errors in the recovery of Sérsic indices. This shows that for mock
galaxies with single Sérsic profiles, our procedure are robust in recovery of their properties
from SDSS images.
As shown in Appendix A (Figure 4.10), sizes of galaxies derived using single Sérsic profile fitting can be biased, especially for massive early-type galaxies. This may
be caused by the existence of additional component(s) or non-Sérsic light profiles. We
61
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
Figure 4.2 – Simulation (I): The comparison between sizes of simulated galaxies (models with
‘single’ Sérsic profiles) and their recovered sizes (using single Sérsic component fittings in left
panel and using Non-parametric method in right panel) and Sérsic indices (middle panel) after
adding them into empty regions of SDSS r-band images. As plots show, there is no systematics in
recovery of parameters of single Sérsic model galaxies for both methods.
have also shown that sizes derived with double Sérsic component, are smaller that sizes
from one component models. We test an idealized case using simulated two-component
objects. For that, we first created a sample of 300 two-component Sérsic galaxies such
that each model galaxy has a central component with median half-light radius of ∼ 1 kpc
and the outer component with median size of ∼ 3 kpc. We also assumed that the central
components have larger median Sérsic indices than the outer-part components. For all
galaxies, the central components are ∼ 0.6 magnitude fainter than the other one. These
numbers are derived from the average results of the two-component fits to our real galaxies at z = 0.01 − 0.02. To ensure that we are testing only the effects of multi component
galaxies, only the sky background levels are added to the images of these model galaxies
without any additional noise or neighbouring objects. We then measure sizes of these
two-component model objects using single Sérsic profile fitting and the non-parametric
method. The results are shown in Figure 4.3. As seen in the left panel, the sizes are recovered robustly with the non-parametric method. However, as shown in the right panel
of Figure 4.3, sizes from single Sérsic fitting are biased (larger) compared to their input
half-light radii, especially for large objects. This simplified test shows that sizes from
single Sérsic profile fitting can be biased for true two-component galaxies. Meert et al.
(2012) use different assumptions for simulated SDSS galaxies and show the existence of
bias in recovered parameters by fitting a single Sérsic profile to real two-component systems. Although our sample are quite nearby (∼ 45 − 85 Mpc), Bernardi et al. (2012) show
the same effect for the main SDSS sample at z ∼ 0.1. Hence, using single Sérsic sizes for
local galaxies can introduce systematics in size analyses.
Nevertheless, fitting correct models to nearby galaxies is complicated. Different authors use different models to fit multi-component galaxies, e.g., traditional deVaucouleurs
plus Exponential disk, Sérsic +Exponential (Meert et al. 2012), double Sérsic or even
using multiple (3-4) Sérsic profiles (Huang et al. 2012). It is also the case that not all of
62
4.3 Sizes at z = 0
Figure 4.3 – Simulation (II): The comparison between sizes (i.e., half-light radii) of simulated
galaxies (models with ‘double’ Sérsic profiles) and their recovered sizes using single Sérsic component fittings (right panel) and non-parametric method (left panel). This shows that sizes derived
from single Sérsic profile fitting are biased for true nearby two-component Sérsic profile objects.
We note that this simulation does not include noise, in order isolate the biases caused by intrinsically
complex structures.
63
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
the galaxies (at wide ranges of stellar masses) need to be measured by multi-component
models (∼ 77% are robustly fit with two-component models in this work). Therefore, for
the rest of this study, we use our non-parametric sizes for these z ∼ 0 galaxies. Our simulations (I & II) demonstrate the robustness of our non-parametric method. In addition,
due to the large angular sizes of our galaxies, the effects of the PSF on sizes from this
method are negligible.
It is worth nothing that fluxes used for estimating the stellar masses of SDSS galaxies
are model dependent and hence these fluxes can be different from fluxes measured through
the non-parametric method for each individual galaxy. Therefore, it is essential to correct
the stellar masses according to the new flux measurements. We rescale the stellar mass of
each galaxy by measuring the ratio between its non-parametric flux and the one used for
estimating its stellar mass from the MPA catalog.
4.4
Stellar Mass-Size Relation At z = 0
The stellar mass-size relation for the SDSS galaxies has been studied by S03. They investigated this relation for objects which are defined as early and late types according to
their Sérsic and concentration indices, and their relations have been widely used in literature. However, it is argued that the half-light sizes used in S03, which are from the
NYU-VAGC catalog and based on one-dimensional (1D) single Sérsic fitting, could have
been underestimated (e.g., Guo et al. 2009, Simard et al. 2011). We have also shown that
using single Sérsic fitting could bias the sizes of galaxies with high stellar masses. As the
mass-size relation could depend on the fitting model employed (specifically at high-mass
ends), our independent non-parametric method for z = 0 galaxies, should remove uncertainties due to model assumptions. Our sample consists of galaxies over a wide range of
stellar mass (& 109 M ) and is suitable for investigating this relation.
We first study the mass-size relation of our sub-samples based on morphological
Galaxy Zoo classifications. The distribution of sizes versus stellar masses of late-type
and early-type galaxies are illustrated in the top row of Figure 4.4. The median sizes in
small bins of stellar masses for each sample are measured (blue and red circles), and it
can be seen that sizes of both late-types and early-types show little or weak correlation
with to mass up to ∼ 3 − 4 × 1010 M ; however the relation steepens beyond this stellar
mass and is stronger for the early-type galaxies. For both types of galaxies, the relations
seem to begin above specific stellar masses.
To further quantify the correlations, we use the functional form employed for late-type
galaxies in S03 (equation 18) for both our late-type and early-type samples:
Rkpc = γ(M∗ /M )α (1 + M∗ /M0 )β−α
(4.4)
Where, α, β, γ and M0 are free fitting parameters. This basically allows the relation
to have two different slopes depending on the stellar mass range. The α and β represent
the slopes of the relation and the characteristic mass, M0 determine the stellar mass at
which the slope of the relation changes. However, this relation is not very sensitive to the
64
4.4 Stellar Mass-Size Relation At z = 0
Figure 4.4 – Top row: The stellar mass-size relation of late-type galaxies (left panel), and earlytype galaxies (right panel). The individual galaxies are shown as small open gray circles and the
blue and red filled circles are the median of the sizes in stellar mass bins. The solid blue and red
lines are the best fits to the data. The mass-size relation from studies of Shen et al. (2003) and Guo
et al. (2009) are also illustrated by dashed and dot-dashed lines, respectively. The best-fit relations
are consistent with Shen et al. (2003), however, for early-type galaxies the relation flattens below
M .∼ 4 × 1010 M . The shaded gray regions show the physical sizes of PSFs in SDSS r-band
images. Bottom row: The size dispersions as a function of stellar masses and their best-fits. The
characteristic stellar masses, where the dispersions change significantly, are shown as vertical dotted
lines.
characteristic mass, M0 , therefore, this can be defined from the size dispersion relation as
follows (equation 19 in S03):
σlnR = σ2 +
(σ1 − σ2 )
1 + (M∗ /M0 )2
(4.5)
where σ1 and σ2 are also free fitting parameters (representing size dispersions at low
and high masses) and M0 is the characteristic stellar mass at which σlnR significantly
changes. Size dispersions as a function of stellar mass for late-type and early-type galaxies are shown in bottom panels of Figure 4.4 (left and right panels, respectively). The best
fits to the data points are shown as solid blue and red lines and the best-fit parameters are
presented in Table 4.1.
For late-type galaxies, the median size dispersions decrease at stellar mass greater than
∼ 4 × 1010 M consistent with S03. The mass-size relation for these galaxies are also con65
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
Figure 4.5 – The stellar mass-size relation of galaxies classified by means of different criteria. In
the right panel, blue, late-type (visually classified), star-forming galaxies, and low-Sérsic index
(n < 2.5) are compared and in the left panel red, early-type (visually classified), non star-forming,
and n > 2.5 are compared. The stellar mass-size relation from studies of Shen et al. (2003) and
Guo et al. (2009) are also illustrated by dashed and dot-dashed lines respectively. The points are
the median size dispersions as a function of stellar mass and the lines represent the best-fits to these
points. As this plot shows, the relation based on different methods of classification of galaxies are
largely consistent, though blue galaxies lie above the other relations.
sistent with S03 (dashed line). The size dispersions for early-types also behave similarly
and decrease for massive galaxies above a characteristic mass around 4 × 1010 M . However, due to low number of objects at these high mass bins, it is not clear how significant
this effect is.
The median sizes of early-type galaxies at a stellar mass range of log(M∗ /M ) ∼ 10 −
11 are consistent with the S03 relation. However, at lower stellar masses (. 2 × 1010 M ),
sizes are almost constant. Therefore, in this mass range, there is little or weak correlation
between stellar mass and size. For late-type galaxies the relation runs parallel at these
masses but with larger sizes. The mass-size relations for galaxies with higher stellar
masses (i.e., & 2 × 1010 M ) are steep for both late and early types. However, each sample
exhibit different slopes and early-types have a steeper mass-size relation (see Table 4.1).
We also present the mass-size relations of galaxies based on different sample definitions such as color, Sérsic indices and sSFR in Figure 4.5 in order to test the effects of
these selections on the mass-size relation and defining baselines for future studies based
on different sample classifications. Interestingly, the mass-size relations based on these
classifications are consistent to the analogous relations in Figure 4.4. In the left panel
of Figure 4.5, late-type galaxies are compared to the star-forming, blue and low Sérsic
index galaxies. They are almost consistent, though the blue galaxies have larger sizes
66
4.5 Redshifting Galaxies to z = 1
at stellar masses & 1010 M compared to the others. This could be caused by excluding
edge-on galaxies using the color criterion. We should note that the Sérsic indices are measured from the degraded and smoothed SDSS images of galaxies (See Appendix B, Figure
4.15), hence removing biases from sub-structure. Nevertheless, it is interesting that the
mass-size relation obtained for objects with Sérsic indices of n < 2.5 are consistent with
S03. The best fits to the mass-size relation are summarized in Table 4.1.
The right panel of Figure 4.5 illustrates the comparison between the mass-size relation
of early-type galaxies and those with red colors, low sSFR and high Sérsic indices. The
relations are also consistent with each other. For all samples, the relations are curved with
a weak relation for galaxies below 4 × 1010 M . The slopes of the mass-size relations at
high mass ends (β) for these red/quiescent/n > 2.5 galaxies are on average around ∼ 0.85,
close to the slope of early-type central galaxies in Guo et al. (2009). However, this slope
is slightly larger for early-type galaxies.
In general, we show that the stellar mass-size relations for both late and early type
galaxies are curved with a steeper slope at higher stellar masses. The size dispersions
bellow the characteristic masses are high but decrease above M0 . This is the case for all
our studied samples. The stellar mass-size relations based on different definitions, such
as color, sSFR, morphology are consistent with the scaling relations of late and early type
galaxies.
4.5
Redshifting Galaxies to z = 1
In order to check whether cosmological effects and observational uncertainties could affect size (and structural parameter) measurements of galaxies at high redshifts, we perform redshifting simulations of the low-z object. We use our sample of galaxies from
SDSS at z ∼ 0 to create artificially redshifted samples of galaxies resembling the same
galaxies at z = 1 in HST WFC3 images. Our redshifting procedure is similar to the
method described by Barden et al. (2008) (FERENGI code) and we briefly describe it
bellow. However, in order to take into account the effects of bandpass shifting, we only
use SDSS r-band images as input and using WFC3- J125 images from CANDELS DEEP
DATA (Bouwens et al. 2012) as output images instead of using the k-correction method
described in Barden et al. (2008). WFC3 is the new near-IR instrument on board of HST
and covering rest-frame optical wavelengths at z ∼ 1 − 3. Hence it is suitable for this
purpose.
4.5.1
Method
The first step in the redshifting procedure is to rebin the low-z images with pixel scale pi
and redshift zi to output images at redshift of zo (= 1 in this work) and pixel scale of po
by a factor of β as:
β=(
Di p i
)( )
Do p o
(4.6)
67
68
α
−0.02 ± 0.07
0.04 ± 0.05
0.01 ± 0.06
0.09 ± 0.09
0.06 ± 0.06
0.18 ± 0.08
0.10 ± 0.09
0.12 ± 0.08
β
1.25 ± 0.21
0.80 ± 0.12
0.91 ± 0.16
0.83 ± 0.21
0.35 ± 0.18
0.33 ± 0.16
0.26 ± 0.19
0.27 ± 0.16
log(γ)
0.24 ± 0.73
−0.31 ± 0.47
−0.05 ± 0.65
−0.86 ± 0.90
−0.20 ± 0.55
−1.40 ± 0.75
−0.74 ± 0.83
−0.87 ± 0.75
M0
10.67 ± 0.20
10.53 ± 0.13
10.55 ± 0.10
10.53 ± 0.16
10.60 ± 0.23
10.32 ± 0.30
10.20 ± 0.21
10.22 ± 0.23
σ1
0.74 ± 0.07
0.75 ± 0.09
0.86 ± 0.11
0.75 ± 0.15
0.50 ± 0.04
0.57 ± 0.05
0.66 ± 0.05
0.67 ± 0.05
σ2
−0.08 ± 0.24
0.13 ± 0.07
0.13 ± 0.08
0.14 ± 0.09
0.16 ± 0.10
0.05 ± 0.12
0.23 ± 0.10
0.24 ± 0.09
Note. The best-fit parameters for the stellar mass-size relation for different types of galaxies at z ∼ 0 (equation 4.4 and 4.5).
Sample
Early-type
Red
Log(S S FR) < −11
Sérsic > 2.5
Late-type
Blue
log(S S FR) > −11
Sérsic < 2.5
Table 4.1 – The fitting results of the parameters in the Size-Mass relations.
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
4.5 Redshifting Galaxies to z = 1
d
where D is the angular diameter distance, expressed as D = (1+z)
2 , and d is the luminosity distance.
The next step is to apply cosmological surface brightness dimming at the rate of
(1 + z)−4 in each rebinned pixel. By considering the fact that the absolute magnitude
of galaxies must be conserved, the total fluxes f of the input and output images must
scale as:
(
di
fo
) = ( )2
fi
do
(4.7)
We note that it has been shown by several studies (e.g., Barden et al. 2005, Labbé et al.
2003) that the intrinsic surface brightness of galaxies increases with redshift. Therefore,
during our procedure of artificially redshifting our galaxies, we incorporate the surface
brightness evolution and making the galaxies one magnitude brighter at z = 1 following
this equation Mevo = xz + M and setting x = −1 (Barden et al. 2008).
It is important to reach the same resolution of the real data at high-z. Therefore, the
next step is to correct the images to the appropriate PSF. This can be done by finding
suitable kernels for convolving low-z images to reach the same PSF properties/shape at
high-z. To do this, for each galaxy we require two PSFs, i.e., its low-z and high-z PSFs.
We use low-z PSFs from SDSS (the ones we used for measuring sizes at z ∼ 0) and for
high-z, the median-stacked PSF which made from non-saturated stars in the J125 WFC3
images. Then, by transformation of PSFs into Fourier space, finding their ratio and transforming the results back into spatial domain, we can find the convolution kernels required
to reach the WFC3’s J125 band PSF. Note that we calculate separately a transformation
function for each galaxy as the kernel depends on the input and output redshifts.
After transforming images to the high-z resolution an pixel scale, the last step is to
add background noise to the images. For this, we put galaxy images into random empty
regions of the J125 band CANDELS DEEP images and then measure their structural parameters as described below. We note that, in order to check the effects of sky variations on galaxy property measurements, we repeated this step by inserting each redshifted
galaxy into multiple empty regions. The final measured size/parameter for each object is
the median of these seven realizations.
The procedure to measure the structural properties of artificially redshifted galaxies
(i.e., size and Sérsic index) is similar to that used in Mosleh et al. (2012). In brief, we used
GALFIT to find the best-fit single Sérsic model for each galaxy. Neighbouring objects
are detected by running SExtractor and masked during profile fitting. Initial parameter
guesses, such as magnitude, half-light radius and axis ratio are provided from the SExtractor output. We used the median-stacked PSF from stars in the field. In Figure 4.6, we
show the SDSS postage stamp images of the galaxies (late-types in the left set of panels
and early-types in the right set of panels) at low-z (the left columns) and after redshifting
to z = 1 (middle columns). The best-fit single Sérsic models of these artificially redshifted
galaxies at high-z are shown in the right columns.
We perform two sets of simulations to test the size measurement accuracy in the J125
WFC3 images, and to check the procedure for artificially redshifting the galaxies. These
69
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
Figure 4.6 – Example images of four spiral galaxies (left set of panels) and four elliptical galaxies
(right set of panels). In each set, the left panels show the SDSS (r-band) postage stamp images
(20000 × 20000 ) of galaxies at 0.01 < z < 0.015and in the middle columns, we show their artificially
redshifted (to z = 1) postage stamp (700 × 700 ) images after adding to WFC3-J125 images and in the
right columns represent the best fit single Sérsic models of these redshifted galaxies.
tests are described in Appendix B. We show that our redshifting method and size measurements at high-z are robust and can recover sizes and structural parameters of model
galaxies without any systematics.
However, as mentioned earlier, using single Sérsic profile fitting for more complex
galaxies in the nearby Universe potentially biases size estimates. This fact raises concerns
about the sizes of galaxies at high redshifts derived from single Sérsic fitting. Therefore, it
is also worth checking whether single Sérsic profile fitting biases sizes of two-component
objects at high redshifts. For that, we use the same simulated two-component model
galaxies in section 4.3.3 (simulation (II), Figure 4.3) and redshift them to z = 1. We
measured their sizes after redshifting with single Sérsic models. The results are shown in
Figure 4.7. This shows that single Sérsic profile fits of two-component galaxies at z = 1
provide reliable sizes, likely due to the smaller structures being washed out at high redshift. Therefore, traditional single Sérsic surface brightness fitting robustly recovers sizes
of our redshifted galaxies.
