stellar populations analysis along the hubble sequence · 2017-10-20 · stellar populations...

Stellar populations analysisalong the Hubble sequence

by

Anaely Pacheco Blanco

Thesis submitted in partial fulfillment of the requirementsfor the degree of

MASTER OF SCIENCE IN ASTROPHYSICS

at the

Instituto Nacional de Astrofısica,Optica y ElectronicaJanuary 2011

Tonantzintla, Puebla

Under the supervision of:

Dr. Jose Ramon ValdesINAOE

Dra. Olga VegaINAOE

Dr. Fabian Rosales-OrtegaConsejo Superior de Investigaciones Cientıficas,

INTA-CAB, Madrid, Spain

c©INAOE 2011The author hereby grants to INAOE permission to

reproduce and to distribute publicly paper and electroniccopies of this thesis document in whole or in part.

Inaoe.DBlue

Inaoep.DBlue

Abstract

In this thesis work a stellar populations study is proposed for two different galaxy sam-

ples. The first galaxy sample comprises 18 Early-Type galaxies from the bright end of

the Color-Magnitude Relation for the Virgo Cluster (Bower et al., 1992). For this sam-

ple, panchromatic data are available: ultraviolet broad-band photometry, optical spectra

and broad-band points and infrarred spectroscopy and photometry. These data will be

used to construct the panchromatic spectral energy distribution to be used in order to

calibrate the stellar population models. Also the spectralindices in the Lick/IDS system

were measured to charactrize the stellar populations. The observations were performed

with long-slit spectroscopy.

The second sample comprises 17 late-type galaxies observedby the PINGS project

(PPAK IFS Nearby Galaxies Survey) (Rosales-Ortega et al., 2010). The observations

were performed by the PPAK instrument (Verheijen et al., 2004; Kelz & Roth, 2006;

Kelz et al., 2006) at Calar Alto Observatory. The advantage of these observations is that

they were performed by means of integral field spectroscopy,giving spatially resolved

spectra.

The stellar populations analysis will be done with two different models, that were se-

lected in order to compare their results. TheBruzual & Charlot(2003) model performs

a full-spectrum fitting, while theBarbaro & Poggianti(1997) model performs the fitting

to specific wavelength intervals and spectral features.

Resumen

En este trabajo de tesis se presenta un estudio de poblaciones estelares y de la histo-

ria de formacion estelar en dos muestras diferentes de galaxias. La primera muestra

comprende 18 galaxias tempranas de la region brillante de la relacion Color-Magnitud

para el Cumulo de Virgo (Bower et al., 1992). De dicha muestra se cuentan con ob-

servaciones en diversas frecuencias del espectro: datos fotometricos en el ultravioleta,

espectros y puntos fotometricos en el optico y espectros ydatos fotometricos en el in-

frarrojo. Estos datos se usaran con el objetivo de construir una distribucion espectral de

energıa abarcando dichas frecuencias, la cual nos servir´a para calibrar los modelos de

sintesıs de poblaciones a utilizar. Para esta muestra tambien se calcularon los ındices

de Lick/IDS para poder caracterizar a la poblacion estelar. Las observaciones para la

muestra de galaxias tempranas fueron realizadas con rendija larga.

La segunda muestra a estudiar comprende 17 galaxias tardıas y fueron observadas como

parte del proyecto PINGS (PPAK IFS Nearby Galaxies Survey) (Rosales-Ortega et al.,

2010). Dichas observaciones fueron realizadas con el instrumento PPAK (Verheijen

et al., 2004; Kelz & Roth, 2006; Kelz et al., 2006) en el observatorio de Calar Alto. La

ventaja de estas observaciones consiste en que son espectros realizados con fibras de

campo integral, dando resolucion espacial de la informacion.

El estudio de las poblaciones estelares se llevara a cabo con dos modelos distintos, los

cuales fueron seleccionados para comparar los resultados obtenidos de ellos. El mod-

elo deBruzual & Charlot(2003) realiza un ajuste a todo el espectro mientras que el

modelo deBarbaro & Poggianti(1997) realiza el ajuste en intervalos y caracterısticas

espectrales seleccionadas.

Acknowledgments

• To Consejo Nacional de Ciencia y Tecnologıa (CONACYT) for the economicsupport provided for my studies.

• To my family for their inconditional support.

• To my advisors and collaborators for allowing me into their group.

• To my friends and collegues.

• To my mentor, German Martınez Hidalgo, for being the lightinto my suddenlydark path.

For all the ones that always stand next to

me, even when they are not physically

here.

Contents

Contents i

List of Figures iii

List of Tables v

1 Introduction 1

2 Stellar Populations Properties Diagnosis 17

2.1 Stellar Populations Indicators . . . . . . . . . . . . . . . . . . . .. . . 17

2.2 Spectral Indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

2.3 Spectral Fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

2.3.1 BP97Sim . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

2.3.2 GALAXEV . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

3 Galaxy Samples and Observations 29

3.1 Early-type Galaxies: The Virgo Cluster Sample . . . . . . . .. . . . . 29

3.1.1 Galaxy sample description . . . . . . . . . . . . . . . . . . . .30

3.1.2 Panchromatic Data . . . . . . . . . . . . . . . . . . . . . . . .31

3.2 Late-type Galaxies: The PINGS Sample . . . . . . . . . . . . . . . .. 40

3.2.1 Galaxy sample description . . . . . . . . . . . . . . . . . . . .44

3.2.2 Illustrative Selected Galaxies: NGC 1058 and NGC 1637. . . . 48

4 Preliminary Results and Future Work 53

4.1 ETGs sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53

4.1.1 ETGs data reduction . . . . . . . . . . . . . . . . . . . . . . .53

4.1.2 ETGs Analysis . . . . . . . . . . . . . . . . . . . . . . . . . .60

4.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71

i

Contents

Bibliography 81

ii

List of Figures

1.1 Hubble sequence . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2

1.2 Fundamental Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

1.3 Color-Magnitude Relation for Coma . . . . . . . . . . . . . . . . . .. 5

1.4 Tully-Fisher Relation . . . . . . . . . . . . . . . . . . . . . . . . . . .6

1.5 Galaxies and their spectra . . . . . . . . . . . . . . . . . . . . . . . . .8

1.6 Age-metallicity degeneracy . . . . . . . . . . . . . . . . . . . . . . .. 10

1.7 IFUs technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

1.8 Color-Magnitude Relation for the Virgo Cluster . . . . . . .. . . . . . 14

1.9 Example of IFS data . . . . . . . . . . . . . . . . . . . . . . . . . . .16

3.1 ETGs NIR spectra . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36

3.2 Passive ETGs MIR spectra . . . . . . . . . . . . . . . . . . . . . . . .41

3.3 Active ETGs MIR spectra . . . . . . . . . . . . . . . . . . . . . . . . .43

3.4 NGC 1058 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50

3.5 NGC 1637 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52

4.1 Absorption lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55

4.2 ETGs optical spectra . . . . . . . . . . . . . . . . . . . . . . . . . . .56

4.3 Index bands representation . . . . . . . . . . . . . . . . . . . . . . . .62

4.4 Indices central bands . . . . . . . . . . . . . . . . . . . . . . . . . . .65

4.5 Indices correlation plots . . . . . . . . . . . . . . . . . . . . . . . . .. 70

4.6 SED for the Virgo sample . . . . . . . . . . . . . . . . . . . . . . . . .72

iii

List of Tables

3.1 Virgo sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32

3.2 GALEX photometry . . . . . . . . . . . . . . . . . . . . . . . . . . .33

3.3 OAGH observational data . . . . . . . . . . . . . . . . . . . . . . . . .34

3.4 2MASS photometry . . . . . . . . . . . . . . . . . . . . . . . . . . . .38

3.5 PINGS sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46

4.1 Extraction aperture for the ETGs . . . . . . . . . . . . . . . . . . . .. 54

4.2 Equivalent apertures for HST photometry . . . . . . . . . . . . .. . . 59

4.3 HST photometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61

4.4 Index bands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63

4.5 LSS sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67

4.6 Lick/IDS FWHM . . . . . . . . . . . . . . . . . . . . . . . . . . . . .68

4.7 Instrumental indices . . . . . . . . . . . . . . . . . . . . . . . . . . . .76

4.8 ETGs centralσ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78

4.9 Transformation Coefficients . . . . . . . . . . . . . . . . . . . . . . .79

4.10 Working plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .79

v

Chapter 1

Introduction

Hubble Sequence

In the early 20s Edwin Hubble introduced a galaxy classification based on the morphol-

ogy observed from optical imaging, providing the followingtypes:

1. Elliptical (E0-E7)

2. Lenticular (S0 or SB0)

3. Spiral (Sa-c or SBa-c)

4. Irregular (Irr)

The morphological classification is sketched in Fig.1.1. Starting from the left hand-

side the elliptical galaxies run to the irregular ones, passing from the lenticular to the

simple and barred spirals.