70
4.5 Redshifting Galaxies to z = 1
Figure 4.7 – Sizes of simulated two-component z ∼ 0 galaxies which have been “redshifted” to
z = 1 and remeasured with single-component Sérsic profile fitting. The input and output sizes are
consistent, indicating that sizes of multi-component galaxies can be reliably derived with singlecomponent Sérsic models at higher redshifts.
4.5.2
Comparing to Sizes at z = 0
In previous sections, we described how the sizes of our sample are measured reliably at
both z ∼ 0 and z = 1. In this section, we compare sizes of galaxies before and after
redshifting to z = 1. The comparison between low-z and high-z sizes for all galaxies
are shown in left upper panel of Figure 4.8 and their median relative differences in small
bins of sizes are shown in the left bottom panel. As can be seen, sizes before and after
redshifting agree well and there are no systematics.
There are also no biases if we split the sample into blue and red galaxies. Although
the random scatter increases with size for red objects, there are no systematics, and on
average sizes of these galaxies can be reliably recovered at high redshift. As mentioned
in section 4.5.1, to check the effects of the sky background on properties of galaxies at
z = 1, we perform different realizations by inserting the galaxies into different random
blank sky regions and remeasure their properties. The galaxy parameters at z = 1 are the
median values of these repeated measurements and the error bars illustrate the 1σ scatter.
Galaxies are also color-coded according to their stellar masses.
The results are the same using different galaxy classifications. For instance, in Figure
71
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
Figure 4.8 – A comparison between sizes of galaxies at low redshift to their sizes measured after
artificially redshifting to z = 1 for all galaxies (left panel), late-type galaxies (middle panel), and
early-type galaxies (right panel). The errors are the standard deviation of their sizes measured at
different positions (different realizations). Sizes of galaxies are recovered after redshifting without
any systematics.
4.8, the size comparison is shown for late-type (middle panel) and early-type galaxies
(right panel). Although the scatter increases for large and massive early-type galaxies,
there is not any systematic differences in their sizes.
It is worth noting that for sizes at z = 0, we used non-parametric method and for galaxies at z = 1 single Sérsic profile fitting is used. Using single Sérsic profile fitting at z ∼ 0
brings systematics when comparing sizes before and after redshifting (e.g, Weinzirl et al.
2011). This is also the case for comparing Sérsic indices, which tend to be overestimated
at z ∼ 0 using single Sérsic profile fitting.
The fact that sizes of multi-component galaxies at z = 1 can be recovered robustly using single Sérsic fitting can be explained by the resolution limit of images at high redshifts.
The differences are mostly noticeable for massive early-type galaxies. The bright centers
of elliptical galaxies have typical sizes of . 1 kpc (e.g., Huang et al. 2012, Hopkins et al.
2009b,a) which is about the typical size of PSF FWHM of WFC3 images (∼ 1.2kpc) at
z = 1. As a result, the inner components are smeared out and the galaxy profiles are
dominated by the outer components. Therefore, using single Sérsic fitting at this redshift
and resolution robustly recovers the true parameters (See Appendix B for additional tests
which illustrate how degrading the resolution affects measured structural parameters of
local galaxies).
We have also checked whether the results after redshifting are sensitive to the signalto-noise (S/N) of images. This has been tested by changing the S/N, either by adding
noise to the SDSS r-band images before redshifting them or arbitrarily increasing the S/N
of redshifted objects. These tests did not show any systematic changes in the size of red72
4.5 Redshifting Galaxies to z = 1
Figure 4.9 – The stellar mass-size relations and size dispersions of late-type (left panels) and earlytype (right panels) galaxies are compared before and after artificially redshifting to z = 1. The blue
and red points are the the median sizes of galaxies in mass bins and the dashed-three dotted lines
are their best fits. The mass-size relations are consistent with the relations at z = 0 (open circles
and solid lines). This further demonstrates that size-mass relations of galaxies are reliable at z = 1
using single Sérsic profile fitting.
shifted objects. Therefore, in general, sizes of galaxies at high redshift can be measured
robustly using canonical single Sérsic profile fitting as long as the physical resolution is
not better than ∼ 1 kpc.
4.5.3
Stellar Mass-Size Relation after Redshifting
It would now be interesting to examine how the stellar mass-size relations look like after
redshifting to z = 1. In Figure 4.9, comparison of the mass-size relations before and after
redshifting to z = 1 are illustrated. The relations for late-type galaxies are shown in the
left panel, where the solid blue diamonds are the median sizes after redshifting in small
mass bins and the dashed-three-dotted line is the best-fit to the data. The open circles are
the median sizes at z = 0 along with the solid black line as a best-fit (same as in Figure
4.4). The size dispersions after redshifting also shown in the bottom left panel. The
relations for early-type galaxies are shown in the right panel. As can be seen, the masssize relations are consistent to their z = 0 after redshifting. The poor constraints at the
high stellar mass end are due to small number statistics; however, the results are consistent
73
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
within uncertainties. This Figure shows that the stellar mass-size relations based on the
single Sérsic profile fitting at high redshifts are robust. Using different definitions for
separating galaxies would result the same after redshifting. In Figure 4.9, we only present
the relations for morphologically selected sample.
4.6
Discussion
In this paper, we use a sample of about 1000 galaxies at 0.01 < z < 0.02 from SDSS DR7
to study their sizes and stellar mass-size relations. We first investigate the robustness of
size measurement methods for these nearby galaxies, using two main procedures for determining sizes and structures: parametric methods (single and double component Sérsic
profile fittings) and a non-parametric method. In agreement with recent works (e.g., Allen
et al. 2006, Bernardi et al. 2012, Meert et al. 2012, Huang et al. 2012), the majority of
galaxies in the nearby Universe are well fit with two component profiles. Comparing the
sizes from the non-parametric method (and from double Sérsic fits) to those from single
Sérsic fits shows the systematic overestimation of sizes from the single Sérsic method.
In particular, sizes and Sérsic indices of early-type galaxies at the high stellar mass end
tend to be overestimated using the single Sérsic fitting approach. Non-Sérsic profiles or
substructures in nearby galaxies may to be the cause of this bias. We tested this by simulating two-component model galaxies and measuring their sizes using single Sérsic fitting
and reached the same conclusion. Using single Sérsic profile fitting also overestimates
the Sérsic indices of these galaxies. Therefore, we caution that relying on single Sérsic
fits can introduce biases for nearby, well-resolved galaxies.
Stellar mass-size relations of z = 0 galaxies from surveys like SDSS are often used
as baselines for quantifying the evolution of higher-redshift galaxy sizes. Using the nonparametric method and classifying our sample thorough a number of frequently-employed
criteria (size, color, morphology, and Sérsic index), we have explored the stellar mass-size
relation of galaxies in the nearby universe down to a stellar mass of 109 M . We show that
the slope of the relation varies with mass for both late-type and early-type galaxies. The
relations flatten for galaxies below about 3 − 4 × 1010 M (see also Figure 11 in Turner
et al. 2012). Moreover, at these low stellar masses, the relations for both late-types and
early-types run parallel but with smaller sizes for early-type objects. Above a characteristic stellar mass of ∼ 3 − 4 × 1010 M , the mass-size scaling relations get steeper with
less scatter for both late- and early-types. However, the early-types have a significantly
steeper relation than late-types.
In S03, the mass-size relation for early-types is reported down to stellar a mass of
∼ 1010 M . They indicated that faint ellipticals were missed in the analysis due to their
type classifications based on concentrations and Sérsic indices. However, they report
tentative evidence that the size-luminosity relation for faint red galaxies flattens at low
masses. Graham & Worley (2008) showed that the size-luminosity relation of elliptical
galaxies has a varying slope. Janz & Lisker (2008) also showed a different size luminosity
relation for dwarf and giant early-type galaxies in the Virgo Cluster and illustrated that
the relation has little to no dependence on luminosity on the faint end. Bernardi et al.
74
4.6 Discussion
(2012) also pointed out the flattening of the early-type mass-size relation, in agreement
with what we see in the right panel of Figure 4.4. With our low-z sample reaching 109 M ,
the flattening of the relation at low masses is clearly seen.
At the high stellar mass end (& 1011 M ), we find that the sizes of the early-type
galaxies tend to be slightly larger than the S03 relation. Guo et al. (2009) also found
a similar trend for early-type central galaxies (dashed-dotted lines in Figure 4.4). We
note that the early-types in our sample are morphologically selected and differ from the
early-types in S03 (defined as n > 2.5). In addition, as mentioned earlier, sizes of high
Sérsic index galaxies maybe underestimated in NYU-VAGC. The number of our earlytype galaxies in this stellar mass bin is low and provides only weak constraints. However,
Bernardi et al. (2012) also show similar behaviour at this high-mass end. They note that
the increase in the steepness of the mass-size relation for high-mass early-types could be
due to BCGs (see also Bernardi 2009, Bernardi et al. 2007). They also pointed out that
the steepness of the relation for early-types changes at these high stellar masses.
However, it is still not clear how the massive early-type galaxies are connected to
low mass ones (i.e.,. 1010 M ) and how the curvature of the mass-size relation arises for
these galaxies. Graham & Worley (2008) argued that the curved size-luminosity relation
for elliptical galaxies is expected from the assumption of varying profile shapes of these
galaxies with luminosity and they are not distinct types. However, Janz & Lisker (2008)
find evidence for the different behaviour of faint and bright early-types (see also Toloba
et al. 2012). Bernardi et al. (2012) also pointed out that the curvature of the early-type
scaling relations might arise from the presence of other components (e.g., a disk) with the
bulges of these galaxies. On the other hand, the characteristic stellar masses mentioned
above are predicted by semi-analytical simulations for spheroids in Shankar et al. (2013).
They show that the physical processes behind the evolution of spheroid sizes are different
below and above these masses, which might naturally explain the differing relations.
For late-type galaxies, we find that the stellar mass-size relation is mostly consistent
among our samples regardless of the exact definition. These relations are also consistent
with the mass-size relation for late-types in S03. However, the mass-size relation for
blue galaxies is somewhat offset to larger sizes and steeper than that derived for other
“late-type” classifications. This is likely a consequence of the strong color-size relation
pointed out by Franx et al. (2008), as well as the exclusion of red, edge-on spirals from
the blue sample. The size-mass relationship among the “early-type” samples appears to
be consistent regardless of the exact classification method used (elliptical, red, n > 2.5
and/or quiescent).
Finally, we artificially redshifted our sample to resemble z = 1 galaxies in WFC3 J125
band images and test the robustness of size and structural measurements at high redshifts.
We remeasure sizes of galaxies with single Sérsic profile fitting, a common method in the
literature for high redshift galaxies. Our results show that using single Sérsic profile fitting recovers the sizes of these redshifted galaxies without any systematics. Interestingly,
this demonstrates that size measurements at high-z are robust, despite the single-Sérsic
models failing for nearby massive early-types. We further verified this with simulations,
finding that once the small components of nearby two-component galaxies are smeared
out at high z, single Sérsic component fitting can adequately measure structural param75
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
eters. Image resolution is thus an important criterion for deciding whether to use single
Sérsic profiles. At a physical resolution . 1 kpc, where central bright components are
well-resolved, overly simple models like single Sérsic profiles can introduce biases, and
a multi-component or non-parametric method should be used.
4.7
Summary
We present the mass-size relation of a sample of nearby galaxies at z = 0.01 − 0.02,
dividing the sample based on several common classifications. We examined different
methods of size measurements in order to quantify the systematics associated in each
method. We also artificially redshifted these galaxies to z = 1 to test potential systematic
effects on their size measurements at high redshifts. From our results we find that:
• Nearby early-type galaxies with masses & 2 × 1010 M are not well fit with single
Sérsic profiles. Two component fits and non-parametric methods appear to provide
less-biased measurements. These methods give effective radii which are smaller
than those measured with single Sérsic fits.
• The stellar mass-size relation of both late-type and early-type galaxies are steep at
high masses (∼ 3 − 4 × 1010 M ) and flatten at low masses.
• Although single-Sérsic profile fits can be biased for nearby, well-resolved galaxies,
they provide robust sizes at high redshifts.
• The stellar mass-size relations of “spiral” and “elliptical” galaxies are not particularly sensitive to the precise definition of these categories (color, Sérsic index,
morphology, sSFR), with the exception of blue galaxies which follow a somewhat
higher and steeper relation.
4.8
Acknowledgments
We thank Rychard Bouwens for providing us CANDELS DEEP images. We also thank
Jarle Brinchmann, Daniel Szomoru, Roozbeh Davari and Simone Weinmann for useful
discussions.
Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the U.S. Department
of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS Web Site is http://www.sdss.org/.
The SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions. The Participating Institutions are the American Museum of Natural History, Astrophysical Institute Potsdam, University of Basel, University of Cambridge, Case
76
4.9 Appendix A
Western Reserve University, University of Chicago, Drexel University, Fermilab, the Institute for Advanced Study, the Japan Participation Group, Johns Hopkins University, the
Joint Institute for Nuclear Astrophysics, the Kavli Institute for Particle Astrophysics and
Cosmology, the Korean Scientist Group, the Chinese Academy of Sciences (LAMOST),
Los Alamos National Laboratory, the Max-Planck-Institute for Astronomy (MPIA), the
Max-Planck-Institute for Astrophysics (MPA), New Mexico State University, Ohio State
University, University of Pittsburgh, University of Portsmouth, Princeton University, the
United States Naval Observatory, and the University of Washington.
4.9
4.9.1
Appendix A
Failure of Single Sérsic Fitting at z = 0
Surface brightness profiles of galaxies in the local Universe rarely conform to simple analytic models (e.g., Allen et al. 2006, Simard et al. 2011). However, single Sérsic profile
fitting is widely used for measuring their structural parameters. In order to test whether or
not using single Sérsic fitting can bias the sizes of local galaxies with well-resolved profiles, we compare the half-light radii of our sample determined through different methods
described in the text. In Figure 4.10, sizes of galaxies measured by using single Sérsic
profile fitting are compared to their sizes derived from the non-parametric method. In the
left top panel, the comparison is shown for all galaxies and in the left bottom panel, the
relative median differences of sizes as a function of single Sérsic sizes are illustrated. As
can be seen, for small galaxies, the median differences are small, however for large galaxies, the systematic differences reach to ∼ 25%, i.e., sizes from single Sérsic profile fitting
are systematically larger than sizes from the non-parametric method for these galaxies. To
diagnose the systematics, we show the comparison for blue and red galaxies separately in
the middle and right panel of Figure 4.10, respectively. This shows that for blue ones the
systematics are less than ∼ 10%, except for the large size end (∼ 20%). However, for the
red galaxies the systematic trend is significant and increases towards larger and massive
objects (right bottom panel).
We also compare half-light radii from one-component Sérsic profile fitting and twocomponent Sérsic profile fitting in Figure 4.11. As it shows, sizes from single Sérsic fitting
are on average larger for large and massive ones than sizes from two-component models.
Specifically, for the red galaxies (right panels of Figure 4.11), there is a systematic bias
toward larger sizes.
The fact that sizes from single Sérsic fitting are larger than sizes from the non-parametric
method and two-component models, raises the question of how the half-light radii from
one-component Sérsic profile fitting could have been overestimated? As an example, a
typical profile of an early-type galaxy is shown in Figure 4.12. In the left panel, the observed profile is shown as black circles and the non-parametric fit overplotted as a blue
line. The red line is the best single Sérsic fit to the galaxy. The single Sérsic profile to the
whole observed profile does not match completely. This can be seen from the extra-light
in central regions of the residual profile which is illustrated in the lower left panel (green
77
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
Figure 4.10 – Top rows: The comparison between sizes of galaxies at 0.01 < z < 0.02 measured in
two different ways, i.e., using single component Sérsic profiles and non-parametric method, for all
galaxies (left panel), blue galaxies (middle panel) and red ones (right panel). Bottom panels, show
the relative differences between sizes of galaxies as a function of their one component Sérsic sizes.
The systematic differences between sizes of red galaxies increases up to about 40% and sizes based
on single Sérsic profiles are larger that non-parametric sizes.
line). The half-light size from single Sérsic fitting is illustrated by black diamond and is
larger than the one derived from non-parametric method (black triangle). The sizes derived using the residual-corrected method (Szomoru et al. 2010) is also shown as a black
star and as can be seen, this method also gives smaller size than the single Sérsic profile
fitting.
The light profile of this galaxy can be described better by adopting two-components
Sérsic profiles. In the right upper panel of Figure 4.12, the two-component models and
the total model are shown in dashed-dotted and solid red lines, respectively. The residual profile in the bottom right panel shows that this approach recovers most of the true
profile of the galaxy. The half-light size derived from this method for this galaxy is consistent with the non-parametric size and hence smaller than single Sérsic profile fitting.
It is worth testing whether the choice of PSF could introduce uncertainties. For that, we
remeasure sizes of this galaxy using a nearby non-saturated star as a PSF. This gives us
the same results as before. Therefore, we conclude that the SDSS synthetic PSFs do not
significantly affect.
This basically shows that if massive galaxies are well-resolved or contain multiple
components, structural measurements using a single analytical model could potentially
be biased. We also used simulations to show this (see section 4.3.3).
78
4.10 Appendix B
Figure 4.11 – The comparison between sizes of galaxies measured using one-component Sérsic
profile fitting and two-component Sérsic surface brightness profiles (for ∼ 77% of total sample). As
it can be seen, galaxies which their profiles could be estimated by two-component Sérsic profiles ,
have smaller two-component Sérsic sizes compare to one-component Sérsic sizes.
4.10
Appendix B
4.10.1
High Redshift Simulations
In order to check how well we can recover galaxy properties in J125 WFC3 images, we
perform simulations by generating ∼ 2300 synthetic simulated galaxies (assuming single
Sérsic surface brightness profile) with random properties within the following ranges:
20 < J125 < 26.5, 0.5 < n < 6.5 and 0 < re < 15 kpcz=1 , convolving with the J125 band PSF. We further add sky background by inserting the simulated galaxy images into
the empty regions of the real J125 -band images, and then remeasuring their structural
properties with the same procedure that we use for real galaxies.
The results of the simulations are shown in Figure 4.13. Synthetic simulated galaxies
are split into late-type (n < 2.5; left panel) and early-type (n > 2.5; right panel) according
to their input Sérsic indices. Then they are split into small bins over the size-magnitude
plane. The relative differences between input and output sizes (i.e, ∆(re )/rein ) in each
small bin of size-magnitude distribution are measured and shaded accordingly. Then we
overplot the distribution of artificially redshifted SDSS late-type and early-type galaxies on this size-magnitude plane, shown as blue and red points, respectively. Therefore,
systematics in size measurements for each redshifted object can be estimated from this
plot.
As it can be seen in Figure 4.13, for late-type galaxies the systematic differences over
the range of artificially redshifted SDSS galaxies are less than few percent. The systematic differences for early-type galaxies are also very small and only increase at the very
79
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
Figure 4.12 – The observed profile (black open circles) of a typical early-type galaxy. In the left
panel, the red line represents the best-fit one component Sérsic profile and the blue line shows
the best-fit one-dimensional Sérsic fit to the outer part of the galaxy (> r p etro9 0 for measuring
non-parametric size). In the right panel, the solid red line represent the total best fit model from
two-component models. The green lines in the bottom panels show the residuals from best-fits
of one component Sérsic profile. The size that derived using residual-corrected method (Szomoru
et al. 2010) is shown by a filled star and non-parametric size is shown by filled triangle. The filled
diamond shows the size of this galaxy using single component Sérsic profile. This plot shows that
profiles of galaxies at these very low redshift might be better explained by two components profiles.
80
4.10 Appendix B
faint magnitude end (i.e.J125 > 25). In general, comparing the distribution of artificially
redshifted SDSS galaxies to the uncertainties in each bin shows that the systematics are
expected to be very small (< 10% at most) for most of our sample. Therefore, we expect
that our size measurement procedure at high-z recovers the properties of galaxies without
introducing significant systematic biases.
The next set of simulations is designed to check our redshifting procedure. For this
purpose, we also create two-dimensional single Sérsic model galaxies with a similar range
of properties to the nearby SDSS galaxies. We assign them similar redshifts as our SDSS
galaxy sample. Then we use our code to artificially redshift these mock galaxies to z = 1,
insert them into J125 WFC3 images, and remeasure their properties using the method
described in section 4.5.1. The results are illustrated in Figure 4.14. In the left panel,
input sizes before redshifting and output sizes after redshifting are compared; in the right
panel, the comparison of input and output Sérsic indices is shown. The error bars come
from the dispersion between different realizations (i.e., using different empty regions).
This plot shows that the properties of these single Sérsic model galaxies can be recovered
after redshifting to z = 1 without any systematics and hence, our redshifting procedure
works robustly.
It is also discussed in the text that using single Sérsic profile fitting likely measures
the true structural parameters of galaxies at high redshifts. We verify this by simulating double-component galaxies and redshifting them to z = 1 (simulation (II) & Figure
4.7). In addition to these results, in order to test whether using low resolution images
washes out the sub-components and changes the galaxies measured structural parameters,
we remeasure galaxy sizes at z = 0 using single Sérsic profile fitting from their degraded
images; i.e., images which are binned (by a factor of 4) and Gaussian smoothed. Figure
4.15 shows the sizes (top row panels) and Sérsic indices (bottom row panels) of these
galaxies after smearing. It can be seen that sizes and Sérsic indices are smaller, especially
for red galaxies after degrading. The results simply illustrate that the bright central parts
of galaxies can bias the measurements of the structural properties of the galaxies in the
nearby universe,when a single Sérsic model is used. Also, it shows that resolution should
be taken into account for structural parameter measurements.
81
Chapter 4 – On the Robustness of z = 0 − 1 Galaxy Size Measurements
Figure 4.13 – The relative differences between input and output sizes of synthetic simulated galaxies (simulation III) are measured in small bins over the (input) size-magnitude plane (left panel:
n < 2.5 and right panel: n > 2.5). In each bin, the colors correspond to the median relative differences between recovered and input sizes of simulated galaxies. The red and blue points represent
the artificially redshifted SDSS galaxies (Left panel: Late-type galaxies and Right panel: Early-type
galaxies) on the size-magnitude plane. This shows that the systematics on size measurements of our
galaxies are very small over their size-magnitude distributions.
Figure 4.14 – Artificial single Sérsic model SDSS galaxies are created and then redshifted to z = 1
using our procedure. The left panel shows the comparison between their input sizes (at z ∼ 0)
to their sizes after artificially redshifted. The right panel illustrates the comparison between the
input and output Sérsic indices. The results indicate that our procedure recovers the parameters of
Sérsic model galaxies and there are no systematics on the measured sizes and Sérsic indices after
redshifting these mock galaxies.
82
4.10 Appendix B
Figure 4.15 – Comparison of sizes (top row) and Sérsic indices (bottom row) of galaxies at z = 0
derived from single component Sérsic fits of SDSS galaxies before (labled as One-component)
and after degrading the resolution (Labled as Binned; through binning and smoothing). This test
shows that using single Sérsic fitting for well-resolved images of nearby galaxies could result in
overestimating parameters such as sizes and Sérsic indices in compared to lower resolution images.
83
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5
Galaxy Zoo: Passive Red Spirals
K. L. Masters, Moein Mosleh, A. Kathy Romer, Robert C. Nichol, Steven P. Bamford,
Kevin Schawinski, Chris J. Lintott, Dan Andreescu, Heather C. Campbell, Ben
Crowcroft, Isabelle Doyle, Edward M. Edmondson, Phil Murray, M. Jordan Raddick,
Anže Slosar, Alexander S. Szalay, and Jan Vandenberg
Mon. Not. R. Astron. Soc., 2010, 405, 783-799
87
Chapter 5 – Galaxy Zoo: Passive Red Spirals
Abstract
We study the spectroscopic properties and environments of red (or passive) spiral galaxies found
by the Galaxy Zoo project. By carefully selecting face-on, disk dominated spirals we construct a
sample of truly passive disks (i.e., they are not dust reddened spirals, nor are they dominated by
old stellar populations in a bulge). As such, our red spirals represent an interesting set of possible
transition objects between normal blue spiral galaxies and red early types, making up ∼ 6% of latetype spirals. We use optical images and spectra from SDSS to investigate the physical processes
which could have turned these objects red without disturbing their morphology. We find red spirals
preferentially in intermediate density regimes. However there are no obvious correlations between
red spiral properties and environment suggesting that environment alone is not sufficient to determine if a galaxy will become a red spiral. Red spirals are a very small fraction of all spirals at low
masses (M? < 1010 M ), but are a significant fraction of the spiral population at large stellar masses
showing that massive galaxies are red independent of morphology. We confirm that as expected, red
spirals have older stellar populations and less recent star formation than the main spiral population.
While the presence of spiral arms suggests that major star formation cannot have ceased long ago
(not more than a few Gyrs), we show that these are also not recent post-starburst objects (having
had no significant star formation in the last Gyr), so star formation must have ceased gradually.
Intriguingly, red spirals are roughly four times as likely than the normal spiral population to host
optically identified Seyfert/LINER (at a given stellar mass and even accounting for low luminosity
lines hidden by star formation), with most of the difference coming from objects with LINER-like
emission. We also find a curiously large optical bar fraction in the red spirals (70 ± 5% verses
27 ± 5% in blue spirals) suggesting that the cessation of star formation and bar instabilities in spirals are strongly correlated. We conclude by discussing the possible origins of these red spirals.
We suggest they may represent the very oldest spiral galaxies which have already used up their
reserves of gas - probably aided by strangulation or starvation, and perhaps also by the effect of bar
instabilities moving material around in the disk. We provide an online table listing our full sample
of red spirals along with the normal/blue spirals used for comparison.
88
5.1 Introduction
5.1
Introduction
The advent of large galaxy surveys like the Sloan Digital Sky Survey (SDSS) in which
photometry (and therefore colours) are readily available for millions of objects has lead to
the common use of optical colours to define “early" and“late" type galaxy samples (e.g.
Simon et al. 2009, Salimbeni et al. 2008, Lee & Pen 2007, Croton et al. 2007, Bundy et al.
2006, Cooray 2005). This method is particularly favoured since obtaining morphologies
for large numbers of galaxies has until recently been impossible. This simplification
is justified since it has been shown many times that the majority of galaxies follow a
strict colour-morphology relation. For example Mignoli et al. (2009) argued that 85% of
galaxies to z∼1 are either red, bulge-dominated galaxies or blue, disk dominated galaxies;
while Conselice (2006) showed a similar result for 22000 low redshift galaxies (both using
automated methods for morphological classification).
However the clear correlation between colour and morphology is surprising, given
that the colours of galaxies are determined primarily by their stellar content (and therefore
their recent star formation history, mostly within the last Gyr) while the morphology is
primarily driven by the dynamical history. The clear link between colour and morphology
then gives a strong indication that the timescales and processes which drive morphological
transformation and the cessation of star formation are strongly related - at least in most
cases. In this paper however, we consider a class of object (the red spirals) where the link
described above appears to be broken.
Since the morphology-density relation was first quantified (Dressler 1980) many mechanisms have been proposed for the transformation of blue, star forming, disk galaxies in
low density regions of the universe, to red, passive, early type galaxies in clusters. A recent review of many of the proposed mechanisms, and the evidence supporting them, can
be found in Boselli & Gavazzi (2006). Clearly two things must happen for a star forming
blue spiral galaxy to turn into a passive red early type. First, star formation must cease
(which can indirectly alter the morphology by causing spiral arms and the disk in general
to fade, possibly producing an S0 or lenticular from a spiral), and secondly, in order to
produce a bona fide elliptical the same, or a different process must also dynamically alter
the stellar kinematics of the galaxy.
The presence of an unusually red or passive (i.e.,. non-star forming) population of
spiral galaxies in clusters of galaxies was first noticed by van den Bergh (1976) in the
Virgo cluster. Later studies of distant cluster galaxies in Hubble Space Telescope (HST)
imaging also revealed a significant number of so-called “passive” spiral galaxies with a
lack of on-going star formation (Couch et al. 1998; Dressler et al. 1999; Poggianti et
al. 1999). Passive late-type galaxies were identified at lower redshifts in the outskirts
of SDSS clusters by Goto et al. (2003), using concentration as a proxy for morphology.
Passive spirals in a cluster at z ∼ 0.4 were studied by Moran et al. (2006) who found star
formation histories from GALEX observations consistent with the shutting down of star
formation from strangulation (as described by Bekki et al. 2002). Passive spirals have
also been revealed in a cluster at z ∼ 0.1 in the STAGES survey, using HST morphologies Wolf et al. (2009), rest frame NUV-optical SEDs (Wolf et al. 2005) and 24µm data
from Spitzer (Gallazzi et al. 2009). In that series of papers, “dusty red late-types" and
89
Chapter 5 – Galaxy Zoo: Passive Red Spirals
“optically passive late-types" are found to be largely the same thing, with a non-zero (but
significantly lowered) star formation rate revealed by the IR data.
Red spirals/late types have been studied in several recent papers (Lee et al. 2008,
Deng et al. 2009, Hughes & Cortese 2009, Cortese & Hughes 2009), as well as Mahajan
& Raychaudhury (2009) who talk about blue passive galaxies (i.e., galaxies with blue
colours, but showing no indication of recent star formation in their spectra) which mostly
appear to have late type morphologies and have very recently shut down star formation.
These might be the progenitors of the red spirals. Bundy et al. (2010) have studied the
redshift evolution of red sequence galaxies with disk like components in COSMOS and
use it to estimate that as many as 60% of spiral galaxies must pass through this phase on
the way to the red sequence - making it an important evolutionary step.
The Galaxy Zoo project (Lintott et al. 2008) revealed the presence of a significant
number of visually classified spiral galaxies which are redder than the blue cloud (between 16-28% of the total galaxy population depending on environment, Bamford et al.
2009). In this paper we study in more detail the physical properties and environments
of this population of red spiral galaxies. Galaxies drawn from this population have the
morphological appearance of spiral galaxies with a distinct spiral arm structure, but have
rest-frame colours which are as red as a typical elliptical galaxy, indicating little or no recent star formation activity. We are studying these objects in order to identify the physical
process which is most important in their formation.
It is clear that all spiral galaxies can be affected by various physical processes as they
evolve – in this paper we attempt to identify which are most important for red spirals,
asking how they are able to shut down star formation while retaining their spiral morphology. A list of possible mechanisms includes processes that depend on environment such
as: (1) galaxy-galaxy interactions: in high density regions there is an increased probability
of interaction with other galaxies. Most major mergers destroy spiral structure (Toomre
& Toomre 1972) unless they involve very gas rich progenitors (Hopkins et al. 2009), but
some interactions can be quite gentle (e.g., Walker, Mihos & Hernquist 1996), for example minor-mergers, tidal interactions etc. (2) Interaction with the cluster itself also occurs
and can remove the gas which forms the reservoir for star formation. This can be due to
tidal effects (e.g. Gnedin 2003), or interaction with the hot intercluster gas, either through
thermal evaporation (Cowie & Songaila 1977) or ram pressure stripping (Gunn & Gott
1972). (3) Processes like harrassment (Moore et al. 1999) and starvation or strangulation
(Larson et al. 1980, Bekki et al. 2002) have also been shown to have a significant effect
on late type galaxies. Harrassment refers to the heating of gas by many small interactions,
while starvation or strangulation refers to the gradual exhaustion of disk gas after the hot
halo has been stripped away. These mechanisms both occur at much larger cluster radii
(i.e., lower densities) than the "classic" environmental effects. Internal mechanisms could
be more important. For example, (4) the latest semi-analytical models of galaxy formation all invoke feedback from a central massive black hole (or active galactic nuclei;
AGN) to explain the most massive red elliptical galaxies (Granato et al. 2004, Silk 2005,
Schawinski et al. 2006, Croton et al. 2006, Bower et al. 2006), although the effect of this
process on disk galaxies has been studied less, it still may have some effect (Okamoto,
Nemmen & Bower 2008). (5) Another culprit could be bar instabilities in spiral galaxies
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5.2 Sample Selection and Data
which drive gas inwards (eg. Combes & Sanders 1981) and may trigger AGN activity
and/or central star formation (eg. Shlosman et al. 2000), perhaps using up the reservoir
of gas in the outer disk and making spirals red. (6) Finally red spirals could simply be old
spirals which have used up all their gas in normal star formation activities without having
any major interactions. In normal spirals, the gas that feeds ongoing star formation comes
from infall of matter from a reservoir in the outer halo (Boselli & Gavazzi 2006). As first
suggested by Larson, Tinsley & Caldwell (1980) and expanded by Bekki et al. (2002) the
removal of gas from this outer halo (“strangulation", or “starvation") will cause a gradual
cessation of star formation proceeding over several Gyrs.
We describe the sample and data along with the selection of the “red spirals" in more
detail in Section 5.2. In Section 5.3 we discuss the stellar populations and star formation
history of the red spirals. In Section 5.4 we discuss their environment and the environmental dependence of star formation. The impact of AGN is considered in Section 5.5,
and bar instabilities are discussed in Section 5.6. In Section 5.7 we discuss the plausible mechanisms for formation of the red spirals and future directions which could be
taken to distinguish between them. We present a summary and conclusions in Section
5.8. The adopted cosmological parameters throughout this paper are Ωm = 0.3, ΩΛ = 0.7
and H0 = 70 km s−1 Mpc−1 .
5.2
Sample Selection and Data
The sample of visually classified spiral galaxies used in this paper is drawn from the
Galaxy Zoo (GZ1) clean catalogue (Lintott et al. 2008) which, by an order of magnitude,
is the largest morphologically classified sample of galaxies. To make this unprecedented
sample, over 160,000 volunteers visually inspected images of SDSS galaxies independently via an internet tool (the original GZ1 sample was selected from the SDSS Data
Release 6; Adelman-McCarthy et al. 2008). For more information on the classification
process in GZ1 and the conversion of multiple classifications per galaxy to redshift bias
corrected type “likelihoods" see Lintott et al. (2008) and Bamford et al. (2009). In brief,
we use the spiral likelihood pspiral and (in order to tell if the spirals have visible spiral
arms) the quantities pCW and pACW which describe how likely the spiral is to have “clockwise" or “anti-clockwise" arms respectively.
We make a volume-limited sample of galaxies from the GZ1 catalogue by selecting
only objects from the SDSS Main Galaxy Sample (Strauss et al. 2002) with spectroscopic
redshift between 0.03 < z < 0.085 and by limiting the sample to an absolute magnitude of
Mr < −20.17. This redshift range is picked to remove problems with peculiar velocities
at the low redshift end (which would bias distance dependent quantities) and the upper
limit is chosen as a compromise between sample size and luminosity range, (and also a
redshift up to which reliable local densities - see below - are available).