Gerard de Vaucouleurs and Allan Sandage expanded to the Hubble morphological

classification in 1959. The Hubble morphological classification considered the tight-

ness of the spiral arms and the presence of a bar in the spiral galaxies, but they included

3 features in order to classify galaxies:

1. Bars: where the notation goes as follows, A for galaxies without bars, B for

galaxies with bars and AB for those showing weak bars.

1

Chapter 1. Introduction

Figure 1.1: Hubble sequence also known as the tuning fork

2. Rings: the galaxies showing rings are denoted by (r), (s) stands for the ones

without them and (rs) are called ”transition” objects.

3. Spiral arms: these are denoted as Sd (SBd) if they show diffuse spiral arms and

a weak bulge, Sm (SBm) for irregular galaxies without a bulgeand Im for very

irregular galaxies.

Despite the origin of the Hubble sequence as a morphologicalclassification, other

physical properties and observational trends of the galaxies are reflected in it, due to

their stellar population content (optical colors, opticallinear sizes, optical luminosity,

optical surface brightness affected by extinction, far infrared emission, radio continuum

emission, X-ray emission, neutral hydrogen mass and content, carbon monoxide (CO),

chemical abundances and total masses) as mentioned byRoberts & Haynes(1994). A

brief description of some main characteristics of each galaxy type is given below.

Elliptical Galaxies

These galaxies are characterized by their elliptical and smooth light profile known as

the de Vaucouleurs profile:

I(R) = I(Re) exp

[

−b

(

R

Re

)1/4

− 1

]

, (1.1)

whereb is such that the half-light is included into the effective radius Re andI(Re)

is the surface brightness at the effective radius. A subclassification described by the

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notationEn is given by their apparent flatteningn = 10(a − b)/a running from 0 to

7, wherea is the semi-major axis andb is the semi-minor axis. Their oblate shape is a

consequence of the velocity dispersion anisotropy. These galaxies are characterized by

their lack of significant amount of cold gas and dust, and therefore, recent and intense

star formation is not expected. As a consecuence their stellar populations are considered

to be old and their colors red. Their optical spectra is dominated by absorption features.

Elliptical galaxies are bright sources of X-rays due to their hot ionized gas (T∼ 107 K).

These galaxies are mainly found in dense environments like clusters. It is interesting

that these galaxies follow scaling relations such as:

The Fundamental Plane: Faber & Jackson found in 1976 a relation that was later

recognized as a projection of the Fundamental Plane (FP). They related the Lu-

minosity L of the galaxy with their velocity dispersionσ. The Fundamental Plane

later introduced byDressler et al.(1987) andDjorgovski & Davis(1987) relates

the effective radiusRe, the effective surface brightnessµB and the central veloc-

ity dispersionσ. This relation is shown in Fig.1.2.

Color-Magnitude Relation (CMR): Found for Virgo and Coma Clusters in 1972 by

A. Sandage, it is also related to the mass of the galaxy. This relation can set con-

straints on galaxy formation and evolution models (Kodama & Arimoto, 1997),

since the dispersion will give information about the formation process and the

slope may constrain the merging history (Renzini, 2006). An example of this

relation for the Coma Cluster is shown in Fig.1.3.

Lenticular Galaxies

This kind of galaxies share elliptical and spiral properties. They have a disc and a bulge

and could show a bar, but they lack of spiral arms, dust and gas. They are denoted asS0

(or SB0, if a bar is seen). In the disc, the stars follow circular rotating orbits, but in the

bulge they move randomly. The light profile of the disc follows the same exponential

law as spirals, detailed in Eq.1.2.

3


Figure 1.2: Fundamental Plane for field Early-Type Galaxies(squares) and for Comaellipticals (triangles,Jørgensen et al.(1995)) taken fromRenzini(2006). Blue squares arefrom Treu et al.(2005) while red squares and black circles are fromdi Serego Alighieriet al.(2005)

Spiral Galaxies

This name came from the spiral pattern present in these type of galaxies. There is also

a bulge and a disc and in some cases a bar. These galaxies are denoted by the notation

S (or SB; for barred spirals) followed by a letter (a, b or c) depending on the tightness

of the spiral pattern and the size of the bulge. The disc follows an exponential light

profile:

I(R) = I0 exp (−R/R0). (1.2)

whereI0 is the central surface brightness andR0 the scale-length. The stars of the

disc in these galaxies move around the galactic center in nearly circular orbits. This

galaxy type follows an empirical relation known as the Tully-Fisher relation, similar

to the Faber-Jackson relation for elliptical and lenticular galaxies. This relates their

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Figure 1.3: CMR (U-V) vs MV for the Coma Cluster taken fromRenzini(2006). Here thecolors represent different galaxies types. Red ones represent elliptical galaxies, orangeare S0, blue comprises spiral and irregular galaxies and open circles are unclassifiedgalaxies.

luminosity L (or absolute magnitude M) with the rotational velocity Vrot as it is shown

in Fig. 1.4. In the case of spiral galaxies they present a variety of stellar populations due

to their active star formation history. From the colors, thereddish bulge is dominated

by older stars while the blueish arms are dominated by gas, dust and younger stars.

Thus a stellar population analysis in this case is more complex due to the presence of

various generations of stars and the effects of dust extinction. The optical spectrum of

spiral galaxies show intense emission lines due to the gaseous component, but also a

stellar contribution of the subjacent older population.

Irregular Galaxies

Those galaxies without a distinctive structure fall here. They are denoted byIrr and

the dwarf irregulars are the most common in the universe. Examples of these are the

Magellanic Clouds.

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Figure 1.4: Tully-Fisher relation (I-band) taken fromBlanton & Moustaka(2009)

Stellar Populations of Early and Late Type Galaxies

The division in early and late type galaxies is related to theerroneous interpretation

that this classification corresponded to an evolutionary sequence. Nevertheless, the

Hubble sequence is related to observable and physical parameters of the galaxies like:

bulge/disc luminosity ratio, stellar population, integrated spectra, star formation histo-

ries (SFHs), relative HI/HII content and chemical abundances of the ISM (Blanton &

Moustaka, 2009).

Basically, Elliptical and Lenticular galaxies belong to the Early-Type Galaxies (ETGs)

and the Spiral and Irregular galaxies to the Late-Type Galaxies (LTGs). The main

classification parameter is their stellar populations. Traditionally, it is thought that the

ETGs are dominated by an almost homogeneous population of old and solar-metallicity

stars formed during an initial intense star formation burstand evolved passively since

then (no recent episodes of star formation) while the LTGs are dominated by young

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and high-metallicity stars and, their higher abundance of neutral and molecular hydro-

gen makes them favorable for recent star formation episodes(e.g. Strateva et al., 2001;

Blanton & Moustaka, 2009).

Therefore, the integrated spectra of an ETG is mostly dominated by red giants and

AGB stars, with intense absorption and metalic lines (e.g.Renzini, 2006, and refer-

ences therein). For the LTGs, on the contrary, the nebular emission is intense compared

to the underlying stellar continuum. An example of the differences in their spectra is

shown in Fig.1.5.

Only the nearest galaxies can be resolved into individual stars, therefore, the study

of their stellar populations can be done only by the analysisof their integrated light.

This limitation made necessary the development of stellar population synthesis mod-

els. They are tools used to interpretate the observations (like colors or spectral features)

and to determine the fraction of stars contributing to the integrated light. Nowadays

there are plenty of population synthesis tools at the disposition of the scientific com-

munity, provided byWorthey(1994); Buzzoni(1995); Bressan et al.(1996); Maraston

(1998, 2005); Bruzual & Charlot(2003); Fioc & Rocca-Volmerange(1997); Vazquez

& Leitherer (2005); Vazdekis et al.(2003); Gonzalez-Delgado et al.(2005) andCid-

Fernandes et al.(2005), but all are in continuous improvement by the inclusion of

new stellar libraries, the effects of non-solar element abundances and enrichment (e.g.

Pietrinferni et al., 2006), the advanced stellar evolutionary stages (e.g.Marigo, 2007)

and binary stars (e.g.Eggleton, 2009; Li et al., 2006). ETGs are important in the con-

text of galaxy formation and evolution, because a considerable fraction of their bary-

onic mass (60-70%) is assembled into stars (Fukugita & Peebles, 2004). As a result

of their scaling relations (FP and CMR) these galaxies are considered as an almost ho-

mogeneous old stellar population and then treated as a simple stellar population (SSP).

A SSP is a coeval (born at the same time) and chemically homogeneous (same ini-

tial chemical abundances) population. However, recent observations have showed that

these galaxies are not as passive as first thought, revealingdisturbed structures (e.g.

Rampazzo et al., 2005; Panuzzo et al., 2007), dust and shells (e.g.Colbert et al., 2001),

UV excess (e.g.Bertola, 1986; Bica et al., 1996) and infrared emission lines (e.g.Bres-

san et al., 2006, PAH), suspecting the evidence of a recent rejuvenation event of the

ETGs.