Our photometric quantities are taken from the SDSS DR6 Adelman-McCarthy et al.
(2008). We use model magnitudes for colours, and Petrosian magnitudes for total luminosities. We also make use of shape/structural parameters from SDSS, namely the axial
ratio (a/b) from the r-band isophotal measurement which is used as a proxy for disk incli91
Chapter 5 – Galaxy Zoo: Passive Red Spirals
nation; and fracdeV (or fDeV ) - the fraction of the best fit light profile which comes from
the de Vaucouleurs fit (as opposed to the exponential fit) and which is used as a proxy for
bulge size in these visually classified spirals (as discussed in Masters et al. 2010).
SDSS 3” fibre spectra are available for all galaxies in our sample. We use equivalent
widths (EW) and absorption line indices measured for SDSS DR7 spectra by the MPAGarching group whose methods are described in Tremonti et al. (2004)1 .
As an estimate of stellar mass, we use the empirical fit in Baldry et al. (2006) which
gives a stellar mass-light ratio in the r-band as a function of the (u−r) colour of the galaxy
(based on calculations of stellar masses from Kauffmann et al. (2003a) and Granato et al.
(2004) using the Bruzual & Charlot (2003) stellar population models). Obviously this
is an oversimplification of the calculation of stellar masses, not taking into account the
varied star formation histories of galaxies with the same colour and luminosity; however
the method does have the advantage of being simply related to only two measured physical
properties of the galaxies (colour and luminosity).
The local galaxy densities used in this paper are identical to those used in Bamford et
al. (2009). The details of the method are described in Baldry et al. (2006). Briefly, ΣN
is determined by N/(π dN2 ), where dN is the projected distance to the Nth nearest galaxy
(with Mr < −20) within cz±1000 km s−1 . The final value used, Σ, is the average of ΣN
for N = 4 and 5. These local densities include a correction for redshift incompleteness
due to fiber collisions by considering the photometric redshift likelihood distributions for
galaxies without spectra. Typical values of Σ range from 0.05 Mpc−2 in voids to 20 Mpc−2
in clusters (Baldry et al. 2006).
5.2.1
Selection of Red Spiral Galaxies
We wish to select from the GZ1 volume limited sample a subset of truly passive red diskdominated spiral galaxies (i.e., not dust reddened, nor red because they are dominated
by bulge emission). We use a cut in the spiral likelihood (corrected for the small bias
described in the Appendix of Bamford et al. 2009) of pspiral ≥ 0.8. Two things can
complicate the picture in a sample selected purely by colour and spiral likelihood:
1. Dust reddening of edge-on spiral galaxies
2. Contamination by early-type spirals and/or S0s.
Masters et al. (2010) show that the impact of dust reddening can be significant for inclined spiral galaxies, and that spiral galaxies with large bulges (as measured by fracdev)
are intrinsically red. Therefore with no cuts on inclination or bulge size, a red spiral sample will be dominated by inclined dust reddened spirals, and spirals with large
bulges. We choose in this work to study only the most face-on spiral galaxies, requiring
log(a/b) < 0.2. This will minimize the impact of dust reddening on the sample (although
we note that even at face-on spirals can be dust reddened; for example Masters et al. 2010
find a median Balmer decrement of 0.3 ± 0.3 mags in the centres of face-on GZ1 spirals).
1
http://www.mpa-garching.mpg.de/SDSS/
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5.2 Sample Selection and Data
Figure 5.1 – Colour magnitude diagram of the“face-on" (log(a/b) < 0.2) volume limited clean
GZ1 sample. The greyscale contours show the location of galaxies in the red sequence and blue
cloud. The solid line indicates the blue edge of the red sequence of GZ1 early types. All red spirals
(having visible spiral arms) are shown colour coded by fracdev (blue: fDeV < 0.1, which roughly
corresponds to type Sd; green: 0.1 < fDeV < 0.5, or Sb-Sc; orange: 0.5 < fDeV < 0.9, or Sa-S0/a;
red: fDeV > 0.9 which are spirals having very large bulges - but note that spiral arms are still visible
here, so these are not S0s.). Our final red spiral sample selects only those galaxies with fDeV < 0.5
(i.e., the blue and green points) to select against spirals dominated by light from the bulge.
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Chapter 5 – Galaxy Zoo: Passive Red Spirals
Both Lintott et al. (2008) and Bamford et al. (2009) show that contamination of S0s
into the GZ1 clean spiral sample should be small - an estimate of 3% contamination is
made. Furthermore we use fracDev ≤ 0.5 to select “disky" spirals. As illustrated in
Masters et al. (2010) using a small sample of GZ1 spirals with B/T from the Millennium
Galaxy Catalogue (Liske et al. 2003) this selects spiral galaxies with B/T < 0.25, or
of types ∼Sb–Sc (where this relation between typical B/T and Hubble type comes from
Simien & de Vaucouleurs 1986). One caveat to note here is that both fracdeV and B/T
are light-weighted quantities, so in using the same fracdeV limit for both red and blue
spirals will results in the red spirals having a slightly lower upper limit in bulge mass
fraction than the blue spirals. This slight bias should only make the conclusions below
stronger, as the red spirals may on average be more disk dominated than the comparison
blue spiral sample.
Finally we require that spiral arms be visible to GZ1 users, using pCW > 0.8 or pACW >
0.8. The presence of spiral arms gives an indication that these red spirals may have only
recently stopped forming stars, since spiral structures are expected to persist for only a
short time after star formation ceases (for example Bekki et al. (2002) found that spirals
arms persisted for only a few Gyrs after the gas which provides the reservoir for ongoing
star formation was removed).
We show in Figure 5.1, the colour magitude diagram of the “face-on" volume limited
clean GZ1 sample. The locus of the galaxy population is illustrated by the greyscale
contours, and the positions of visually classified spirals in the red sequence are hi-lighted.
The best fit to the red sequence of early types (pel ≥ 0.8) is (g − r) = 0.73 − 0.02(Mr + 20),
and the scatter is σ = 0.1 mags. We therefore define the blue edge of the red sequence as
(g − r) = 0.63 − 0.02(Mr + 20),
(5.1)
which is indicated by the solid line in Figure 5.1, and define a red spiral as one redder
than this limit. Since the limit depends on magnitude, we point out that in our definition a
blue spiral with a high luminosity could actually be slightly redder than a red spiral with
a low luminosity.
The colour cut used here to select red spirals is different from than that used by either
Bamford et al. (2009), who used a cut in (u − r) vs. stellar mass; or Skibba et al. (2009),
who used k-corrected (to z = 0.1) magnitudes, which reddens the red sequence by ∼ 0.1
mags. Our cut is more conservative that either of those papers; they effectively select red
spirals as being redder than most of the blue cloud, while we select red spirals to be as
red as most elliptical galaxies. The difference in the two approaches is especially large
at the low luminosity/stellar mass end of the galaxy population where (as can be seen in
Figure 5.1) the blue cloud is significantly bluer than the red sequence. However, the major
difference in our sample and all previous ones used to study passive or red spirals is that
we have made an effort to remove dust reddened inclined spirals, which has not been done
before (e.g. Bamford et al. 2009, Skibba et al. 2009, Wolf et al. 2009).
Our final sample consists of 5433 face-on disky spirals with visible spiral arms, 294 of
which (or 6%) are classified as red. In what follows, we refer to the remaining 5139 spirals as our comparison sample a refer to them as either “blue" spirals, or “normal" spirals.
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5.2 Sample Selection and Data
Figure 5.2 – This figure shows the fraction of all face-on, disky GZ1 spirals which are found to be
red (i.e., Nred /Nspiral ) as a function of (1) redshift, (2) fracdeV (or bulge size), (3) stellar mass, and
√
(4) r-band absolute magnitude. N counting errors are shown.
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Chapter 5 – Galaxy Zoo: Passive Red Spirals
We provide an electronic table listing the SDSS names, positions and optical photometry parameters used in this paper for these two samples (our red spirals and comparison
sample). A sample of this table is provided in the Appendix.
Figure 5.2 shows the redshift, fracdeV (for bulge size), luminosity and stellar mass
distributions of the red spirals compared to all spirals (in the face-on, disky sample). Red
spirals are more likely to be found at the higher luminosity and larger fracdeV (and hence
larger bulge) end of the spiral distribution showing that as is well known, luminous spirals
with large bulges (earlier spiral types) are more likely to be red. There is a slight trend
with redshift which can be explained by effect of the luminosity distribution in a volume
limited sample.
As also discovered by Wolf et al. (2009), red (or passive) spirals are an insignificant
fraction of the total spiral population at stellar masses below ∼ 1010 M (although note
that Bamford et al. 2009 shows that in the densest regions the few remaining low mass
spirals are mostly red) but are a significant fraction of spirals at large stellar masses. This
shows that massive galaxies are red independent of morphology. However we note here
that this mass distribution may be slightly biased by our decision to classify spirals as red
only if they are as red as ellipticals. This cut biases against low mass red spirals as the
blue cloud at low masses/luminosities moves further from the red sequence. Our sample
is also incomplete for red objects below 1010.3 M which corresponds to the luminosity
limit for the reddest objects. Finally, we comment that the stellar population models of
Bruzual & Charlot (2003) on which the Baldry et al. (2006) stellar masses are based,
struggle to make red low mass objects (since all their red objects must be very old, and
therefore have very high mass-light ratios) so the use of this stellar mass estimate may
anyway bias high the masses of the redder spirals. A more detailed modelling of the star
formation history using stellar populations which account for the known populations of
young red stars (the thermally pulsing asymptotic giant branch (TP-AGB) phase included
in Maraston 2005) would provide more reliable stellar masses for these objects.
Figure 5.3 shows example images of red and blue spirals from our sample of faceon disky spirals. The blue spirals shown have been picked to have similar redshifts and
absolute magnitudes as the red spiral directly above them. A range of redshifts are shown.
In these gri colour composite images the colour difference between red and blue spirals
is quite clear to the eye. Figure 5.4 shows SDSS fibre spectra for the same galaxies in
Figure 5.3 (arranged in the same order), and even in this small sample it is clear that red
spirals show less (but not zero) nebular emission from on-going star formation than the
blue spirals (since they have smaller Hα emission lines) and have older stellar populations
(the break at ∼ 4000Å is larger in the red spirals than the blue spirals).
5.3
Star Formation in Red Spirals
In this section, we use the SDSS fibre spectra to study in more detail the star formation
history and mean stellar age of “red spiral" galaxies with reference to our comparison
sample of blue spirals. Spectroscopic parameters are ideal for studying the stellar content
of galaxies. A full star formation history model fit to the galaxy spectra is beyond the
96
5.3 Star Formation in Red Spirals
Figure 5.3 – Top row: examples of face-on, red, disky spirals with visible arms (as described in
the text), Bottom row: face-on, blue, disky spirals picked to have similar redshifts, absolute r-band
magnitudes, angular sizes and fracdeV values as the red spiral immediately above them. Images
are SDSS gri composites, all 10 × 10 in size (these are some of the largest angular size galaxies in
our sample). The size of the SDSS fibre is indicated at top left of the top left image. Galaxies are (in
red/blue pairs from left to right): SDSS J131428.83+334109.2 and SDSS J130058.63+395132.1 at
z ∼ 0.04, Mr ∼ −20.3; SDSS J082959.05+304340.1 and SDSS J100515.00+513545.9 at z ∼ 0.05
and Mr ∼ −21.7; SDSS J104034.48+004902.6 and SDSS J123317.60+575620.1 at z ∼ 0.07 and
Mr ∼ −22.6; and SDSS J134248.47+145553.5 and SDSS J155357.57+383923.9 at z ∼ 0.08 and
Mr ∼ −22.3.
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Chapter 5 – Galaxy Zoo: Passive Red Spirals
Figure 5.4 – SDSS fibre spectra of the spirals shown in Figure 5.3. Even in the central 300 , these
spirals are clearly different in colour; the red spirals (top) mostly have continuum emission which
increases towards long wavelengths (i.e., a red colour), while the blue spirals have continuum levels
decreasing in that direction. Also note the significantly larger Hα emission in the spectra of the blue
spirals (indicative of more ongoing star formation), and the larger break at ∼ 4000Å in the spectra
of the red spirals (indicating an older stellar population).
98
5.3 Star Formation in Red Spirals
Figure 5.5 – Balmer decrement in the SDSS fibre (expressed in magnitudes of extinction between
Hα and Hβ) as a function of stellar mass for the blue (blue squares) and red (red dots) face-on disky
spirals. Error bars indicate our estimate of the 1σ error on the median value.
scope of this paper, but absorption line indices such as HδA and the 4000Å break strength
provide information about stellar content and recent star formation history of a galaxy,
while Hα and [OII] emission lines can indicate the presence of recent star formation.
5.3.1
Dust Content
Before proceeding to use the spectral information to study the stellar content of the red
spirals we first want to check the dust content of the red spirals relative to the blue spirals.
It is possible that the red colours of the spirals could be due to an enhanced amount
of extinction and reddening from dust (even in our specially selected sample of face-on
spirals designed to minimize dust effects) rather than an ageing stellar population from a
lack of recent star formation. In fact Wolf et al. (2009) find that ongoing star formation
in their red spirals is obscured, although we note again that their objects include dust
reddened inclined spirals which we have removed.
In order to quantify the levels of extinction we compare the difference in flux between
the first two lines in the Balmer series (Hα and Hβ). The expected flux ratio between
these lines is <int = Fα /Fβ = 2.76, and has only a mild dependence on the temperature
of the gas emitting the radiation (from <int = 3.30 at 2500◦ K to <int = 2.76 at 20000◦ K;
Osterbrock 1989). Therefore, deviations from the expected ratio can be used to measure
the relative extinction between Hα (at 6562.8 Å in the r-band) and Hβ (at 4861.3 Å in
99
Chapter 5 – Galaxy Zoo: Passive Red Spirals
g-band). The relative extinction between these two wavelengths in magnitudes is
E(Hβ − Hα ) = 2.5 log
<obs
,
<int
(5.2)
which is equivalent to a colour in narrow band filters at these wavelengths.
In Figure 5.5, we plot the Balmer decrements from the 3” SDSS fibre of blue and
red spirals as a function of their stellar mass. This figure clearly indicates an increase in
dust content of blue spirals as a function of stellar mass to a maximum at around M ∼
1010.5 M . The trend is less clear in the red spirals where the numbers are significantly
smaller, but tentatively supports a drop off in dust content for the highest mass objects (as
also seen in Masters et al. 2010). A negligible number of face-on spirals (either red or
blue) have zero Balmer decrements in their central regions, showing that dust reddening
always plays some role. However, we see no evidence for red spirals having significantly
larger dust content than blue spirals at a given stellar mass (except perhaps in the lowest
mass bin of the red spirals) and thus argue that the difference in colour is not due to
differences in the dust content of the two populations.
5.3.2
Recent Star Formation History
Following the method in Kauffmann et al. (2003a), we use the Balmer absorption-line
index HδA and the Dn (4000) break to estimate mean stellar ages and recent star-burst
activity of our sample.
The observed spectrum of a galaxy is the combination of flux from many stars. In
galaxies with old stellar populations there are a large number of stellar absorption lines
(mostly from ionized metals) which crowd together at around 4000Å. The 4000Å break
which they produce is the strongest discontinuity seen in the optical spectrum of a galaxy.
In galaxies with a younger stellar population, there are many more hot stars, and the
metals in them are multiply ionized. This significantly reduces the strength of the break,
making it a good indicator of the mean age of a galaxy’s stellar population. We follow
Kauffmann et al. (2003a) and represent the strength of the 4000Å break by the Dn (4000)
index (Balogh et al. 1999).
HδA absorption lines can be used to trace the recent (≤ 1 Gyr) star formation activity
of galaxies (Kauffmann et al. 2003a). HδA in the integrated galaxy spectra is almost
entirely the contribution of A-type stars. The peak of this absorption feature thus occurs
roughly 1 Gyr after a burst of star formation, once O and B stars have expired and the
integrated light is dominated by A stars.
Histograms of the distribution of the two measurements for all the red and blue spirals
are shown in Figure 5.6. In Figure 5.7, we plot HδA versus Dn (4000) for our blue and
red spirals samples split into 4 bins of stellar mass (starting at log(M? /M ) = 10.3 where
the sample is complete for both red and blue spirals). These figures illustrate that the red
spirals, on average (luminosity weighted), have both older stellar populations and are less
likely to have had significant bursts of star formation in the last Gyr (they have larger
mean Dn (4000) and smaller HδA ). The data are overplotted on the models of Kauffmann
et al. (2003a) showing the regions covered by their starburst (filled triangle), poststarburst
100
5.3 Star Formation in Red Spirals
Figure 5.6 – Histograms of the distribution of HδA and Dn (4000) for the red and blue spiral samples
(solid and dotted lines respectively). The y-axis shows the number in a given bin, relative to the
total number in the respective sample. Counting errors are shown on the histogram for red spirals;
due to the larger numbers of blue spirals the errors on those histograms are significantly smaller.
(open triangle) and quiescent galaxies (filled squares). We can clearly see that red spirals
at all masses are unlikely to fall in the part of the Dn (4000)-HδA plane which is occupied
by star bursting or post star bursting galaxies (i.e.,. they are not above the main locus
of points), but that a significant fraction do lie in the part of the plane in which galaxies
are expected to have formed an insignificant fraction of their stars in the last 2 Gyrs
(Kauffmann et al. 2003a), as well as in the mid-region where galaxies are expected to
have mixed star formation histories (ie. a mix of recent and much older star formation).