From previous studies ofETGs using stellar population synthesis techniques interest-

7


Figure 1.5: Spectra of the different morphological classes, image fromStrateva et al.(2001).Where z is the redshift, r∗ and u∗ are the measured magnitudes from the SDSS filters r and u,respectively.

ing conclusions have been made.Bower et al.(1992) from the analysis of the CMR of

the Virgo and Coma Clusters showed that cluster ellipticalshave formed the majority

of their stars atz & 2. Also, Bernardi et al.(2003, 2006) from the analysis of the FP

found that ETGs in low-density environments are in average 1Gyr younger than those

on denser environments. However,Trager et al.(2008) find that ETGs in the Coma

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cluster and field ellipticals show the same mean age.

Balmer absorption lines (Hγ, Hδ and Hβ) are commonly used as age estimators for

old stellar populations, while for the metallicity the<Fe> and Mg2 indices are often

used. Notice, however that an absolute determination of theages and the metallicities

is not possible due to the age-metallicity degeneracy (Worthey, 1992). This degeneracy

makes necessary the searching of new spectral indices to break it (e.g.Yamada et al.,

2006). In Fig. 1.6(a)I show the optical spectra of a SSP for two different ages and

metallicities (10 Gyr with Z=0.008 and 4.5 Gyr with Z=0.02).It is evident that they are

indistinguishable, this is the age-metallicity degeneracy effect. In Fig.1.6(b)the same

SSPs are shown but in a wider spectral range, from the ultraviolet to the infrared. From

this plot, it is shown that in order to make a precise study of the stellar populations in

ETGs, a panchromatic approach is necessary.

The most massive galaxies present enhanced Mg abundances relative to Fe, that

arises from theα−enrichment (including Mg) produced by the Type II supernovae (e.g

Wheeler et al., 1989). A lower limit to the formation redshiftzF & 2.5 of ETGs was set

by Kelson et al.(2001) using Balmer absorption lines.Thomas et al.(2005) found that

the metallicity and the [α/Fe] ratio correlates to the velocity dispersion (or mass).They

also find that lower-mass ellipticals show evidence of recent (. 1 Gyr) star formation.

This was confirmed byKaviraj et al.(2007b) using GALEX observations.

From all the above, we can conclude that the study of the stellar populations in ETGs is

not finished yet. The main present problems are the age-metallicity degeneracy and the

evidence of rejuvenation episodes, implying that an ETG cannot be treated as a SSP.

The study of the stellar populations inLTGs is even more complicated due to their

more complex SFHs and the presence of dust extinction (e.gLeitherer et al., 1996).

Therefore, they can not be treated as a SSP, and they must be analyzed with the com-

posite stellar population (CSP) method (e.g.Serra & Trager, 2007). A combination

of different generations of stars (each one treated as a SSP)would reproduce the in-

tegrated characteristics. So, LTGs are still unexplored objects due to their complexity

and their substructure (Ganda et al., 2006), and mainly the two-dimensional kinematics

and stellar population analysis.

For a long time the spectroscopy has been done with long-slitspectrographs. The

information derived by this technique depends on the size ofthe slit and in which region

9


(a) Optical spectra

(b) Spectrum from the ultraviolet to the infrared

Figure 1.6: Age-metallicity degeneracy in the optical wavelength range can be broken usingother wavelength ranges such as Ultraviolet or Infrared

10

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of the galaxy it is positioned. A great variety of previous studies used this technique

in the nuclear regions of the galaxies, sampling a small region (Trager et al., 1998;

Worthey, 1992; Annibali, 2005) and providing global parameters of the galaxy, lacking

of a truly spatially resolved study. The recent developmentof new instrumentation,

as Integral Field Spectroscopy, has allowed the analysis ofspatially resolved stellar

populations. In the next section a brief description of the Integral Field Spectroscopy is

given.

Integral Field Spectroscopy

Integral Field Spectroscopy (IFS) consist of a simultaneously spatially resolved spectra

over a 2D field, producing a datacube of a scalar quantity related to a flux density as a

function of spatial coordinates in the field and wavelength:I(x, y, λ). There are several

instruments and techniques to achieve IFS. A brief explaination of each one follows.

Integral Field Units

Besides the spectrograph, an Integral Field Unit (IFU) is necessary for obtaining IFS.

The IFU will divide the 2D spatial plane into a continuous array and this can be done

in three different ways:

1. Lenslet array: A microlens array (MLA) is the dividing element. The incoming

light will be concentrated in a small dot that will be dispersed by the spectro-

graph. The MLA can be tilted from the optical axis of the system to avoid that

the spectra of each dot overlaps.

2. Fibres: This is the most used technique. The dividing element is a bundle of

optical fibres which transfer the light into the spectrograph. A disadvantage of

this technique is that the sampling is not contiguous due to the gaps between the

fibre cores, this can be corrected by adding an array of lenslets in front of the

fibre bundle.

3. Image-slicer: The dividing element is a segmented mirrorin thin horizontal sec-

tions. Suitable for infrared wavelengths.

11


Fabry-Perots or tunable filters

Fabry-Perot imaging spectrographs can cover a large FoV (∼ 5 arcmin) with high spa-

tial and spectral resolution in a single exposure but only for a single wavelength, so for

completing the datacube you must scan along the wavelength range of interest.

Multi-Object Spectroscopy

This technique is designed to obtain spectra of multiple andseparated targets in the

FoV by using a slit mask or fibres or lensets that can be positionated in the region of

interest.

The IFS techniques described are illustrated in Fig.1.7.

Figure 1.7: Schematic view of the different IFUs techniques, image taken fromIntegral FieldSpectroscopy Wiki(2010)

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Objectives and Methodology

The principal aim of this thesis is to study the stellar content and star formation history

in different types of galaxies along the Hubble sequence. The stellar populations in a

galaxy provide information on their formation and evolution. In order to do the analy-

sis, we will perform the stellar population synthesis method by using the state of art of

stellar atmosphere models and stellar evolutionary tracks.

In order to reach this goal we have selected two different samples of nearby galax-

ies. The ETGs sample is composed of galaxies belonging to thebright end of the

color-magnitude relation of the Virgo cluster (Bressan et al., 2006). For this sample we

already have infrared data (SPITZER/IRS spectra and broad-band images, NIR spec-

troscopy and 2MASS photometry), optical data (OAGH spectraand HST photometry)

and ultraviolet data (GALEX photometry). The available data will allow us to con-

struct, for the first time, the complete panchromatic SED forthese galaxies. The SED

will allow us to study the energetic sources at different wavelengths (e.g.Boselli et al.,

2003) and to calibrate our stellar population synthesis models.We will also calculate

spectral indices in the Lick/IDS system and their correlation to the SED, being useful

for models recalibration. The description of the Lick/IDS system and the technique will

be given in more detail in Section2.2.

The LTGs sample is composed of a variety of nearby spiral galaxies (normal, lop-

sided, interacting and barred). We will use the advantage ofIFU observations per-

formed with the PMAS/PPAK spectrograph at Calar Alto as partof the PINGS (PPAK

IFS Nearby Galaxies Survey) project (Rosales-Ortega et al., 2010). Two galaxies of

the PINGS sample were selected: NGC 1058 and NGC 1637 as the initial sample for

the LTGs study. The stellar population synthesis will be initially performed with two

different models:Bruzual & Charlot(2003) model and theBarbaro & Poggianti(1997)

model. These models were in principle selected because the first one is a full-spectrum

fitting while the second fits specific wavelength intervals and spectral features. This

will allow us to compare the results derived from both modelsand to inspect the ad-

vantages or disadvantages of using this kind of methods. These galaxies were chosen

mainly because the mosaic covers the full optical size (defined by the B-band 25 mag

isophote) of the galaxy, giving a good surface coverage so they can provide a complete

13


(a) CMR (U-V) (b) CMR (V-K)

(c) CMR (J-K)

Figure 1.8: Color-Magnitude Relation of the Virgo Cluster taken fromBower et al.(1992).

14

/home/anaely/Desktop/pre-PhD/tesisINAOE/figures/cmrbowera.eps

/home/anaely/Desktop/pre-PhD/tesisINAOE/figures/cmrbowerb.eps

/home/anaely/Desktop/pre-PhD/tesisINAOE/figures/cmrbowerc.eps

spatially resolved stellar population study.

The first population synthesis model (Bruzual & Charlot, 2003) was selected because

one of the galaxies in the sample (NGC 628) has been already studied with it (Sanchez

et al., 2010). The other population synthesis model (Barbaro & Poggianti, 1997) is

adopted in order to compare the results and taking advantageof the capability of the

model to work with selective extinction and non-continuousSFHs. It is also desirable

to conduct a panchromatic study for the LTGs sample, starting with infrared photome-

try using CANICA at the OAGH, that will allow us to study the older population and

the extinction. The details regarding to the observationalprogram are yet to be anal-

ysed.

To show the advantages of the IFS observations that will be used to obtain the spatially

resolved stellar population study for our LTGs sample, the optical spectra for different

regions inside a galaxy of this sample (NGC 1058) are shown inFig. 1.9.

The thesis is structured as follows:

• Chapter 2: This gives a description of the tools to be used in order to study the

stellar populations of our samples of galaxies.

• Chapter 3: Provides a description of the samples (ETGs and LTGs) and their

available observational data (long-slit spectroscopy andIFS).

• Chapter 4: Here I present the preliminary results and the future work.

15


(a) Image atλ = 4050A and selected spaxels

(b) Optical spectra from the selected spaxels

Figure 1.9: Optical spectra for selected regions (arm, intra-arm, center and a HII Region) inNGC 1058

16

/home/anaely/Desktop/pre-PhD/tesisINAOE/figures/index_plot.ps

/home/anaely/Desktop/pre-PhD/tesisINAOE/figures/ngc1058regs.eps

Chapter 2

Stellar Populations Properties

Diagnosis

The evolution of a galaxy is imprinted in their stellar populations, as a result of their

Star Formation History (SFH). Since the analysis made by Roberts(1963) the Hubble

sequence has been seen as a monotonic sequence in present-day Star Formation Rates

(SFRs) and past SFHs. This lead to the development of severaldiagnostic methods

for determining the global SFRs. The first attempt based on the integrated colors was

done byTinsley (1968), Tinsley (1972) and Searle et al.(1973). Direct diagnostic

methods based on integrated emission-line fluxes (Cohen, 1976; Kennicutt Jr., 1983),

near-ultraviolet continuum fluxes (Donas & Deharveng, 1984) and infrared continuum

fluxes (Harper & Low, 1973; Rieke & Lebofsky, 1978; Telesco & Harper, 1980) are

commonly used to determine very recent (∼ 107 yr) star formation events. This work

will be devoted to study the SFH of our sample of galaxies, andthen, the earliest star

formation events as a function of time. The following sections in this Chapter will be

dedicated to explain the different methods used to analyze the SFHs.

2.1 Stellar Populations Indicators

Generally, galaxies can not be resolved into individual stars which limits their study to

the integrated light where the contributions of all their components are mixed. For this

reason, a stellar population synthesis model must be able toreproduce the integrated

17

Chapter 2. Stellar Populations Properties Diagnosis

properties of a galaxy in order to infer the age, metallicityand star formation history

(SFH) of its population. We can distinguish between two approaches of population

synthesis: an empirical and an evolutionary one.

In the empirical approach, the observed spectrum of a galaxyis reproduced by a combi-

nation of spectra of individual stars or star clusters with different ages and metallicities

from a library (Faber, 1972; O’Connell, 1976; Pickles, 1984). This approach does not

consider stellar evolution and as a consequence is not possible to study the past or future

of the galaxy spectrum. On the other hand, the evolutionary approach takes into account

the stellar evolution (Tinsley, 1978; Bruzual, 1983; Renzini, 1986; Renzini & Buzzoni,

1986; Arimoto & Yoshii, 1987; Worthey, 1994; Bressan et al., 1994; Maraston, 2005).

Basically, two main ingredients are necessary for the latter: a stellar evolutionary pre-

scription and a stellar spectral library.

Ideally, the stellar evolutionary prescription must include all the evolutionary phases

(from the earliest to the latest) for all mass ranges. In the case of the stellar spectral

library, this should provide a complete coverage of the Hertzprung-Russell diagram,

accurate atmospheric parameters (effective temperatures, surface gravities and metal-

licities), and the most complete wavelength coverage with good spectral resolution.

The library can be theoretical (based on atmosphere models,limited by the knowledge

of the physics of stellar atmospheres) or empirical (based on observations of stars, lim-

ited by the quality of the observations and biased by the targeted stellar population).

Other ingredients are: the Initial Mass Function (IMF), that will populate the zero-age

main sequence according to its slope and their lower and upper mass limits, and the

SFH, that will give the time dependence of the stellar population spectrum.

In order to determine the SFHs from the integrated spectra ofthe galaxy, you can

use the spectral indices (e.g.Dressler & Gunn, 1983; Buzzoni et al., 1992; Bressan

et al., 1996) or a full-spectrum fitting technique (e.g.Tinsley & Danly, 1980; Cardiel

et al., 2003; Cid-Fernandes et al., 2005). The spectral indices consider some interesting

spectral features from which the stellar populations age and metallicity can be derived,

while the full-spectrum fitting technique consider all the wavelengths involved in the

observational data available. In the following sections I give a more detailed description

of these techniques. In this thesis, in order to perform stellar population synthesis, we

will use the spectral indices for the ETGs sample while for the LTGs sample the two

18

2.2. Spectral Indices

stellar populations models will be used by means of two different models: the simplified

model of Barbaro & Poggianti(1997) (hereafter BP97Sim) and GALAXEV byBruzual

& Charlot (2003). Both models are described in the following subsections.

2.2 Spectral Indices

A spectral index, or line-strength, is a measure of the intensity of a spectral feature

of interest. Since first introduced byFaber et al.(1977) and Burstein et al.(1984),

the Lick/IDS system has been widely used in order to trace thestellar populations of

intermediate-old systems from their optical integrated spectra. The Lick/IDS system

consists of 25 spectral indices defined for a spectral dataset of 460 stars, 35 globular

clusters and 400 galaxies observed between 1972 and 1984 at the Lick Observatory

with a Cassegrain spectrograph in the wavelength range between 4000-6400A and

∼ 8 A resolution.

The determination of the stellar populations ages, metallicities and abundances is done

from an adequate combination of the line-strength indices sensitive to the parameter of

interest and then compared to the modeled line-strengths. This method relies on the de-

pendence of the spectral features present in the optical spectra with the temperature and

luminosity class of the stars. Due to the small wavelength interval between the spectral

features and that are used as flux ratios, this technique is not affected by extinction and

distance.

The Balmer lines (Hβ, HγA, HγF , HδA, HδF ) had been widely used as age indicators,

while a combination of Fe and Mg indices are used for the metallicity estimation (e.g.

O’Connell, 1980; Dressler & Gunn, 1983; Worthey & Ottaviani, 1997; Ferreras et al.,

1999; Wu et al., 2005; Jimenez et al., 2007; Harrison et al., 2010). Some of these

combinations are:

< Fe >= (Fe5270 + Fe5335)/2 (2.1)

[MgFe] =√

Mgb < Fe > (2.2)

The detailed process on the measurement and calibration of the spectral indices is given

in Section4.1.2.

19


2.3 Spectral Fitting

2.3.1 BP97Sim

Model Description

A simplified model of the original described by Barbaro & Poggianti (1997) is prefered

in order to reduce the model parameters, to study discontinuous star formation histories

and to allow the implementation of selective extinction fordifferent stellar popula-

tions, also because the basic physical parameters that describe the integrated spectra

are included. In this approach the integrated spectra is a combination of 10 stellar pop-

ulations of different ages. Each generation was born with a Salpeter IMF in the mass

range 0.1-100 M⊙. The ages of the populations are:

1. Youngest population (3 × 106, 8 × 106 and107 yr) responsible for the ionizing

photons that produce the emission lines.

2. Intermediate population (5 × 107, 108, 3 × 108, 5 × 108 and109 yr) responsible

for the strongest absorptions of the Balmer lines (EW(Hδ)> 4A)

3. Older population (> 1 Gyr) contributing significantly in the spectral continuum

affecting the spectral lines equivalent widths.

These populations were chosen taking into account observational constraints for the

evolutionary timescales.

For each single generation the integrated and composite spectra are produced using

the original model ofBarbaro & Poggianti(1997). This is an evolutionary population

synthesis model that computes the integrated spectra of a galaxy from the far UV to

the infrared and includes the contributions from the stellar populations and the ionized

interstellar gas. The non-thermal gaseous emission (from non-stellar ionizing sources)

and the far IR emission of dust are not included. A brief description of the original

model is given byBarbaro & Poggianti(1997).

1. Stellar component:

20

2.3. Spectral Fitting

• All the evolutionary phases -up to the AGB and post-AGB- are included,

except the pre-main sequence. Different metallicities areallowed.

• For stars withTeff > 5500 K and in the UV region, the spectral library

is based on the stellar atmospheres ofKurucz(1993). Covering the wave-

length range< 14500A.

• For stars withTeff < 5500 K observed spectra fromLancon & Rocca-

Volmerange(1992) were adopted. Wavelength range: 14500-25000A, with

a resolution of 25-70A and a unique calibration independent of Z.

• The region forλ > 25000 A is not included because it is strongly affected

by dust emission.

• For the fitting of the visible and infrared spectra an interative procedure was

performed using as an aid a blackbody spectrum.

• In the far UV region, forTeff > 50000 K, the spectra were approximated

using a blackbody distribution.

• In the wavelength range 3500-7500A , for all the luminosity classes at solar

metallicity with a resolution of 4.5A , the spectral library ofJacoby et al.