In contrast, many of the blue spirals (especially at the lower stellar masses) are in the
region of the plane occupied by galaxies with mixed star formation histories, although
there are also star-burst/post star-burst as well as more quiescent blue spirals.
Figure 5.7 illustrates clearly the mass dependence of spiral star formation history;
lower mass spirals are more likely to have had recent star formation. This is true both for
red and blue spirals in our sample, however in any given mass bin the red spirals have
both lower HδA and larger Dn (4000) than equivalent blue spirals. It is clearly not stellar
mass alone which is determining the SF history of the red spirals.
The range of stellar ages of red spirals are similar to early-type galaxies (at least to
first order considering the range of Dn (4000) – this does not account for metallicity effects which could cause a systematic offset) and they have not experienced recent burst of
stars (in the last 1-2 Gyr); i.e. they are not post-starburst galaxies. However, the presence
of spiral arms gives an indication that these red spirals must have recently been forming some stars, since spiral structures are expected to persist for only a short time after
star formation completely ceases. The prevailing model for the origin of spiral structure
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Chapter 5 – Galaxy Zoo: Passive Red Spirals
Figure 5.7 – HδA versus Dn (4000) is plotted for our sample of blue and red face-on, disky spirals. In
each panel the blue spirals are shown by grey circles, and the red spirals are shown by red triangles.
The red and blue error bars indicate the interquartile ranges for the red and blue spirals respectively.
The different panels show the evolution with stellar mass, with the lowest mass galaxies at the upper
left, down to the highest masses at the lower right. The red spiral galaxies on average show older
stellar populations and less recent bursts of star formation in every mass bin. The data are plotted
over galaxy models of Kauffmann et al. (2003a) showing regions covered by their starbursting (filled
triangle), post starburst (open triangle) and quiescent (filled squares) galaxies.
102
5.4 The Effect of Environment
in disk galaxies is the density wave theory proposed originally by Lin & Shu (1964).
Discussing observations available at the time, which showed that galaxies without significant amount of interstellar gas do not have prominent spiral patterns, Lin & Shu (1964)
suggest that any spiral structure, even if present in the old stellar population would not
be visible, due to a lack of gas and star formation. More recent numerical simulations
support this early picture of a relatively rapid fading of spiral arms after star formation
ceases. For example Bekki et al. (2002) found that spiral arms persisted for only a few
Gyrs after the gas which provides the reservoir for ongoing star formation was removed.
Observationally Ishigaki et al. (2007) use spatially resolved spectroscopy of the passive
spiral SDSS J074452.52+373852.7 to show that this galaxy probably stopped forming
stars about 1-2 Gyrs ago - and it’s spiral structure is still just visible. Follow-up integral
field unit, and/or higher S/N spectroscopy for a representative sample of the red spirals
could measure population ages and test this picture further. Such work is planned.
In the red spirals, current star formation is significantly reduced compared to the normal/blue spirals, even at fixed stellar mass but it does not appear to have completely
stopped in all objects (as we will see below). Major amount of star formation cannot have
ceased abruptly recently (as they are not post-starburst), or very long ago (more than a
few Gyrs because of the presence of spiral arms). It is therefore possible to conclude that
star formation either ceased abruptly in the red spirals between the post-starburst and spiral arm fading time scales (about one to a few Gyrs ago) or that there has been a gradual
cessation of star formation in the red spirals over the past few Gyrs.
5.4
The Effect of Environment
The morphology-density relation (Dressler 1980) revealed that spiral galaxies favour
lower density environments than early-types. However, recent work (Ball et al. 2008,
Bamford et al. 2009, Skibba et al. 2009, Deng et al. 2009, e.g.) has shown that the
colour-density relation is stronger than the morphology-density relation (ie. at a fixed
morphology galaxies in higher density environments are redder, but at a fixed colour,
there is little morphology-density dependence). We have already seen (Bamford et al.
2009, Skibba et al. 2009) that GZ1 red spirals are more common in high density regions
(and conversely blue early-types are more common in low density regions; Schawinski et
al. 2009b). There are also clear suggestions in both Bamford et al. (2009) and Skibba et al.
(2009) that the peak of the red spiral distribution occurs in intermediate density regions.
Therefore environment is clearly a candidate for driving the process which turns spirals
red. As discussed in Section 5.1, various environmental mechanisms have been proposed
to suppress star formation and turn galaxies red in high density regions. In this section
we will consider the effect of environment on the red spirals in particular, looking at their
preferred locations, and tracers of their star formation as a function of local density.
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Chapter 5 – Galaxy Zoo: Passive Red Spirals
Figure 5.8 – Fraction of red spiral galaxies (red solid line) and blue spirals (blue dashed line)
relative to all types of SDSS galaxies in our volume limited sample plotted versus environment as
measured by Σ. The error regions are also shown; note that the binning is the same for both red and
blue spiral samples, and adjusted to have ∼ 30 red spirals per bin.
5.4.1
The Environments of Red Spirals
In Figure 5.8, we present the fraction of galaxies in our red and blue spiral samples (relative to the full volume limited galaxy sample) versus the local galaxy density. We confirm
the previous findings that red spiral fraction increases with local galaxy density, along
with the well established observation that the fraction of blue (or normal) spirals decreases. This figure suggests that the red spiral fraction peaks at intermediate densities,
around Σ = 1 Mpc−2 , inside the infall radius of a typical cluster, but not in their cores (see
Figure 5 of Bamford et al. 2009 for the correlation of Σ with distance to the nearest cluster
centre, this level of Σ corresponds to d ∼ 5 − 15 Mpc depending on the richness of the
cluster - for example it could be quite close in to a poor group, or much further away from
a rich cluster). In order to look at the impact of close neighbours, and not just local density, we also consider the (projected) distance to the nearest neighbour (within 100 kms−1
in the SDSS DR6 Spectroscopic Galaxy Sample). Figure 5.9 shows the fraction of red
and blue spirals in our face-on disky spiral sample as a function of this distance, showing
that red spirals are a lot more likely to have close neighbours than blue spirals. (Of course
Σ and the distance to the nearest neighbour are correlated - galaxies with a higher Σ will
naturally have a nearer closest neighbour, and we have not attempted to disentangle the
two measurements here.)
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5.4 The Effect of Environment
Figure 5.9 – Fraction of red spiral galaxies (red solid line) and blue spirals (blue dashed line)
relative to all types of SDSS galaxies in our volume limited sample as a function of projected
distance to nearest neighbour. The error regions are also shown; note that the binning is the same
for both red and blue spiral samples, and adjusted to have ∼ 30 red spirals per bin.
5.4.2
Environmental Dependence of Star Formation
We now study the environmental dependence of star formation tracers in our samples of
red and blue spirals. In Figure 5.10, we show the median equivalent widths (EW) of [OII]
and Hα as a function of local galaxy density for both blue and red face-on disky spirals.
At all densities, red spirals have significantly lower but non-zero equivalent widths in
these two tracers of ongoing star formation, but interestingly there are no significant trends
with local density in either population, neither do we see any evidence for a change in the
distribution of the quantities with environment (consistent with the findings of Bamford
et al. 2008 for Hα in the galaxy population as a whole). There is perhaps a hint that the
[OII] EW decreases with density for red spirals - a straight line fit to this trend has a ∼ 2σ
significance (a slope of −1.0 ± 0.4). We also see a slight increase in the Hα EW in blue
spirals at very high density, which may be related to interaction triggered star formation
in this population - or perhaps a higher rate of AGN contamination in blue spirals in high
density regions. This figure includes all galaxies, including those classified as AGN by
their optical spectra (see Section 5.5 below), however in Section 5.5 we will show there is
a higher AGN fraction in the red spirals than the blue, so removing AGN contamination
from these lines will only make the difference between red and blue spirals stronger.
Figure 5.11 shows similar relations to that shown in Figure 5.10 for the tracers HδA
and Dn (4000) (as discussed in Section 5.3, these are tracers of recent starbursts and the
mean age of the stellar population respectively). Again we see that at all densities these
indicators show less recent star formation and older stellar populations in red spirals than
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Figure 5.10 – The median equivalent widths of [OII] and Hα as a function of local galaxy density.
Blue and red spirals are shown as blue stars/red dots respectively. Error bars show our estimate of
the 1σ error on the median value.
Figure 5.11 – Median values of HδA (a tracer of recent star formation) and Dn (4000) (a tracer of
average stellar age) as a function of local galaxy density. Blue and red spirals are shown as blue
stars/red dots respectively. Error bars show our estimate of the 1σ error on the median value.
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5.5 The Impact of AGN
Figure 5.12 – Distribution of face-on disky red spiral galaxies in BPT diagram. The size and colour
of the points indicates the stellar mass of the galaxies (as labelled). The diagonal dividing line for
LINERs/Seyferts is taken from Schawinski et al. (2007).
blue spirals, and that there are no significant trends with density in either population. We
have repeated this exercise using (projected) distance to the nearest neighbour, and find
similar results.
Red spirals in all environments have lower rates of recent and on-going star formation
than blue spirals. This suggests that despite the increased fractions of red spirals in high
density regions, environment is not the only factor in the shutting down of star formation
in red spirals - i.e., the main physical process cannot only happen in high density regions
(ruling out ram pressure stripping as the dominant process) and neither can it proceed
faster in higher densities.
Our data are consistent with the process that turns spirals red being more likely to
happen in high density regions as long as it is possible and proceeds in the same fashion
in all environments. Both gentle interactions, and/or strangulation mechanisms could
explain these observations.
5.5
The Impact of AGN
The most recent semi-analytic models for galaxy formation all invoke some form of AGN
feedback which inhibits star formation in the most massive, red (early-type) galaxies
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Figure 5.13 – Distribution on the BPT diagram of our sample of face-on disky blue spiral galaxies
with the same number of objects in each mass bin as the red spirals shown in Figure 5.12 (selected
randomly). The size and colour of the points indicates the stellar mass of the galaxies (as labelled).
(Granato et al. 2004, Silk 2005, Croton et al. 2006, Bower et al. 2006) in order to match
the number counts and properties of these objects in the local universe. Observational
evidence now exists to support this hypothesis, showing that the AGN fraction peaks in
the region between the blue cloud and the red sequence (Schawinski et al. 2007, 2009a).
Could AGN feedback be responsible for the shutdown of star formation in the red spirals?
We test this by using emission line diagnostic diagrams (Baldwin Phillips & Terlevich
1981, hereafter BPT; Veilleux & Osterbrock 1987, Kewley et al. 2001, 2006, Cid Fernandes et al. 2001) to probe the dominant source of ionisation in the red and blue spiral
galaxies. For this study, we restrict our analysis to galaxies with greater than 2σ emission
line detection for all four lines used in the BPT diagram (i.e. [OIII], Hα, [NII] and Hβ).
Likewise, in order to reduce the effect of aperture bias of the SDSS 300 fibre on the BPT
diagram, we shift the lower redshift range of our sample up from z > 0.03 to z > 0.05.
This reduces the sample size to 181 (60%) of the red spirals, and 3462 (66%) of the blue
spirals.
Standard emission line diagnostic diagrams (e.g. Kauffmann et al. 2003b, Schawinski
et al. 2007) are used to divide galaxies whose budget of ionising photons is dominated
by current star formation (i.e. ionisation from OB associations) and those whose interstellar medium is excited by other processes. These other processes include AGN, but
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5.5 The Impact of AGN
also shocks and evolved stellar populations such as post-asymptotic giant branch (pAGB)
stars, extreme horizontal branch stars, white dwarfs (Stasińska et al. 2008, Sarzi et al.
2009).
Observationally, the area between these two regions is populated by transition or composite objects where the total contribution to the ionising budget from star formation and
other processes is roughly comparable. Kewley et al. (2001) give a prescription based
on theoretical modelling of starburst galaxies which indicates the region of the diagram
which can be explained by starburst emission (to the lower left of the line), while Kauffmann et al. (2003b) made an empirical fit to the observed separation between the populations in SDSS galaxies, which is often used as a lower limit for the location of AGN. Here
as a short-hand, we will call objects to the upper right of the Kewley et al. (2001) line
“AGN" (even if other processes may be more important in some objects), or sometimes
"Seyfert+LINER" (as explained below), objects below the Kauffmann et al. (2003b) line
“star-forming" and objects falling between the two lines “composite" objects.
The region dominated by ionization from processes other than star formation is furthermore divided into Seyferts and LINERs (low-ionisation nuclear emission-line regions;
Heckman 1980). To split this region into Seyfert and LINER types we use the diagonal dividing line suggested by Schawinski et al. (2007). Objects in the Seyfert region are clearly
identified as classical obscured (Type 2) Seyferts (i.e., AGNs), while the LINER region is
more controversial and possibly represents a heterogeneous population (see Section 5.6 of
Ho 2008 for a recent review of possible sources of ionisation for LINERs). Recent results
from the SAURON survey by Sarzi et al. (2009) show that the extended LINER emission
seen in most SDSS fibre spectra (whose physical footprint corresponds to 2-3 kpc in the
sample studied here) is inconsistent with a central point source for the ionisation, ruling
out nuclear activity as the dominant source for the emission. Intriguingly, this is even the
case when the presence of nuclear activity (e.g. from radio data) is detected.
The position of red spirals on a BPT diagram is illustrated in Figure 5.12 where points
are coded (both in size and colour) by the stellar mass of the galaxy. Many more of the red
spirals than the blue are placed above the Kewley et al. (2001) dividing line, indicating
that they are not dominated by emission from star forming regions, but their gas must be
ionised by other mechanisms (30 ± 4%2 of all face-on disky red spirals in redshift interval
of 0.05-0.085, compared to 4 ± 1% of blue spirals). As the plot indicates, a significant
fraction of these galaxies are LINER-type (82 ± 12%). The remaining red spirals have
many more composite objects than are found in the normal spiral population (49 ± 5%
compared to 15 ± 1% of blue spirals) with only a relatively small fraction being classed as
starforming by the Kauffmann et al. (2003b) criterion (21 ± 3% of red spirals compared
to 81 ± 2% of blue spirals).
Part of these trends can be explained by the larger stellar masses of the red spirals,
since it is well known that Seyferts and LINERs are more common in higher mass galaxies
(e.g. Kauffmann et al. 2003b). Therefore for a fair comparison we construct a sample of
blue spirals selected from the full blue spiral population in such a way that they have the
2
√
Errors on the fractions given in this Section and elsewhere are N counting errors. This obviously breaks
down when fractions approach zero or one, however for the purposes of this work the approximation of the
errors is adequate.
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Chapter 5 – Galaxy Zoo: Passive Red Spirals
same mass distribution as the red spirals (our “mass matched" blue spiral sample). We
show 181 of these galaxies (i.e., the same number as in the red spiral sample for ease of
comparison) on the BPT diagram in Figure 5.13. Compared to this mass matched sample
of blue spirals, red spirals are still significantly more likely to host optically identified
Seyfert+LINER emission lines. Recall, 30 ± 4% of red spirals are above the Kewley
et al. (2001) division and 48 ± 5% are in the composite region. In comparison we find
only 7 ± 1% mass matched blue spirals in the Seyfert+LINER region and 23 ± 1% in the
composite region. Red spirals are therefore ∼4 times as likely to have Seyfert+LINER
emission lines, and twice as likely to be composite objects when compared to similar blue
spirals.
We plot in Figure 5.14 the observed fractions of Seyfert+LINER and starforming
galaxies as a function of mass for both the red and blue spirals. For both sub-populations
the Seyfert+LINER fraction increases with stellar mass, while the starforming fraction decreases, however as previously commented, at a given stellar mass red spirals are roughly
twice as likely to be classifed as Seyfert/LINER, and less likely (roughly half as likely) to
be classified as a starforming. There is a suggestion that the increase of Seyfert+LINER
fraction with mass is also faster in the red spirals than it is in the blue spirals (at the
expense of “composite" objects, since the starforming fractions are seen to decrease at
approximately the same rate).
AGN fractions in all galaxies have generally been shown to be independent of environment (Miller et al. 2003, Sorrentino, Radovich & Rifatto 2006). However, recent
work on X-ray selected AGNs does suggest an environmental dependence such that X-ray
selected AGN are more common in groups than clusters (Arnold et al. 2009, this work
also comments on the complete disjoint of X-ray selected and BPT selected AGN samples making such studies hard to compare) and Lee et al. (2009) also suggest AGN are
less common in higher densities. Here, we see no signature of a density dependence of
the Seyfert+LINER fraction of red spirals, although we note that the red spiral sample is
quite small to divide in this way and covers only a limited range of densities.
Red spirals with emission lines which are not classified as coming from star formation are more likely to be classified as LINERS than similar objects in the blue spirals
population, with 82 ± 12% of those in red spirals being LINERS versus 57 ± 7% in the
mass matched blue spirals. This means the Seyfert fractions of red and blue spirals of the
same mass are actually quite similar (6 ± 2% of red spirals versus 3 ± 1% of blue spirals)
- the main difference in the two populations appears to be in the LINER fraction which
suggests a link between LINER emission and the shutting down of star formation in spiral
galaxies. Overall 25 ± 4% of the red spirals are classified as having LINERs, while only
4 ± 1% of the (mass matched) blue spirals meet the LINER criteria. Interestingly in visually classified early type galaxies, Schawinski et al. (2007) also found that an increase in
LINER fraction was associated with “stellar quiescence", while Smolčić (2009) studying
radio loud AGN also found that the radio AGN in the red sequence were dominated by
low ionization AGN which were classified as LINERs in the BPT diagram.
The Balmer line emission from even a small amount of star formation is expected
to dominate any AGN emission. Schawinski et al. (2010) study the masking of AGN
(Seyfert) emission in star forming galaxies and show that for AGN [OIII] luminosities
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5.5 The Impact of AGN
Figure 5.14 – Fraction of galaxies in a given stellar mass range which are classifed as "AGN"
(Seyfert+LINER) or starforming from the BPT diagram (expressed as a percentage; note that the
fraction classified as composites are not shown). The trends for√blue spirals are shown with the blue
lines, red spirals by the red lines. Shaded regions show the N counting errors on the fractions.
Obviously these errors break down where the fractions approach zero or one, but give a reasonable
estimate elsewhere.
Figure 5.15 – Histogram of [OIII] luminosities of optically identified Seyferts and LINERS in the
red spirals (red dotted line) and blue spirals from the mass matched sample (black solid line). The
typical error on the red spiral histogram is indicated, offset for illustration purposes. Note that the
y-axes are scaled such that the total area under each histogram is equal.
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Chapter 5 – Galaxy Zoo: Passive Red Spirals
below 1039 erg s−1 most galaxies with star formation present will not be classified as AGN,
and that only above 1040 erg s−1 will the sample of AGN identified by optical emission
lines be reasonably complete in the blue cloud. We show in Figure 5.15 histograms of the
[OIII] luminosities (extinction corrected using the method described in Lee et al. 2009) of
both red and blue spirals (from the sample matched in mass with the red spirals) classified
as having either Seyfert or LINER emission. This diagram suggests that there may be a
difference in the luminosities of the emission lines identified in the two populations, such
that fainter lines (below about 1039.3 erg s−1 ) are found in the red spiral population which
are not found in the blue spiral population. However, since the actual number of red
spirals are small, the histograms do agree within the error.
If true, the above observation suggests that at least some LINERs are being revealed
in the red spiral population, either because the emission lines are no longer dominated
by star formation, or perhaps because the smaller amount of recent star formation means
there is less dust shrouding the AGN. However the difference cannot account for all of the
extra LINERs in the red spirals - i.e., even at the luminous end of the distribution where
we would not expect LINERs to be hidden in the blue spirals, we find more LINERs in
red spirals (considering only emission with L[OIII]> 1039 erg s−1 we find 24 ± 4% of the
red spirals have emission not consistent with star formation compared to 7 ± 1% of the
mass matched blue spirals), so we are able to say that at least high luminosity LINER
emission is correlated with the shutting down of star formation in spiral galaxies.
Since we do not have either integral field observations or X-ray/radio data of red spirals, we present two alternative interpretations for the high LINER fraction in red spirals:
1. Photoionisation from evolved stellar populations.
If we assume that the LINER emission in red spirals is mostly due to photoionisation from evolved stellar populations (e.g. Stasińska et al. 2008), then we can naturally account for the relatively higher fraction of LINERs in red compared to blue
spirals in the following way: in massive galaxies, there is a substantial component
of hard ionising radiation coming from evolved stellar populations, that would, in
the absence of other factors, produce a weak LINER spectrum. In blue spiral galaxies, this signature is mostly overwhelmed by ongoing star formation, whereas in red
spirals, where star formation has been gently quenched, no such competing source
of photons is available.
2. Low-luminosity nuclear activity.
If we assume that the LINER emission in red spirals is due to photoionisation from
a low-luminosity, low-Eddington AGN (e.g. Kewley et al. 2006), we can ask about
the role of this AGN in the evolution of red spirals. As suggested earlier, red spirals
gently quenched their star formation in an extended process that began about 2
Gyr in the past. This in turn implies that the current LINER AGN can not be
responsible for the suppression of star formation as it is happening now - with a
substantial time delay after the quenching process. A similar, though shorter time
delay is seen between the suppression of star formation and the start of substantial
black hole growth (Schawinski et al. 2007). The LINER phase in red spirals, like in
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5.6 Bar Fractions in Red/Blue Spirals
early-types (Schawinski et al. 2007), seems to be a post-quenching phenomenon.
The interesting question then becomes why the particular internal environments of
red spiral galaxies that have already quenched their star formation is so conducive
to low-level black hole growth.
Further observations of red spirals are required to fully distinguish between these
two interpretations. Spatially resolved spectroscopic observations (long-slit or IFU) are
needed to test whether the LINER emission in red spirals is spatially extended as it is
in early-types. Deep X-ray or radio observations could yield evidence for ongoing black
hole accretion.
5.6
Bar Fractions in Red/Blue Spirals
Even a cursory inspection of a small sample of images suggests that red spirals may have
a significantly higher bar fraction than blue spirals (e.g. Figure 5.3). Two of us (BC
and KLM) visually inspected the entire face-on disky red spiral sample, along with a
similar number of the random mass matched blue spirals. We find that red spirals have
an optical bar fraction of at least 67 ± 5% (raw fractions were 72% for BC and 67% for
KLM) and up to 100% including more uncertain identifications, while the blue spirals
have a bar fraction of only 27 ± 5% (28% from BC and 26% from KLM). These bar
identifications used the SDSS gri images typically used by Galaxy Zoo, and were based
on classic visual bar identification methods such as those used by de Vaucouleurs et al.
(1991) to find a bar fraction of 25-30% in the RC3. More recent work on bar fractions in
the literature (e.g. Jogee et al. 2004, Sheth et al. 2008, Barazza et al. 2008, Aguerri et
al. 2009) use automated techniques for finding bars using elliptical isophote fitting. The
two studies using SDSS data on ∼2000 “disk" galaxies (Barazza et al. 2008, Aguerri
et al. 2009) are most directly comparable to this study. Both however use automated
techniques to identify disk/spiral samples based largely on concentration (Aguerri et al.
2009) and colour (Barazza et al. 2008, this study does also consider Sersic fits, but the
final results are from colour selected “spirals" only), so we expect systematic differences
with our visually identified face-on spiral sample and inparticular point out that red spirals
by our definition will be completely absent from the Barazza et al. (2008) study, and
extremely rare in Aguerri et al. (2009). The overall bar fractions found by Barazza et al.
(2008), Aguerri et al. (2009) are comparable to our total bar fraction of ∼50% (they find
50% and 45% of their disk samples hosting bars), but intriguingly both studies suggest
a trend for bluer disk galaxies to be more likely to host bars, in direct contrast to the
clear signal we find for red spirals to have more obvious bars in the gri images. It is
not clear at this point if the difference in these trends is due to the sample selection or
the bar identification method (although Aguerri et al. (2009) claim only a 7% difference
between their automated bar finder and a visual check of their sample). A more detailed
study of bar fractions in Galaxy Zoo galaxies as a function of various galaxy properties
and considering possible biases on the visual bar identification method with gri images is
being prepared using bar identifications for almost 30,000 spiral galaxies collected during
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Chapter 5 – Galaxy Zoo: Passive Red Spirals
the second phase of Galaxy Zoo (GZ2; Masters et al. in prep.). For the purposes of this
work, the huge increase in bar fraction between the blue and red spiral samples gives such
a strong hint of a trend of bar fraction with colour (in the sense that red spirals are much
more likely to host bars), that it suggests bars may be providing an important clue to the
formation of the red spirals and therefore the impact of bars should be considered in a
discussion of their possible origin.
In simulations of spiral galaxy formation, bars form quickly once a stable disk is
formed, and are difficult to destroy (e.g. Debattista et al. 2006). However, the impact
of higher density environments on bars is unclear. Tidal interactions might induce bar
formation (eg. Hernquist & Mihos 1995), but they also act to heat the disks of spirals,
and bars form most quickly in cold disks (eg. Toomre 1964). If external triggers such as
tidal interactions are the most important source of bar instabilities, then the higher density
environments of the red spirals may naturally lead to high bar fractions.
A possible explanation for the high bar fraction in red spirals could be that the bars
themselves are at least partly responsible for the process which turned off star formation
in these objects. Bars are known to be the most efficient way to redistribute material in
the disks of galaxies (eg. Combes & Sanders 1981), by channelling gas into the central
regions of the galaxy. Bars have been invoked (eg. Shlosman et al. 2000) as a way to
feed gas to the central black hole - the increase in LINER fraction we observe in the
red spirals could be a remnant of this process (if they are LINERs associated with AGN).
Perhaps the bars in the red spirals have removed the cold gas from the disk and channelled
it inwards where it has either been used as fuel for the AGN, or created a starburst. Of
course, this starburst must have happened more than ∼ 1 Gyr ago, to be consistent with
our observation that red spirals are not post starburst objects, but if bars are as robust as
simulations suggest then they would still persist for a long time after evidence of any bar
triggered central starburst was removed.
5.7
Discussion
Since red spirals are observed at all density levels, the process which creates red spirals
cannot be confined only to regions of high galaxy density; environment alone is not sufficient to determine whether a galaxy will become a red spiral or not. The lack of any clear
correlation of the star formation rates of red spirals with environment, also indicates that
red spirals in low density regions are similar to those in clusters making it more difficult
to invoke only environmental processes in their formation. The process which turns spirals red may be more likely to occur in higher density regions, but must be possible, and
proceed in a similar way in all environments, unless completely different mechanisms are
responsible for red spirals in high and low density regions. That the red spiral population
has a significantly higher mean mass than the population of blue spirals, also indicates
that they are not uniformly sourced from the field population. However, perhaps the mass
transition between red and blue spirals represents the lowest mass spiral which can retain
its spiral structure under the influence of environmental effects which shut off its star formation (i.e.,. low mass blue spirals might pass through the red spiral phase very quickly,
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5.7 Discussion
or experience both morphological and colour transformation at the same time).
We suggest that rather than representing an intermediate stage of environmental transformation, red spirals could be “old spirals" who through normal internal evolution have
already used up their reservoirs of gas - perhaps aided by the redistribution of gas due
to a bar instability. We suggest that part of the reason they are found to be more common in higher density regions is because the initial density fluctuations decoupled from
the Hubble flow earlier there (see Bromm et al. 2009, for a review) and galaxies started
assembling at much earlier times (Cooper et al. 2009) in dense environments so have had
longer to use up their gas. Such objects would naturally be found at the high mass end of
the galaxy distribution as they have been assembling for a long time. Red spirals presumably become less common in the highest densities where strong environmental processes
are more important and may have already changed all spirals into early type galaxies.
It has been shown that for a typical spiral (i.e., with typical star formation rates) to use
up all its gas within a Hubble time requires that there is no infall of additional gas from its
halo (Larson et al. 1980). Therefore strangulation (or removal of gas from the outer halo
- a process which would be more common in satellite galaxies in higher density regions,
but can happen even in low mass groups Kawata & Mulchaey 2008) is probably required
and could by itself create a population of red spirals preferentially found in intermediate
density regions (if those in the highest densities were further disrupted). It was observed
by Skibba et al. (2009) that the Galaxy Zoo red spirals are preferentially satellite galaxies
in massive halos (while blue spirals are preferentially the central galaxy in a low mass
halo). This observation supports the idea of strangulation as an important part of the
mechanism which creates red spirals. In this scenario they are accreted onto the massive
halo as a blue spiral, after which their outer halo gas reservoirs are gently stripped by
the main galaxy, and no further accretion of cold gas can take place. (Bekki et al. 2002)
showed that in such a scenario spiral arms would persist for a few Gyrs after the gas was
removed. Lower mass spirals presumably are disrupted by gravitational effects in the
massive halo and cease to display spiral features, so this model can explain both the mass
and environmental distribution of the red spirals.
If other environmental processes are responsible for turning spirals red, they must be
very gentle and happen over long timescales. Continued tidal interactions and/or minor
mergers (i.e., galaxy harrassment, Moore et al. 1999) could be responsible - these would
heat the disk gas above the density required for star formation, but not remove it. If tidal
interactions are also responsible for creating bars (e.g. Hernquist & Mihos 1995) the high
bar fraction we observe could be a remnant of this (although the bars may still help to
shut down star formation by re-distributing and heating the gas themselves).
Several authors (e.g. Goto et al. 2003, Wolf et al. 2009) have suggested that red (or
passive) spirals are the progenitors of S0 galaxies. The origin of the S0 galaxies has been
an ongoing debate for more than three decades (Dressler 1980, Moran et al. 2007). S0s are
often argued to be too bright and massive and have too large bulge-disk ratios to simply
be faded spirals (e.g. Burstein et al. 2005), but Moran et al. (2007) argue that they have
linked passive spirals with young S0s in two z ∼ 0.5 clusters and that a combination of gas
stripping and gentle galaxy-galaxy interactions could be responsible for the change, and
Driver et al. (2007) show that bulge light is severely attenuated by dust in spiral galaxies
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Chapter 5 – Galaxy Zoo: Passive Red Spirals
which may help to resolve the bulge-disk ratio issue.
There is only one observation in this paper which is immediately in conflict with
the idea of the Galaxy Zoo red spirals being the progenitors of S0s. We observe a high
optical bar fraction in the face-on disky red spirals, while S0s have a significantly lower
bar fraction (Aguerri et al. 2009). Our disky red spirals cannot simply turn into S0s as
their spiral arms fade, as the bar instability would remain much longer than the arms.
However in this work we have purposely selected red spirals with small bulges. Perhaps
S0s form from red spirals with large bulges. Further study of the red Galaxy Zoo spirals
with large bulges may clear up this issue.
5.7.1
Future Directions
This work has used optical data from SDSS to reveal the star formation history, dust content, AGN properties, environments and morphologies of a unique sample of intrinsically
red disk dominated spiral galaxies. It is clear that significantly more information can be
obtained from other surveys, wavelengths, and from future theoretical modelling, which
will help to shed light on the dominant physical process which formed these objects.
If strangulation is the dominant process forming red spirals they should have almost
no residual neutral hydrogen (alternatively, if tidal interactions are responsible by gently
heating the disk gas, and thus lowering its density below the threshold for star formation,
they should still contain significant quantities of HI). This will be tested using data from
the ALFALFA blind HI survey (Giovanelli et al. 2005) which covers much of the SDSS
footprint.
The debate over the nature of the LINER emission could be solved by moving to
other wavelengths to reveal the AGN or by obtaining spatially resolved optical spectra
to look at the extent of the emission. Deep targeted X-ray observations would reveal
objects currently growing their black holes. Unfortunately, currently available public Xray surveys are too small an area or at too low luminosity levels to be of use. (For example
the XMM Cluster Survey, XCS (Romer et al. 2001) has only 220 of the blue spirals and 6
of the red spirals studied here in its footprint (1 blue spiral is detected), while the ROSAT
All-Sky Survey, RASS (Voges et al. 1999) has a high flux limit). Current radio continuum
surveys (for example the NRAO-VLA Sky Survey, NVSS; Condon et al. 1998) could also
reveal ongoing black hole accretion, or radio-loud AGN.
More sophisticated modelling of the spectral information (for example from VESPA,
Tojeiro et al. 2009) would provide time resolved star formation histories and more reliable
stellar masses. Spatially resolved spectra would additionally allow separate study of the
star formation histories of the different regions of these galaxies, and provide dynamical
information possibly helpful in determining the role of the bars.
The interpretation of the increased bar fraction in the red spirals is made difficult by
the wide range of suggestions of the impact of bars on spiral galaxies. More detailed
modelling of spiral galaxies with bars would be extremely helpful in interpreting those
observations. We can also use Galaxy Zoo 2 data (which asks for a more detailed classification of among other things barred galaxies) to study the more general properties of a
large sample of galaxies with bars. For example studying the environmental dependence
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5.8 Summary and Conclusions
of barred galaxies compared to non-barred galaxies would shed light on the role tidal
interactions play in bar formation.
5.8
Summary and Conclusions
We study the interesting population of red, or passive, spiral galaxies found by the Galaxy
Zoo project. We identify from these red spirals a population of intrinsically red true
disk dominated spirals by limiting the sample in inclination (to reduce the impact of dust
reddening), requiring that spiral arms be visible, and removing bulge dominated systems
using the SDSS parameter fracdeV. We compare this sample to blue spirals selected in
the same way and find that:
• Red spirals are more likely to be more massive, luminous galaxies than blue spirals.
They represent an insignificant fraction of the spiral population at masses below
1010 M but are significant at the highest masses, showing that massive galaxies are
red regardless of morphology.
• At the same mass as blue spirals, face-on red spirals do not have larger amounts of
dust reddening (as measured by the Balmer decrement), therefore their red colours
indicate an ageing stellar population not an increased dust content.
• Red spirals have lower (but not zero) rates of ongoing and recent star formation
when compared to blue spirals. This is partly related to their higher average mass,
however at a fixed mass, red spirals still have less recent star formation than blue
spirals.
• As previously observed, red spirals are more common at intermediate local densities (around, or just inside the infall regions of clusters). They are also observed to
be more likely than blue spirals to have close neighbours.
• Red spirals in all environments have lower rates of recent and on-going star formation than blue spirals, and there are no significant trends of the star formation rates
with environment when spirals are split into red/blue. Clearly the process which
creates red spirals is not confined to regions of high galaxy density. So environment
alone is not sufficient to determine whether a galaxy will become a red spiral or
not.
• Red spirals are more than four times more likely to be classified as Seyfert+LINER/composite
objects from their optical spectra than blue spirals. This is partly due to the higher
masses of red spirals but is still observed when they are compared to a blue spiral
sample selected to have the same mass distribution. We find that a small fraction
of low luminosity AGN are being revealed as the star formation is turned off in
the red spirals, but this is not enough to account for all the difference. Most of the
difference comes from an increased fraction of LINER-like emission (82 ± 12%
of Seyfert/LINERs found in red spirals are LINERs compared to 57 ± 7% in blue
spirals).