(1984), which covers the spectral types O-M was used.

2. Ionized gas emission (line and continuum spectrum):

• This contribution is added for objects younger than 107 yr.

• Ionizing flux of the young population is computed with the stellar atmo-

spheres model ofKurucz(1993).

• Luminosities of the nebular hydrogen lines (Balmer series)are derived us-

ing recombination case B.

• Luminosities of other lines are derived using HII region models byRubin

(1985) andStasinska(1990).

Technique

For producing the synthetic spectra in this case, we will follow the procedure given in

Poggianti et al.(2001) andMayya et al.(2004). First, in order to compare the model

21


with the observations, the modeled spectra (∼ 4 A) have to be broadened for matching

the resolution of the observations (7A for ETGs and 8A for LTGs). The samples are

described in more detail in Chapter3. Each generation is assumed to be extincted by

a uniform screen of dust with a Galactic extinction lawRV = AV /E(B − V ) = 3.1

(Cardelli et al., 1989), butE(B−V ) varies for different populations. The best-fit model

will be chosen as the one that minimizes the differences between observed selected

features and the modeled ones. A merit function will be constructed for N=12 features

( EW: [OII]3727, Hδ, Hβ, Hα, Relative Intensities; between them, of the continuum

flux in the wavelength ranges: 3770-3900, 4020-4070, 4150-4250, 4600-4800, 5060-

5150, 5400-5850, 5950-6250 and 6370-6460A):

(MF )2 =N

∑

i=1

W 2i

(

Oi − Mi

Ei + E0

)2

(2.3)

wherei refers to the features of interest,Mi is the value predicted by the model,Oi

is the observed value,Ei is the accuracy; being 1% for the continuum features and

10% for the EWs,E0 is the minimum error,Wi is the weight of the feature, being

1 for all the features except for 3770-3900A (0.4) and [OII]3727 (0.5) due to the

flux calibration uncertainty of Jacoby’s spectra below 4000A and that [OII]3727 is not

related in a simple way to the star formation rate being sensitive to factors like: hardness

of the ionizing spectrum, local conditions of the nebula, the density and metallicity

of the gas (Poggianti et al., 2001) . The merit function will be minimized using the

simulated annealing method with the Numerical Recipes’ routine AMEBSA available

from Numerical Recipes Third Edition Webnotes(2007).

2.3.2 GALAXEV

Stellar Evolution Prescription

This model allows the use of three stellar evolution prescriptions:

1. Padova 1994:

• Stellar evolutionary tracks computed byAlongi et al.(1993), Bressan et al.

(1993), Fagotto et al.(1994) andGirardi et al.(1996)

22


• Initial chemical compositions Z1 = 0.0001, 0.0004, 0.004, 0.008, 0.02, 0.05

and 0.1, where Y=2.5Z+0.23 with Z⊙=0.02 and Y⊙=0.28.

• Initial masses in the range0.6 ≤ m ≤ 120 M⊙, except for Z=0.0001 where

0.6 ≤ m ≤ 100 M⊙ and Z=0.1 where0.6 ≤ m ≤ 9 M⊙, because for

more massive stars mass-loss by stellar winds domines and for this high

metallicity mass-loss rates were not available.

• Radiative opacities ofIglesias et al.(1992).

• Includes phases of stellar evolution from the zero-age mainsequence (ZAMS)

to the beginning of the thermally pulsing regime of the asymptotic giant

branch (TP-AGB) for low and intermediate masses and core-carbon igni-

tion for massive stars.

• For solar composition, the models are normalized to the temperature, lumi-

nosity and radius of the Sun at age of 4.6 Gyr.

• Overshooting included for convective cores ofM > 1.5 M⊙ in a mild

regime (Λc ≤ 0.52 ), for the mass range 1-1.5 M⊙ with a reduced efficiency,

also included for the envelopes of low and intermediate massstars.

2. Padova 2000:

• New version of the Padova 1994 library.

• Revised equation of state.

• Low-temperature opacities.

• Inclusion of masses down to m=0.15 M⊙, but no more massive than 7 M⊙

because the new equation of state affects mainly the evolution of stars with

M< 0.6 M⊙.

• Chemical abundances Z=0.0004, 0.004, 0.008, 0.019 and 0.03, where Y=2.25Z+0.23

with Z⊙=0.019 and Y⊙=0.273.

3. Geneva:1 here X+Y+Z=1, where X is the H relative mass abundance, Y is the He relative mass abundance

and Z is the relative mass abundance of higher elements2 where the free path of the convective elements is given asΛc × Hp, whereHp is the local pressure

scale height andΛc is a free parameter to be fixed.

23


• Only for solar metallicity.

• Tracks ofSchaller et al.(1992) for m ≥ 2 M⊙, Charbonnel et al.(1996) for

0.8 ≤ m < 2 M⊙ andCharbonnel et al.(1999) for 0.6 ≤ m < 0.8 M⊙.

• Abundances X=0.68, Y=0.30 and Z=0.02.

• Opacities ofRogers & Iglesias(1992) for m ≥ 2 M⊙, Iglesias & Rogers

(1993) for 0.8 ≤ m < 2 M⊙.

• Phases of stellar evolution: ZAMS to the beginning of the TP-AGB or core-

carbon ignition according to the initial mass.

• Overshooting included for convective cores ofm > 1.5 M⊙ in a mild

regime.

• Differences of this model to the Padova 1994 one: absence of overshooting

for the mass range 1-1.5 M⊙ and in the envelopes of low and intermediate

mass stars, higher helium fraction, inclusion of mass loss along the red giant

branch, convection treatment in the core-helium burning, internal mixing

and mass loss of masive stars.

4. Supplements:

• Evolutionary tracks of the low and intermediate mass stars beyond the early-

AGB with TP-AGB and post-AGB. Adoption of the effective temperatures,

bolometric luminosities and lifetimes of the TP-AGB stars of the Vassil-

iadis & Wood (1993) models for the metallicities Z=0.001, 0.004, 0.008

and 0.016.

• Transition from the M-type star (Oxygen rich) to C-type (Carbon rich) due

to the Carbon dredge-up defined byGroenewegen & de Jong(1993) and

Groenewegen et al.(1995) models, requiring that, for a given initial main-

sequence mass the relative durations of the two phases are the same given

by these models.

• For the post-AGB evolution, the tracks are taken from the models ofVassil-

iadis & Wood(1994) for the metallicities in the range0.001 ≤ Z ≤ 0.016.

For lower-mass stars, theSchonberner(1983) track of a 0.546 M⊙ with

Z=0.021 was adopted.

24


• For ages greater than 20 Gyr, white dwarf cooling models for0.4 ≤ m ≤1.0 M⊙ of Winget et al.(1987) were adopted.

• Unevolving main-sequence stars of masses0.09 ≤ m < 0.6 M⊙.

Stellar Spectral Library

1. Low Resolution:

• Model atmospheres for stars in the metallicity range10−5 . Z . 10 Z⊙

from Lejeune et al.(1997) andLejeune et al.(1998) in the wavelength range

91 A to 160µm, with λ/∆λ ≈ 200 − 500. As Bruzual & Charlot(2003)

mentioned they used Kurucz (1995) theoretical spectra for the hotter stars

(O-K), observed spectra fromBessell et al.(1989), Bessell et al.(1991) and

Fluks et al.(1994) for M giants,Allard & Hauschildt(1995) for M dwarfs.

There are three available versions of this library:

(a) BaSeL 1.0: spectra rebinned on homogeneous scales of fundamen-

tal parameters (effective temperature, gravity, metallicity) and wave-

length.

(b) BaSeL 2.2: Corrections for systematic errors evident inthe UBVRI-

JHKL colour-temperature relations (Lejeune et al., 1998) applied to

BaSel 1.0. Correction derived for solar metallicity applied to all metal-

licities.

(c) BaSeL 3.1: Semi-empirical corrections made byWestera(2001) and

Westera et al.(2002) for model atmospheres at non-solar metallicities

using metallicity-dependent UBVRIJHKL color calibrations.

• The models cover temperatures2000 ≤ Teff ≤ 50000 K

• For stars hotter than 50 000 K (50000 ≤ Teff ≤ 106 K), the non-LTE model

atmospheres ofRauch(2002) for Z=Z⊙ and Z=0.10 Z⊙ was adopted. This

model covers the wavelength range 5-2000A with a resolution of 0.1A.

• For Z=0.0004 and 0.0001,Teff ≥ 50000 K pure blackbody spectra was

assumed, also for stars cooler than 2000 K, for all metallicities.

2. Higher Resolution:

25


• STELIB, a library of 249 observed spectra of stars (LeBorgne et al., 2003)

in a wide range of metallicities (−2.0 < [Fe/H] < +0.50)3 . In the wave-

length range: 3200-9500A, with a FWHM of 3A(λ/∆λ ≈ 2000) and a

sampling interval of 1A, S/N∼ 50 pixel−1. Covering the spectral types from

O5 to M9 and luminosity classes from I to V. Due to contamination from tel-

luric features the wavelength intervals 6580-6950A and 7550-7725A were

not considered in the fits.