117
Chapter 5 – Galaxy Zoo: Passive Red Spirals
• Red spirals have significantly higher bar fractions than blue spirals (70% versus
27%), suggesting that bar instabilities and the shutting down of star formation in
spirals are correlated.
We propose three possible origins for the red spiral population studied in this work
and suggest the most likely explanation is that a combination of the three accounts for the
shutting down of their star formation while they retain their spiral structure:
1. Perhaps red spirals are just old spirals which have used up all of their gas. They are
found preferentially in intermediate density regions because structures first starts to
form at the peaks of the dark matter distribution, but in the centres of clusters spiral
morphologies cannot stand up to the environmental disturbances. Red spirals then
represent the end stages of spiral evolution irrespective of environment (and in the
absence of major mergers) - the spiral version of “downsizing".
2. Perhaps red spirals are satellite galaxies in massive dark matter halos. In this scenario, they are accreted onto the halo as a normal blue spiral and have experienced
either strangulation (where the gas in their outer halos has been gently stripped off,
and no further cold gas has been allowed to accrete) or harassment (heating their
disk gas and preventing further star formation). Low mass spirals would probably
be disrupted in this process and so are not observed as red spirals.
3. Perhaps red spirals evolved from normal blue spirals which had bars that were
particularly efficient at driving gas inwards. This removed gas from the outer disk
and turned the spiral red. If it triggered star formation in the central regions it must
have occured more than ∼ 1 Gyr ago since red spirals are not post starburst galaxies.
The red spirals in this work probably cannot be the progenitors of S0s as they have a
significantly higher bar fraction than in observed in the S0 population. S0s may however
be the end product of red spirals with larger bulges than we have studied here.
ACKNOWLEDGEMENTS This publication has been made possible by the participation of more than 160,000 volunteers in the Galaxy Zoo project. Their contributions are
individually acknowledged at http://www.galaxyzoo.org/Volunteers.aspx. KLM
acknowledges funding from the Peter and Patricia Gruber Foundation as the 2008 Peter
and Patricia Gruber Foundation International Astronomical Union Fellow, and from the
University of Portsmouth and SEPnet (www.sepnet.ac.uk). Support for the work of MM
in Leiden was provided by an Initial Training Network ELIXIR (EarLy unIverse eXploration with nIRspec), grant agreement PITN-GA-2008-214227 (from the European Commission). AKR, MM, HCC, RCN acknowledge financial support from STFC. Support for
the work of KS was provided by NASA through Einstein Postdoctoral Fellowship grant
number PF9-00069 issued by the Chandra X-ray Observatory Center, which is operated
by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract
NAS8-03060. CJL acknowledges support from The Leverhulme Trust and the STFC Science In Society Programme. Funding for the SDSS and SDSS-II has been provided by the
118
5.9 Appendix A: Sample of Data Tables
Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the U.S. Department of Energy, the National Aeronautics and Space Administration,
the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS Web Site is http://www.sdss.org/.
5.9
Appendix A: Sample of Data Tables
We provide in this Appendix samples of the data tables we make available electronically
listing important information (all based on SDSS data) for both our red (Table 5.1) and
blue (Table 5.2) face-on disky spiral samples. In both tables columns are (1) SDSS objid;
(2 and 3) RA and Dec in J2000 decimal degrees; (4) Redshift; (5) Absolute r-band (Petrosian) magnitude, Mr ; (6) (g − r) colour (from model magnitues); (7) “redness", defined
as the distance in magnitudes from the blue limit of the (g − r) verses Mr red sequence
(see Equation 5.1 in Section 5.2.1); (8) axial ratio, log(a/b) from the r-band isophotal
measurement; and (9) fracdeV; the fraction of the best fit light profile made up by a de
Vaucouleur profile (as opposed to an exponential disk).
119
120
SDSS objid
587731186741346415
588015509270364319
587731187279265981
587731187279331410
588015508734148754
...
RA (J2000 deg)
1.218164
2.277073
3.718539
3.771462
3.789492
...
Dec (J2000 deg)
0.351724
0.042422
0.634254
0.642945
-0.366536
...
Redshift
0.0833
0.0735
0.0642
0.0621
0.0661
...
Mr
-21.26±0.01
-21.75±0.01
-21.15±0.01
-21.50±0.01
-22.18±0.01
..
(g − r)
0.695±0.020
0.701±0.021
0.756±0.039
0.662±0.017
0.687±0.018
...
“Redness"
0.040
0.036
0.103
0.002
0.013
...
Table 5.1 – A Sample of Face-On, “Disky" Red Spirals. (The full table is available in the online version of the paper.)
log(a/b)
0.144
0.143
0.042
0.179
0.070
...
fracdeV
0.42
0.46
0.00
0.32
0.40
...
Chapter 5 – Galaxy Zoo: Passive Red Spirals
SDSS objid
587727225690259639
587727225690259660
587730773888991473
588015510343385206
588015510343516321
...
RA (J2000 deg)
0.276560
0.325174
0.566363
0.665200
0.941711
...
Dec (J2000 deg)
-10.400263
-10.426144
14.671807
0.942673
0.854914
...
Redshift
0.0754
0.0767
0.0834
0.0807
0.0611
...
Mr
-21.41±0.01
-21.03±0.02
-20.91±0.02
-22.38±0.01
-20.69±0.01
..
(g − r)
0.434±0.020
0.561±0.028
0.503±0.035
0.632±0.018
0.378±0.023
...
“Redness"
-0.225
-0.090
-0.145
-0.046
-0.266
...
Table 5.2 – A Sample of Face-On, “Disky" Blue Spirals. (The full table is available in the online version of the paper.)
log(a/b)
0.084
0.078
0.106
0.079
0.185
...
fracdeV
0.12
0.07
0.06
0.22
0.00
...
5.9 Appendix A: Sample of Data Tables
121
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125
Nederlandse samenvatting
Geschiedenis
Aan het begin van de twintigste eeuw was het algemeen aanvaard dat onze Melkweg bijna
het hele Universum vulde. Pas in de jaren ’20 van de vorige eeuw werden er aanwijzingen gevonden voor sterrenstelsels buiten onze Melkweg. Pioniers zoals Edwin Hubble
vonden bewijs dat veel van de waargenomen "planetaire nevels” eigenlijk sterrenstelsels
buiten onze Melkweg zijn. Grote aantallen sterrenstelsels zijn sindsdien gevonden en
waargenomen. Om op een effectieve manier over deze objecten te kunnen praten werd
door astronomen besloten om sterrenstelsels te classificeren aan de hand van hun structuur
en vorm, of kortweg morfologie. Eén van de eerste classificatieschema’s werd geïntroduceerd door Edwin Hubble (1926), en is bekend geworden als Hubble’s Stemvork. Dit
schema, dat vandaag de dag nog steeds gebruikt wordt, onderscheidt sterrenstelsels als
elliptisch, lenticulair, spiraalvormig, of onregelmatig. Elke klasse kan op zijn beurt weer
opgesplitst worden in subklassen aan de hand van extra kenmerken, zoals bijvoorbeeld
de aanwezigheid van een balk. De verschillen tussen deze type sterrenstelsels reflecteren
de verschillen in hun fysieke eigenschappen. Sinds de eerste classificaties is het doel van
astronomen geweest om deze sterrenstelsels en hun fysieke eigenschappen in meer detail
te bestuderen.
Men ontdekte dat spiraalvormige sterrenstelsels andere sterpopulaties hadden dan elliptische. De hoeveelheid gas en recente gevormde nieuwe sterren in spiraalstelsels zijn
verschillend ten opzichte van elliptische sterrenstelsels, en verder hebben ze blauwere
kleuren. De sterpopulaties van elliptische sterrenstelsels zijn oud, met rodere kleuren, en
elliptische stelsels zijn gemiddeld zwaarder dan spiraalstelsels (Kauffmann et al. 2003,
Blanton et al. 2005). Over het algemeen vormen observationele eigenschappen zoals
kleur, vorm, helderheid, huidige sterformatie, stellaire en dynamische massa, circulaire
snelheid, en snelheidsdispersie de empirische grondslag voor het onderscheiden en het
bestuderen van de onderliggende fysica in sterrenstelsels (zie bijvoorbeeld Blanton &
Moustakas 2009).
De diversiteit aan verschillende soorten sterrenstelsels in het nabije Universum leidde
tot de vraag waar deze verschillende types vandaag komen. Astronomen proberen daarom
het onderliggende verhaal te ontdekken over de vorming en evolutie van sterrenstelsels,
vanuit zowel theoretisch als observationeel oogpunt. Het theoretische raamwerk afkomstig uit de jaren 1960-70 (bijv., Eggen et al. 1962, Sandage et al. 1970, Press & Schechter
1974), beschrijft de vorming van sterrenstelsels vanuit gravitationele instabiliteiten, ontstaan uit perturbaties in de verdeling van donkere materie en condensatie van gas.
Volgens de huidige theorie voor de vorming van sterrenstelsels geldt dat, zodra een
127
Nederlandse samenvatting
halo van donkere materie ineenstort, het gas binnenin deze halo zeer snel afkoelt. Deze
afkoeling vermindert de druk van het gas; om te voorkomen dat al het gas naar het centrum valt is een hoeveelheid impulsmoment nodig (ontstaan uit getijdenkrachten in het
jonge Universum). Dit zorgt ervoor dat het gas samenkomt in een roterende schijf (zie
bijvoorbeeld, Mo et al. 1998). Echter, verschillende theoretische modellen gebruiken verschillende aannames voor de dichtheidsprofielen van de halo van donkere materie, evenals
voor de initiële afhankelijkheid van het gas-impulsmoment op de halo van donkere materie. Het is onduidelijk of het gas-impulsmoment kan veranderen met de tijd, of hoe
sterformatie en feedback processen een effect hebben op de structuur van sterrenstelsels,
zoals bijvoorbeeld hun afmeting.
Er zijn kortweg twee verschillende scenario’s voor de formatie van de bulge (centrale
verdikking) van spiraalsterrenstelsels. Men gaat ervan uit dat ze gevormd worden door
een botsing van twee sterrenstelsels, of door de instabiliteit van de schijf. De formatie
van de bulge door middel van een botsing van twee sterrenstelsels, vereist de aangroei
van gas op een later moment om een schijf te vormen rond de bulge. Daarom is het goed
mogelijk dat in dit scenario de kern en de schijf verschillende sterpopulaties hebben. Bij
een scenario met een instabiele schijf zal materiaal dat al aanwezig is de bulge vormen.
Toch zijn er nog veel extra aannames nodig (bijvoorbeeld feedback processen) om een
compleet beeld te krijgen over de vorming en evolutie van typische spiraalsterrenstelsels.
De vorming van elliptische sterrenstelsels wordt ook niet goed begrepen. Een van de
mogelijke mechanismen voor de formatie van deze elliptische sterrenstelsels is door middel van een botsing van twee sterrenstelsels. Uit simulaties van botsende schijfsterrenstelsels is gebleken dat globale eigenschappen van elliptische sterrenstelsels gereproduceerd
kunnen worden (bijv., Hernquist 1992). Ondanks het feit dat dit algemene model veel
simpele karakteristieken voor deze sterrenstelsels goed kan voorspellen blijven er veel
aspecten die niet overeen komen met waarnemingen.
Om die reden blijven directe waarnemingen essentieel om de formatiemodellen voor
sterrenstelsels te testen. Het is van groot belang dat er niet alleen wordt gekeken naar
complete verzamelingen van nabije sterrenstelsels, maar ook naar grote verzamelingen
van sterrenstelsels op het moment dat ons Heelal jonger was. Om deze reden is het
identificeren van de eerste en verste sterrenstelsels steeds belangrijker geworden sinds
de midden-jaren ’70. In de jaren ’90 verschoof de waarneembare grens van verre sterrenstelsels naar roodverschuiving z ∼ 1 − 4, wat overeenkomt met een terugkijktijd van
∼ 7 − 12 miljard jaar. Dankzij zeer diepe waarnemingen zijn in de laatste tien jaar de
verzamelingen hoge-roodverschuiving sterrenstelsels enorm gegroeid en is de observationele limiet verder vooruitgeschoven naar z ∼ 10 (Bouwens et al. 2012).
Schalingrelaties
Een van de belangrijkste onopgeloste problemen in de astrofysica is het begrijpen van
de formatie en evolutie van sterrenstelsels. Er zijn veel complementaire manieren om
de evolutie van sterrenstelsels te bestuderen en om de connectie te vinden tussen verre
128
Schalingrelaties
sterrenstelsels en sterrenstelsels in het huidige Heelal. De meeste geaccepteerde methodes zijn of gericht op de evolutie in de helderheids- of massafuncties van sterrenstelsels,
of op de evolutie in de hoeveelheid sterformatie of stellaire massa dichtheid, of op de
evolutie van de waargenomen schalingrelaties van sterrenstelsels. Neem bijvoorbeeld de
helderheidsfunctie; deze beschrijft het aantal sterrenstelsels met een bepaalde helderheid.
Dit kan op zijn beurt gebruikt worden om het totale aantal sterrenstelsels te bepalen op
verschillende tijdstippen. Op deze manier geeft de evolutie van de helderheidsfunctie met
roodverschuiving ons essentiële informatie om de evolutie van sterrenstelsels te begrijpen.
Sterrenstelsel tonen een grote verscheidenheid aan fysieke eigenschappen zoals helderheid, stellaire massa, afmeting en rotationele snelheid. Sterrenstelsel vertonen goed
gedefinieerde schalingrelaties tussen deze eigenschappen. Voor spiraalstelsels, bijvoorbeeld, wordt het verband tussen de helderheid en de rotationele snelheid beschreven door
de ‘Tully-Fisher’ relatie (Tully & Fisher 1977). Dit is kortweg de correlatie tussen de
dynamische massa en de helderheid van sterrenstelsels. De relatie tussen de snelheidsdispersie en de helderheid van elliptische sterrenstelsel is bekend als de ‘Faber-Jackson’
relatie (Faber & Jackson 1976), waarbij elliptische sterrenstelsels met een hogere snelheidsdispersie helderder zijn.
Het is essentieel om deze schalingrelaties te bestuderen over een groot bereik in roodverschuiving. Dit kan ons helpen vast te stellen hoe sterrenstelsels zich bewegen binnen
deze relatie en maakt het dus mogelijk om verschillende evolutionaire modellen te testen. Over het algemeen geldt dat het bepalen van de helling, nulpunt en spreiding rond
deze relaties op verschillende tijdstippen van fundamenteel belang is om de verschillende
modellen voor de formatie voor sterrenstelsels te testen.
Echter, er zijn een aantal uitdagingen om de benodigde precisiewaarnemingen te verkrijgen. Om bijvoorbeeld de rotationele snelheid of snelheidsdispersie te meten voor
sterrenstelsels op hoge roodverschuiving zijn diepe spectroscopische observaties vereist.
Het verkrijgen van een groot aantal van deze metingen is een tijdsintensief proces. Daar
komt bij dat als sterrenstelsels minder helder worden de onzekerheid van deze metingen
toeneemt. Om deze reden is het bepalen van correlaties tussen sommige eigenschappen
van sterrenstelsels bijzonder moeilijk op hoge roodverschuiving.
Van deze schalingrelaties is degene tussen de stellaire massa en de afmeting van sterrenstelsels bijzonder belangrijk. De afmeting van een sterrenstelsel kan worden bepaald
door middel van waarnemingen in een enkele filter (fotometrie). De stellaire massa van
een sterrenstelsel kan ook robuust worden gemeten met behulp van fotometrie op vele
verschillende golflengtes en precieze modellen voor sterpopulaties. Het is daarom minder
moeilijk om een goede schatting te maken voor de afmeting en massa als het gaat om
grote hoeveelheden sterrenstelsels op hoge roodverschuiving in vergelijking met de spectroscopische metingen zoals eerder beschreven. Daar komt bij dat de stellaire massa en
de afmeting van sterrenstelsels twee belangrijke ingrediënten zijn voor het karakteriseren
van sterrenstelsels en belangrijke fysische betekenis hebben. Het bestuderen van deze
eigenschappen op verschillende tijdstippen in het Heelal zal bijdragen in het onderzoek
naar hoe de structuur van nabije sterrenstelsels is ontstaan en wat de eigenschappen zijn
van hun voorgangers op hoge roodsverschuiving. In het kort, het kan ons helpen om de
verschillende evolutionaire scenario’s voor de formatie en evolutie van sterrenstelsels af
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Nederlandse samenvatting
Figuur 1 – De stellaire massa-grootte relatie voor spiraal- en elliptische sterrenstelsels in de SDSS
(bovenste paneel) en de dispersie in de afmetingen als een functie van stellaire massa (onderste
paneel) uit de studie door Shen et al. (2003).
te bakenen.
De relatie tussen de stellaire massa en de afmeting van sterrenstelsels in het huidige
Heelal is voor het eerst beschreven in Kauffmann et al. (2003), en goed gekarakteriseerd
door Shen et al. (2003), die gebruik maken van een verzameling sterrenstelsels in de Sloan
Digital Sky Survey (SDSS). Het bovenste paneel van Figuur 1 laat de massa-grootte relatie zien voor spiraal- en elliptische sterrenstelsels zoals bestudeerd door Shen et al. (2003).
De relatie is verschillend voor spiraal- en elliptische sterrenstelsels. Op hoge massa geldt
dat spiraalsterrenstelsels een steilere relatie hebben in vergelijking met elliptische. Dit reflecteert verschillen in de formatiemechanismen van elk type sterrenstelsel. De spreiding
in de afmetingen (onderste paneel van Figuur 1) laat ook een variatie zien als functie van
de stellaire massa: de spreiding neemt af voor massievere sterrenstelsels.
De eerste baanbrekende onderzoeken naar de afmetingen van sterrenstelsels op hoge
roodverschuiving werden gedaan in de jaren ’90 (bijv., LBGs op z ∼ 3 door Giavalisco
et al. (1996), of Lilly et al. (1998) sterrenstelsels tot z ∼ 1). Echter, de resultaten van
deze verschillende onderzoeken waren niet in overeenkomst, mede veroorzaakt door de
moeilijkheidsgraad om een groot aantal van deze sterrenstelsels te meten op hoge roodverschuiving, maar ook door selectie-effecten voortkomend uit de oppervlakte helderheid
limiet. Deze studies naar de helderheid-grootte relatie van sterrenstelsels verbeterden later door het gebruik van diepe waarnemingen vanaf de grond en vanuit de ruimte. Deze
onderzoeken lieten zien dat sterrenstelsels in het jonge Heelal kleiner waren in vergelijking met sterrenstelsels met een vergelijkbare massa/helderheid in het lokale Universum
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Schalingrelaties
Figuur 2 – De relatieve distributie van de stellaire massa en afmeting van dode sterrenstelsels op
z ∼ 2 en in het nabije Universum. De verschillende pijlen laten de voorspelling zien voor elk model
als functie van roodverschuiving. (Figuur afkomstig uit Bezanson et al. (2009)).
(bijv., Trujillo et al. 2006b, Zirm et al. 2007, van Dokkum et al. 2008). Dit betekent dat
de afmeting van sterrenstelsels, gegeven een stellaire massa, moeten groeien in tijd met
maximaal een factor ∼ 6.
Dit proces van groei in de afmeting van sterrenstelsels kan verschillend zijn voor elke
type en kan variëren op elk tijdstip. Stervormende sterrenstelsels op hoge roodverschuiving (bijv op z ∼ 2), hebben een grotere fractie gas per stellaire massa in vergelijking met
hun tegenhangers op lage roodverschuiving (e.g., Erb et al. 2006). Een mogelijke verklaring voor de groei in afmeting voor deze sterrenstelsels zou kunnen worden gegeven door
de aanwas van gas op de schijf wat weer omgezet wordt in nieuwe sterren (bijv., Law
et al. 2012).
Verschillende observaties hebben verder laten zien dat elliptische sterrenstelsels op
hoge roodverschuiving ook significant kleiner zijn dan stelsels op lage roodverschuiving.
Er zijn twee belangrijke vraagstukken voor deze sterrenstelsels. Allereerst: hoe zijn deze
sterrenstelsels gevormd op hoge roodverschuiving? En ten tweede: hoe verhouden deze
sterrenstelsels zich tot hun lokale analogen. De formatie van deze compacte dode sterrenstelsels wordt nog nauwelijks begrepen. Niettemin zijn verscheidene mechanismen
voorgesteld om de groei in afmeting van deze sterrenstelsels te verklaren. De vaakst
voorkomende voorbeelden zijn door middel van grote botsingen, kleine botsingen, of adiabatische expansie (bijv., Khochfar & Silk 2009, Naab et al. 2009, Bezanson et al. 2009,
Fan et al. 2008). Deze verschillende mechanismen kunnen de stellaire massa en massaprofielen op verschillende manier veranderen.
De waargenomen stellaire massa-grootte relatie voor deze massieve dode sterrenstel131
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sels zou kunnen helpen om te bepalen welke van de verschillende modellen de juiste is.
Botsingen van sterrenstelsels met weinig gas en met dezelfde massa (grote botsingen)
kunnen de afmeting en de stellaire massa van deze sterrenstelsels verdubbelen. Kleine
botsingen zorgen voor een grotere groei in afmeting ten opzichte van de groei in stellaire
massa, en dit proces conserveert de centrale dichtheid en snelheidsdispersies. Het adiabatische expansie scenario voorspelt dat een grote hoeveelheid materiaal efficiënt wordt
uitgestoten door middel van een vorm van feedback (bijv. Quasar feedback). Echter, in
dit proces wordt de centrale dichtheid en de snelheidsdispersie van een elliptisch sterrenstelsel veranderd (zie Figuur 2 voor meer details). Door de verschillende schalingrelaties
op verschillende roodverschuivingen (tijdstippen) te vergelijken met de resultaten van simulaties kunnen we de verschillende scenario’s toetsen voor de vorming en evolutie van
sterrenstelsels.
Dit Proefschrift
De onzekerheden geassocieërd met de waargenomen eigenschappen van sterrenstelsels
kunnen worden verminderd door extra observaties die gebruik maken van diepere data
met grotere gebieden aan de hemel en goed gedefinieerde selectiemethoden. Metingen op
meerdere golflengtes zijn krachtige instrumenten voor dit soort studies. Door gebruik te
maken van de snelle recente ontwikkeling op het gebied van infrarood metingen van sterrenstelsels, en met behulp van aanvullende optische en nabije-infrarood waarnemingen,
is het nu mogelijk geworden om de eigenschappen van verschillende typen sterrenstelsels
over een groot bereik in roodverschuiving te bestuderen en de observationele limieten
verder vooruit te schuiven tot het tijdstip van de formatie van de eerste sterrenstelsels
(z ∼ 10).
In dit proefschrift ligt de focus op het bestuderen van de structurele eigenschappen van
sterrenstelsels, zoals hun afmetingen en helderheidsprofielen, en te analyseren hoe deze
eigenschappen veranderen als functie van tijd. In het bijzonder bestuderen we de stellaire
massa-grootte relatie van sterrenstelsels tussen z = 7 en z = 0, door gebruik te maken van
recente diepe observaties in het nabije infrarood. De combinatie van diepe optische en
nabije-infrarood waarnemingen maakt het mogelijk om de spectra van sterrenstelsels te
karakteriseren over een groot bereik in roodverschuiving, in het bijzonder tijdens de piek
in de sterformatie activiteit (z ∼ 2). Het bestuderen van de eigenschappen van sterrenstelsels en het bepalen van de schalingrelaties op verschillende tijdstippen is van groot belang
om onderscheid te kunnen maken tussen de verschillende fysische processen die invloed
zouden kunnen hebben op de vorming van deze sterrenstelsels (bijv., aanwas van gas op
sterrenstelsels, of grote/kleine botsingen en feedback effecten).
Hoofdstuk 2: In dit hoofdstuk presenteren we de eerste studie naar de evolutie van
de afmetingen van sterrenstelsels die gebruik maakt van een verzameling van objecten
met een spectroscopische roodverschuiving tussen z ∼ 0.5 − 2.5 in het GOODS-Noord
veld. Over het algemeen maken studies slechts gebruik van fotometrische roodverschuivingen; door stelsels met spectroscopische roodverschuivingen te gebruiken kunnen we
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Dit Proefschrift
belangrijke selectie effecten verwijderen. Verder bestuderen we de afmeting van verschillende type UV-heldere stervormende sterrenstelsels op hoge roodsverschuiving. Dat wil
zeggen, we meten de afmetingen van verschillende soorten sterrenstelsels, zoals Lyman
Break Sterrenstelsels, BM/BX sterrenstelsels, en Lyman Break analogen, op een roodverschuiving van z ∼ 1. Bovendien vergelijken we de afmetingen van deze sterrenstelsels
met andere type stervormende sterrenstelsels, zoals BzKs en sub-millimeter sterrenstelsels (SMGs). De positie van deze sterrenstelsels ten opzichte van de massa-grootte relatie
kan aanwijzingen geven over hun connectie met andere soorten sterrenstelsels.
Hoofdstuk 3: Met de komst van de recent geïnstalleerde Wide Field Camera 3 (WFC3)
op de Hubble Space Telescope en de daarmee gemaakte ultradiepe nabije-infrarood observaties van de Hubble Ultra Deep Field (HUDF), is het mogelijk geworden om een groot
aantal nieuwe kandidaat-Lyman Break Sterrenstelsels (LBGs) te identificeren, reikend tot
de beginfase van de formatie van de eerste sterrenstelsels (bijv. tot z ∼ 8). De meeste onderzoeken zijn vooral gericht geweest op de evolutie van de helderheidsfunctie, stellaire
massa, en mate van sterformatie in LBGs op deze roodverschuiving (bijv., Bouwens et al.
2011, Gonzalez et al. 2011). Echter, de stellaire massa-grootte relatie van deze sterrenstelsels op z & 4 zijn nog niet in detail onderzocht. In dit Hoofdstuk maken we daarom
gebruik van de ultra diepe WFC3 nabije-infrarood en IRAC observaties in de HUDF en
het Early Release Science (ERS) veld, om de stellaire massa-grootte relatie van LBGs te
bestuderen tot een roodverschuiving van z ∼ 7.
Op z & 4 wordt optisch licht roodverschoven naar het mid-infrarood, wat een probleem is voor het bepalen van stellaire massa’s. Met de Spitzer Space Telescope is het
mogelijk om gevoelige fotometrische metingen uit te voeren op deze golflengtes; helaas
zorgt zijn grote PSF voor problemen, doordat sterrenstelsels optisch vermengen. Echter,
er bestaan robuuste technieken om voor deze versmeerde objecten individueel de fotometrie te bepalen, wat weer gebruikt kan worden om de stellaire massa van sterrenstelsels
op hoge roodverschuiving accuraat te bepalen (Labbé et al. 2006). Bovendien hebben
we de afmetingen van deze stelsels gemeten met een meettechniek (uitgaande van een
Sérsic model) die consistent is met de manier waarop dit veelal wordt gedaan op lagere
roodsverschuivingen. Met behulp van deze methoden zijn we in staat om de stellaire
massa-grootte relatie te bepalen voor sterrenstelsels tot z ∼ 7.
Hoodstuk 4: De stellaire massa-grootte relatie van sterrenstelsels in het huidige Heelal
kan gebruikt worden als een basislijn voor de evolutie van de afmetingen van sterrenstelsels als een functie van tijd. Om die reden bestuderen we in dit Hoofdstuk de massagrootte relatie voor een verzameling van sterrenstelsels op z = 0.01 − 0.02, waarbij de
verzameling is opgedeeld aan de hand van algemene classificatiemethoden. We bestuderen verschillende technieken om de afmetingen van sterrenstelsels te bepalen: een enkel
Sérsic profiel, een twee-componenten Sérsic profiel, en een non-parametrische methode,
met als doel om de systematische onzekerheid te kwantificeren die bij elke techniek hoort.
Tot slot testen de we de potentiële systematische fouten in de bepaling van afmetingen op
hoge roodverschuiving door onze sterrenstelsels op z = 0 artificieel te verschuiven naar
z = 1 en de metingen opnieuw uit te voeren, gebruik makend van een enkel Sérsic profiel.
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Nederlandse samenvatting
Hoofdstuk 5: Vele studies hebben aangetoond dat de meerderheid van sterrenstelsels
een kleur-morfologie relatie vertoont, zowel op lage als hoge roodverschuiving. In andere
woorden, morfologische transformatie en het einde van sterformatie zouden gecorreleerd
kunnen zijn. Echter, er is een populatie van rode, dode spiraal sterrenstelsels (zonder
enige vorm van sterformatie), als eerste opgemerkt door van den Bergh (1976) en Couch
et al. (1998) , die niet binnen deze relatie past.
In dit Hoofdstuk maken we gebruik van zorgvuldig geselecteerde schijfstelsels (op
z ∼ 0) uit de Galaxy Zoo morfologische catalogus (visueel geselecteerd), om een verzameling op te bouwen van echt passieve schijf sterrenstelsels. We proberen de verschillende fysische processen te onderzoeken die verantwoordelijk kunnen zijn voor stopzetten
van de sterformatie in deze rode passieve spiraalsterrenstelsels zonder de spiraal morfologie te verstoren. We bestuderen de eigenschappen van het stof en stellaire populaties
in deze sterrenstelsels in vergelijking tot blauwe, nog levende spiraalstelsels. Bovendien
analyseren wij het effect van de omgeving op deze sterrenstelsels en onderzoeken we of
er aanwijzingen zijn voor AGN activiteit. Verder onderzoeken wij de fractie van objecten
met bepaalde morfologische kenmerken (zoals bijvoorbeeld een balk) in rode en blauwe
spiraalstelsels.
134
Curriculum vitae
I was born on September 16, 1980 in Shiraz, Iran. My interest in Astronomy grew with
me from the time I was a child and started when I read Isaac Asimov’s book. During
high school, my keen desire triggered me to register at the first Iranian Astronomical
Institute for learning elementary Astronomy. The total solar eclipse in 1995 in Iran and
the passage of the Comet Hale-Bopp a year later inspired me to choose the subject of
physics at university (1998) in order to find the answers to thousands questions which
arose in my mind. My first year of studying at Shiraz University ended with the last total
eclipse of twentieth century (Aug 11 1999). This event led me to become a member of a
student group at Biruni Observatory, Shiraz University. This Observatory was active with
the photometry and data analysis of variable stars, especially eclipsing binary stars using
photomultiplier tube (PMT) with its 20” telescope.
During my undergraduate studies I attended small workshops, seminars and schools
to learn more about astronomy. While I was giving lectures in astronomy to the general
public and visitors of the Biruni Observatory, I also became acquainted with photometry
of variable stars and started to collaborate with postgraduate students o data acquisition,
photometry and photometric data reduction of eclipsing binary stars. I then decided to do
my B.Sc. project on a photometry of a delta scuti star under the supervision of Prof. N.
Riazi of Shiraz University. This experience introduced me to a wide area of observational
Astronomy and gave me an impulse to be enthusiastic in the field of observations.
The association with Biruni Observatory was continued after completing the B.Sc.
(2002) and I had the opportunity to work with a CCD camera. Because of lack of experiences with CCD imaging in my country, I tried to obtain experience with CCD imaging
and compiling information from different sources. The result of this effort was then published as a book (in Persian) in 2006 on “Digital Imaging and Astronomical Image Processing” in 263 pages, in which I have introduced the structure of CCDs, practical ways
for CCD imaging, photometry with CCDs, using digital cameras for astronomical imaging and introduction to image processing. The book is at the level of advance amateurs
and undergraduate students.
In September 2006, I started a master program in Astronomy at the university of
Sussex (Brighton, UK). I carried out my Msc project on the “Extraction of luminous red
galaxies (LRGs) from the Dark Energy Survey (DES) simulation”, under supervision of
Dr. Kathy Romer. After my Msc., I started to collaborate with the Galaxy Zoo team,
specifically, Prof. R. C.Nichol and Dr. K. Masters at the Institute of Cosmology and
Gravitation (ICG) in Portsmouth, on studying the properties of red spiral galaxies.
In January 2009, I started my PhD in Astronomy at the Sterrewacht Leiden (Leiden
University) under the supervision of Prof. Marijn Franx and Dr. Rik Williams funded by
the Marie Curie Initial Training Network of the European Union (ELIXIR). My research
has been dedicated to investigate how structural properties of galaxies such as their sizes,
135
Curriculum vitae
surface brightness profiles and other physical properties change with time.
During my PhD, I participated in the many schools, such as three ELIXIR Schools in
Astrium (Germany), ESA/ESTEC (Netherlands) and also a summer school in Heidelberg
(Germany) and NOVA fall school (Netherlands) and Oort Workshop (Leiden). I also presented my work in workshops, conferences and seminars, specifically in Lorentz Center
(Leiden), Oxford (UK), Madrid (Spain), Cambridge (IoA, UK) and Durham (UK).
I would like to continue my career in Astrophysics and I be will considering upcoming
postdoc opportunities.
136
Acknowledgements
The completion of this thesis would not have been possible without the encouragement,
support and help of many people. I would like to express my gratitude to all those who
gave me the support, inspiration and help to complete my thesis.
First, my family, which I am deeply indebted. Mahsan, your precious words, love,
kindness and encouragement brighten every day of my life. Mom and Dad, you are great
supporters. You taught me to be hard working, strong, patient and to be committed to
achieve the best. Mom and Dad, thank you for all of your love and valuable things you
have provided for me and all your dedication in every step of my life. My sisters, Najmeh
and Negin, you always gave me a lot of energy. I am very grateful to them.
My group members have been great supporters and help in many ways. Shannon, I
am very fortunate to have you as a friend and officemate, in one word, you are awesome.
Jesse, thank you for all your help, especially with the Dutch summary. Daniel, thanks
for useful discussions. Mattia, I am really happy for being in the same group. Adam, I
always enjoyed brightening discussions with you. Rychard and Ivo, thanks for all your
help. Ryan, thank you for the great supports at the beginning of my PhD. Maaike, thanks
for your friendship and all your help especially in my beginning days in the Netherlands.
Rik, I very much appreciated your stimulating suggestions, encouragement and all your
valuable hints all the time.
I am grateful to my other friends and colleagues in Leiden. Ali, Maryam, thanks for
your support and encouragements. Sean, I really enjoyed sharing our office with you and
I will definitely miss the useful conversations and discussions with you. Joakim, thanks
for your hospitality. Akbar, Behnam, Hossein and Behrooz, Maryam Hashemi, I am very
grateful for your friendship and warm and supportive words over the last four years.
I am very grateful to Ali Dariush whose helps, encouragements and friendship mean
a lot for me. I also would like to thank Kathy Romer, for inspiring me and encourage to
continue my study. Karen, Bob, I really enjoyed and learned a lot by collaborating with
you.
I also would like to acknowledge a large amount of support from the staff and computer group at Leiden Observatory over the last four years. I had also few visits to
Carnegie Observatories in Pasadena, and benefit from the staff and supports scientist there.
Thank you all.
137
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