3. Wider Spectral Coverage:

• Based on an observational spectral library of 131 Galactic stars, (Pickles,

1998). Covering the spectral types: O5-M10 and luminosity classes: I-V.

• The spectral library is divided in three metallicity groups: 11 considered

metal-weak, 12 metal-rich and 108 with solar metallicity.

• Wavelength range: 1150A-2.5 µm, with a sampling interval of 5A /pixel,

giving λ/∆λ ≈ 500.

• Main sequence and subgiant stars hotter than 40000 K, giant stars hotter

than 32000 K, supergiants hotter than 26000 K and cooler than4000 K are

not included.

• Ultraviolet spectra based on International Ultraviolet Explorer (IUE) obser-

vations, with a sampling interval 1-1.2A for the wavelength range 1205-

1935A, 2A for 1935-3150A. For the Extreme UV (91-1195A) is completed

with BaSeL 3.1 spectra.

• In the infrared (2.5-160µm) for M0-M10 giant stars synthetic spectra from

Fluks et al.(1994). For 5000A -10 µm, 10 equally spaced stellar temper-

atures in the range2600 ≤ Teff ≤ 4400 K based on theSchultheis et al.

(1999) model.

4. Carbon stars and super wind phase:

• Period-averaged spectra for models and observations of Galactic stars.

3 Being[Fe/H ] = log(NFe/NH)∗− log(NFe/NH)⊙ whereNFe andNH is the number of iron andhydrogen atoms per unit of volume, respectively

26


• For C-type TP-AGB stars, solar metallicity models for carbon stars in the

range2600 ≤ Teff ≤ 3400 K of Hofner et al.(2000), wavelength range:

2500A -12.5µm.

• Empirical corrections for the UBVRIJHK broad-band colors were applied.

• For the superwind phase, 16 TP-AGB stars with VRIJHKL data and partial

UB information were used.

Technique

In this Section, we will briefly describe the technique used for producing synthetic

spectra, called Isochrone synthesis. This is based on the assumption that any star for-

mation history can be expanded in series of instantaneous bursts called Simple Stellar

Population (SSP).

As mention byCid-Fernandes(2007) the integrated light of a LTG can be described

by the contribution ofN∗ different generations of stars (different ages and metallicities)

given by

Lgalλ (~x, AV ) = Lgal

λ0

N∗∑

j=1

xjlλ(tj, Zj) ⊗ LOSV D × 10−0.4AV rλ (2.4)

wherelλ is the spectrum assigned from the spectral library of the population j normal-

ized atλ0, tj andZj are the ages and metallicities of each generation,xj is its light

fraction,LOSV D is the line-of-sight velocity distributions andrλ = (Aλ − Aλ0)/AV

is the reddening law. The SFH is encoded in the population vector~x. The population of

the different evolutionary phases along the isochrone is given by the IMF. To each star

populating the isochrone, a spectrum is assigned from the stellar spectral library in use.

The IMF is an adjustable parameter, but theChabrier(2003) parametrization is used.

φ(log m) ∝

exp[

− (log m−log mc)2

2σ2

]

m ≤ 1M⊙

m−1.3 m > 1M⊙

(2.5)

wheremc = 0.08M⊙ is the mean mass,σ = 0.694 , with lower and upper mass cut-offs

mL = 0.1M⊙ andmU = 100M⊙. The SED of a SSP is normalized to a total stellar

4 σ2 =< (log m− < log m >)2 > is the variance inlog m

27


mass of 1 M⊙ at aget′ = 0, sampled in 221 unequally spaced time-steps from 0-20 Gyr

and covering the wavelength range 90A-160µm.

28

Chapter 3

Galaxy Samples and Observations

In this Chapter I will describe the selection criteria defining the galaxies samples di-

vided in early and late types. The observational data available for each one is also ex-

plained, emphasizing the fact that for the ETGs sample the optical spectra is obtained

with the long-slit technique while for the LTGs one is done with an IFU technique.

3.1 Early-type Galaxies: The Virgo Cluster Sample

In this Section a description of the main features of the observational data available

for the sample of ETGs is given. The set of data includes broad-band photometry

in the UV (GALEX), optical (HST), NIR (2MASS and CANICA/OAGH) and MIR

(SPITZER) spectral ranges, and also spectroscopic low-resolution data in the optical

(OAGH), NIR (TNG) and in the MIR (SPITZER) spectral ranges. The wide spectral

range and the quality of the data will allow to perform and compare different standard

population synthesis analysis, for instance, Lick indices(Buzzoni et al., 1992; Bres-

san et al., 1996; Annibali et al., 2007), broad-band photometric data fitting from UV

to the NIR (Mayya et al., 2004; Bianchi et al., 2005; Kaviraj et al., 2007b,a; Bridzius

et al., 2008; Rodriguez-Merino et al., 2010), evolutionary synthesis modelling and/or

full-spectrum modelling, by fitting the optical spectrum with a linear combination of

multiple SSPs (Tinsley & Danly, 1980; Cardiel et al., 2003; Cid-Fernandes et al., 2005;

Sarzi et al., 2006; Sanchez et al., 2010). The wide spectral range of the data will allow,

for the first time, the building of a set of panchromatic SEDs of ETGs which would

29

Chapter 3. Galaxy Samples and Observations

allow a good calibration of the panchromatic theoretical SSPs, to correlate the SEDs

with spectral indices, and the identification of the features of fully passively evolving

ETGs (Bressan et al., 2006). Furthermore, to have a good calibrated panchromatic

SEDs allows to check the method proposed byBressan et al.(1998, 2006) to broke the

age-metallicity degeneracy in ETGs by using the optical to MIR spectral ranges.

Notice that one of the main problems of these kind of work, from the observational

point of view, is to compare data within the same aperture. Special care was taken in our

data set, from UV to MIR, ensuring the homogeneity of the databy the use of a unique

aperture of 5 arcsec in radius, which, at the distance of the sample, corresponds to the

emission region of the central 390 parsecs. The election of this aperture was actually

imposed by the effective aperture of the SPITZER spectra, which were the starting

points for the panchromatic data set. In the following Subsections, a description for

each spectral range, the sources and the main features of thedata to be used are given.

In Chapter4.1a description of the reduction and calibration process already performed

in the data and the current status of the same ones is detailed.

3.1.1 Galaxy sample description

The galaxy sample covers 18 bright galaxies from the Virgo cluster color-magnitude

relation (Bower et al., 1992) observed in three SPITZER observing programs resulting

in a data set of low-resolution spectra from the IRS instrument:

• Cycle 1: Breaking the age metallicity degeneracy in local early-type galaxies:

clues about formation and evolution of spheroids, P.I. A. Bressan.

• Cycle 2:The evolution of early-type galaxies in nearby clusters: breaking the age

metallicity degeneracy with Spitzer IRS Blue Peak-up imaging, P.I. A. Bressan.

• Cycle 3: Tracing the eventful life of field early-type galaxies with the silicate

emission feature of evolved stars, P.I. R. Rampazzo.

A sample of 65 ETG galaxies, predominantly at low-density environments, have

been already studied by Rampazzo and collaborators (Rampazzo et al., 2005; Annibali

et al., 2006, 2007; Panuzzo et al., 2010). They used Lick/IDS indices to determine the

30

3.1. Early-type Galaxies: The Virgo Cluster Sample

age, metallicity and [α/Fe] of the stellar population, and also to study if there are gra-

dients. They found a wide spread in the age distribution, from a few Gyr to 15 Gyr.

They also analyzed possible correlations between age, metallicity and α−enrichment

with the central velocity dispersion and the local galaxy density. In the case of the cen-

tral velocity dispersion, they found that the chemical enrichment is more efficient and

that the star formation process is shorter in more massive galaxies. They also conclude

that very young objects are found in low-density environments while at high-density

environments the ages are never younger than 5 Gyr. They did not find environmental

effects for theα−enrichment. In single galaxies, the central regions are more metallic

than the outer ones. I will use the same method for the analysis of our galaxy sample,

more detailed explanation is given in Section??. The details of the SPITZER observa-

tions and the reduction process are presented later in this Chapter (Section3.1.2). The

main properties of these galaxies are sumarized in Table3.1, where Col. (1) gives the

galaxy name under the New General Catalogue (NGC), Cols. (2)and (3) list the equa-

torial coordinates from NED1 , Col. (4) provides the V magnitudes taken from NED,

while Col. (5) provides the morphological and spectral classification of the galaxy,

when available, from NED. Finally, Cols. (6) and (7) list theradial velocity and the

central velocity dispersions from NED and HYPERLEDA2 , respectively. In this the-

sis, I will adopt an average distance of 16.1 Mpc to all of galaxies of the Virgo Cluster

(Kelson et al., 2000).

3.1.2 Panchromatic Data

One of the aims of the project is to construct for the first timethe panchromatic SED

for these ETGs. Therefore, observations at several wavelengths are required. Most of

them were taken from the literature and databases. A brief description of the available

data divided by wavelength range is given below.

1 NASA/IPAC Extragalactic Database2 Hyperleda(2010)

31


Table 3.1: Main properties of our ETGs sample

Name RA(2000) Dec(2000) V Type z [km/s] σ[km/s]NGC4339 12h23m34.95s 06d04m54.3s12.26 E0,Sy2 1289 113.73NGC4365 12h24m28.23s 07d19m03.1s10.52 E3 1243 256.15NGC4371 12h24m55.43s 11d42m15.4s11.79 SB0 943 134.64NGC4377 12h25m12.27s 14d45m43.8s12.76 SA0 1375 144.06NGC4382 12h25m24.05s 18d11m27.9s10.01 SA0,pec 729 178.67NGC4406 12h26m11.74s 12d56m46.4s9.83 S0/E3 -244 235.01NGC4435 12h27m40.49s 13d04m44.2s11.74 SB0,Liner 801 156.68NGC4442 12h28m03.89s 09d48m13.0s11.38 SB0 532 186.73NGC4473 12h29m48.87s 13d25m45.7s11.16 E5 2244 179.25NGC4474 12h29m53.54s 14d04m07.1s12.38 S0,pec 1588 87.67NGC4486 12h30m49.42s 12d23m28.0s9.59 E0-1,Sy 1307 334.44NGC4550 12h35m30.60s 12d13m15.3s12.56 SB0,Liner 381 96.42NGC4551 12h35m37.97s 12d15m50.4s12.97 E 1172 106.75NGC4564 12h36m26.99s 11d26m21.5s12.05 E6 1142 157.4NGC4570 12h36m53.40s 07d14m47.9s11.84 S0/E7 1730 187.85NGC4621 12h42m02.32s 11d38m48.9s10.57 E5 410 225.15NGC4636 12h42m49.87s 02d41m16.0s10.43 E/S0 938 203.14NGC4660 12h44m31.98s 11d11m25.9s12.16 E5 1083 188.59

Ultraviolet data

The UV data were provided by A. Marino3 . They consist ofphotometric data in the

Far UV (FUV: 1350-1750A) and the Near UV (NUV: 1750-2800A) bands taken with

GALEX (Galaxy Evolution Explorer) telescope. This is a modified Ritchey-Chretien

telescope with a diameter of 50 cm. The aperture is 4.5 arcsecFWHM for the FUV and

6.0 arcsec FWHM for the NUV. The AB magnitudes were measured from the GALEX

intensity images within a 5arcsec-radius circular aperture.

The UV data are presented in Table3.2. The first column indicate the galaxy name,

the second and third columns are the FUV and NUV AB magnitudesthat can be con-

verted into fluxes by using the following expressions:

FUV : m(AB) = −2.5 log(

flux/1.40 × 10−15 erg s−1cm−2A−1

)

+ 18.82 (3.1)

NUV : m(AB) = −2.5 log(

flux/2.06 × 10−16 erg s−1cm−2A−1

)

+ 20.08 (3.2)

3 private communication, (2007)

32


Table 3.2: Ultraviolet AB magnitudes measured within a 5 arcsec radius circular aperture.

NGC FUV NUV4339 20.96±0.40 19.36±0.104365 18.41±0.07 18.12±0.044371 20.20±0.12 19.04±0.054377 20.39±0.37 19.08±0.124382 19.37±0.22 17.76±0.074406 - - - - - -4435 - - - - - -4442 19.33±0.09 18.41±0.044473 19.30±0.09 18.31±0.044474 21.35±0.17 19.35±0.064486 17.27±0.10 16.70±0.054550 19.43±0.09 18.57±0.044551 21.03±0.15 19.63±0.054564 18.78±0.08 18.29±0.054570 19.26±0.09 18.35±0.054621 18.44±0.08 18.00±0.044636 18.95±0.18 18.43±0.094660 19.74±0.10 18.58±0.04

Optical data

Spectroscopy datawere obtained in the observing runs of april 2005; january, february

and march 2006; february 2007; march and april 2008 at the ”Guillermo Haro” Astro-

physical Observatory (OAGH) located in Cananea, Sonora (+31o03‘ 10“ N, 110o23‘

05“ W) with the 2.12 meter Ritchey-Chretien telescope and the Boller and Chivens

spectrograph with two gratings (150 l/mm and 600 l/mm). The spectrograph was

mounted at the f/12 Cassegrain focus of the telescope. The plate scale of the spec-

trograph with a CCD TK1024 is 0.463 arcsec/pixel and 0.382 arcsec/pixel with a Ver-

sarray CCD detector (1324 x 1300 pixels) along the spatial direction. The slit length is

∼ 3 arcmin.

The observations were done with the 150 l/mm grating (∼ 7 A) covering the wave-

length range from 3800 to 7000A and a slit aperture of 2 arcsec sampling a physical

size of∼ 156 pc (assuming a mean distance to the Virgo cluster of 16.1 Mpc taken

from Kelson et al., 2000). The slit was oriented in order to match the position angle of

SPITZER-IRS observations. The observational conditions during the optical observa-

33


Table 3.3: Observational data for the acquisition of the optical spectra at OAGH.

NGC Obs Date UT exp time[s] airmass4339 22/02/06 09:01 5400 1.124365 12/04/05 05:48 2400 1.184371 30/01/06 10:48 3600 1.064377 24/02/06 09:48 5400 1.064382 29/01/06 09:17 3600 1.144406 02/04/08 07:57 5400 1.084435 01/04/08 06:56 5400 1.054442 12/04/05 06:58 3600 1.084473 29/01/06 10:29 3600 1.074474 25/02/06 09:39 5400 1.054486 10/02/07 08:57 5400 1.144550 02/04/08 06:19 5400 1.084551 25/02/06 11:43 5400 1.224564 27/02/06 09:47 5400 1.064570 27/02/06 11:31 5400 1.254621 12/04/05 08:07 3600 1.064636 13/03/08 08:52 5400 1.144660 12/04/05 09:15 3600 1.14

tions of the galaxy sample are shown on Table3.3, where the column 1 is the name of

the galaxy, column 2 the date of the observation in the formatday/month/year, column

3 is the UT of the observation, column 4 the exposure time of the observation in seconds

and column 5 the airmass of the observation. The final (reduced and calibrated) spectra

and the reduction process will be presented and explained inSection4.1. In order to

correct for aperture differences between the data, we need broad-band photometry.

The broad-band optical imageswere obtained from the HST database atMulti-

mission Archive at STScI(2009) in the available filters at WFPC1-2(F300W, F450W,

F555W, F547W, F606W, F675W, F702W and F814W) and ACS(F475W,F658N and

F850LP). The detailed process of the reduction and calibration of the images, as well as

the integrated magnitudes or fluxes within the central 5 arcsec are presented in Section

4.1. Notice that these data were needed in order to calibrate ouroptical spectra. This

process will also be explained in Section4.1.1.

34


Near-Infrared (NIR) data

NIR Spectroscopic observationswere provided by A. Bressan4 and they were ob-

tained with the 3.58m Alt-Az active optic Galileo National Telescope (TNG-INAF)

located at La Palma, Spain (+28o45‘ 28.3“ N, 17o53‘ 37.9“ W), by using the NICS

instrument and the AMICI grism, with a slit width of 2 arcsec giving low-resolution

spectra (R∼ 25) in the wavelength range from 0.8 to 2.4µm. The data reduction was

performed with the standard IRAF procedures as detailed in Section4.1.1. The NIR

spectra for some of the galaxies in the sample are shown in Fig. 3.1. Due to bad ob-

serving conditions some of the galaxies (NGC 4551, NGC 4564,NGC 4570, NGC

4636) were not observed. Currently, these spectra are not corrected for aperture effects.

That will be done in the same way as the optical data by usingNIR broad-band data,

within the central 5 arcsec. In Table3.4 the available 5 arcsec radius circular aperture

2MASS (Two Micron All Sky-Survey) magnitudes at 1.25µm (J-band), 1.65µm (H-

band) and 2.17µm (K-band) collected from IRSA are diplayed. In order to correct for

aperture differences those galaxies without 2MASS data, weare currently carrying out

a CANICA (OAGH) observational program. The 2MASS magnitudes can be converted

into fluxes using the following expressions:

J = −2.5 logF

1.594 × 10−20 erg cm−2s−1Hz−1 (3.3)

H = −2.5 logF

1.024 × 10−20 erg cm−2s−1Hz−1 (3.4)

Ks = −2.5 logF

6.667 × 10−21 erg cm−2s−1Hz−1 (3.5)

Mid-Infrared (MIR) data

As mentioned before, thespectroscopic MIR datadefined the final number of objects

of our ETGs sample and also the working aperture for the remaining observational data.

The data set consist of low-resolution SPITZER-IRS MIR spectra from 5 to 21.3µm

for all the galaxies listed in Table3.1, except for NGC 4406 because of the low S/N of

its spectrum. The spectra were observed by SPITZER in cycles1, 2 and 3 and reduced

and calibrated by A. Bressan5 , who provided them for this thesis.

4 private communication, (2010)5 private communication, (2009)

35


Figure 3.1: NIR spectra for some of the galaxies in the ETGs sample.

36

/home/anaely/Desktop/pre-PhD/tesisINAOE/figures/NGC4339NIR.eps









Figure 3.1: Cont. NIR spectra for some of the galaxies in the ETGs sample.

37








Table 3.4: 2MASS magnitudes for the ETGs in our sample.

NGC J H Kλ(A) 12500 16500 21600

NGC4339 11.289±0.004 10.588±0.004 10.336±0.006NGC4365 – – –NGC4371 10.840±0.003 10.141±0.003 9.899±0.004NGC4377 10.855±0.002 10.158±0.003 9.918±0.003NGC4382 – – –NGC4406 – – –NGC4435 10.288±0.001 9.547±0.002 9.247±0.002NGC4442 – – –NGC4473 – – –NGC4474 11.164±0.003 10.473±0.003 10.218±0.003NGC4486 – – –NGC4550 11.193±0.003 10.484±0.003 10.277±0.004NGC4551 11.463±0.003 10.772±0.004 10.519±0.005NGC4564 10.440±0.002 9.709± 0.002 9.444±0.003NGC4570 10.167± 0.002 9.447±0.002 9.190±0.002NGC4621 – – –NGC4636 – – –NGC4660 10.208±0.002 9.503±0.002 9.261±0.002

38


The observations were performed in Standard Staring mode with low-resolution

(R∼64-128) modules SL1 (7.4-14.5µm), SL2 (5-8.7µm) and LL2 (14.1-21.3µm).

These spectra were reduced and flux-calibrated with a pipeline specially developed for

ETGs, that exploits the large degree of symmetry that characterizes the light distribu-

tion of these galaxies. Finally, the extraction of the spectrum was done with a fixed

aperture of 3.6 x 18 arcsec2. The reduction procedure is fully described in Bressan

et al.(2006), here only the main features are summarized.

1. We first carried out the e−/sec to Jy conversion corrected for aperture losses

(ALCF) and slit losses (SLCF). To estimate the ALCF four calibration stars were

used (HR 2194, HR 6606, HR 7341 and HR 7891) and defined as the average

ratio of the fluxes extracted within the standard aperture and twice the standard

aperture. The SLCF is defined as the wavelength-dependent ratio between the

whole flux of a point source on the FoV and the flux selected by the slit. This

was done by simulating the PSF of the system and adopting a hatbeam transmis-

sion function of the slit.

2. Recovery of the intrinsic SED of the galaxy by the convolution of a surface

brightness profile model with a PSF taking into account the relative position an-

gles of the slits and the galaxy to obtain the received flux within the aperture. The

profile considered is a wavelength-dependent two-dimensional modified King’s

law:

I = I0

[

1 +X2

R2c

+Y 2

[Rc(a/b)]2

]−γ/2

where X and Y are the coordinates along the major and minor axes of the galaxy,

b/a is the axial ratio (from the literature),I0, Rc andγ are free parameters and

functions of the wavelength obtained by fitting the observations to the simulated

profile.

3. We estimated the S/N by considering two sources of noise: instrumental and

background noise (measuring the variance of pixel values inbackground-substracted

images) and a Poissonian noise of the source (estimated as the square root of the

ratio between the variance of the number of e− extracted per pixel in each expo-

sure and the number of the exposures).

39


Following Bressan et al.(2006) the ETGs are classified in two groups depending on

the different ”degree” ofactivity seen in their MIR spectra. They claim that a proper

definition ofpassiveETG can be only established from the analysis of the MIR spec-

tral features (see alsoPanuzzo et al., 2010). These authors define as passively evolving

ETG those whose MIR spectra do not show any emission lines or PAH emission fea-

tures, whileactiveETG refers to objects that show at least, one of the features.The

main characteristic of a passive MIR spectrum is the presence of the broad emission

feature around∼ 10µm that is attributed to silicate emission arising from the dusty

circumstellar envelopes of Oxygen rich AGB stars (Athey et al., 2002; Molster et al.,

2002; Sloan et al., 1998; Bressan et al., 1998) superimposed on the photospheric stellar

continuum from red giant stars. Passive ETGs of our sample are showed in Fig.3.2

while the 4 objects presenting emission lines and/or PAH emission features are showed

in Fig. 3.3.

Broad-band MIR data are also available at MIPS (24, 70 and 160µm) and IRAC

(3.6, 4.5, 5.8 and 8.0µm) in the central 5 arcsec provided by A. Bressan6 .

3.2 Late-type Galaxies: The PINGS Sample

PINGS is the acronym forPPAK IFS Nearby Galaxies Survey, P.I. F.F. Rosales-Ortega

(Rosales-Ortega et al., 2010). This project is a two-dimensional spectroscopic mo-

saicking that obtains a continuous spectral coverage of the17 nearby disk galaxy sam-

ple. More than 50 000 individual optical spectra and a total observed area of almost

80 arcmin2 represents the final data set of this project. Because of the 2-dimensional

nature of the project it was designed to study the distribution of the chemical properties

of the gas in the galaxies, and the spatially resolved variations of the stellar continuum

across the surface area of the sample.

The PINGS project uses observations from the Potsdam Multi Aperture Spectro-

graph (PMAS,Roth et al., 2005) mounted at the Cassegrain focal station of the 3.5 m

telescope located at the German-Hispanic Astronomical Centre at Calar Alto (CAHA),

Spain. The PMAS instrument is an integral field spectrophotometer covering the optical

range between 0.35-1 microns operating under a lens array-fiber bundle principle with


40

3.2. Late-type Galaxies: The PINGS Sample

Figure 3.2: MIR spectra of the passively evolving ETGs of thesample.41

/home/anaely/Desktop/pre-PhD/tesisINAOE/figures/4339IR.eps









Figure 3.2: Cont. MIR spectra of the passively evolving ETGsof the sample.

42







Figure 3.3: SPITZER/IRS spectra of the ETGs of the sample showing activity.

43






3 reflective gratings (1200, 600, 300 grooves mm−1 corresponding to approximately

1.5, 3.2, and 8A resolution in first order) and 3 magnifications (8 x 8 arcsec2, 12 x 12

arcsec2, or 16 x 16 arcsec2) . This was developed and constructed at the Astrophysical

Institute Potsdam (AIP).

The PMAS fiber PAcK (PPAK, Verheijen et al., 2004; Kelz & Roth, 2006; Kelz

et al., 2006) is a retrofitted bare fiber bundle which increases the PMAS FOV to 65 x

74 arcsec2 with a central hexagonal bundle of 331 optical fibers that sample 2.7 arcsec

per fibr. The central hexagon is surrounded by six ”mini-IFUs” with 36 active fibers

recording the sky background. Another 15 fibers can be illuminated directly by internal

lamps for instrument calibration.

3.2.1 Galaxy sample description

The PINGS project was specially designed to obtain completemaps of the emission-

line abundances, stellar populations and reddening using an IFS mosaicking imaging.

The data can be used to derive:

1. Oxygen abundance distributions using strong-line diagnostics and absorption-

corrected line ratios (Hα, Hβ, [OII], [OIII], [NII], [SII])

2. Local nebular reddening estimates based on the Balmer decrement

3. Ionization structure in HII regions and diffuse ionized gas using forbbiden-line

diagnostics of Oxygen and Nitrogen

4. Maps of the star formaton history of the galaxy from the analysis of the underly-

ing continuum.

The galaxy sample was selected in order to achieve the scientific goals mentioned

above and taking into consideration other factors such as:

• FOV of the PPAK unit (In order to maximise the physical linearresolution achieved

by the mosaicking technique only nearby galaxies were observed at a maximum

distance of 100 Mpc).

• Observational constraints (observing time and meteorological conditions, right

ascension and declination optimized for the Calar Alto observatory localization)

44


• Galaxy properties such asinclination (face-on),surface brightness(high),bar

structure, spiral arm structure and environment (isolated, interacting and

clustered).

The galaxy sample is composed mainly of normal symmetric face-on nearby spiral

galaxies, but includes also some lopsided, interacting andbarred spiral galaxies. The

17 sampled galaxies comprise a maximum distance of 100 Mpc and an average dis-

tance of 38 Mpc (H0=73 kms−1Mpc−1) and a good fraction of them belongs to the

Spitzer Infrared Nearby Galaxies Survey (SINGS,Kennicutt Jr. et al., 2003) ensur-

ing the availability of ancillary data. The target observation priority accounts for the

size of the object, the number of PPAK adjacent pointings to complete the mosaic

and the scientific relevance of the galaxy. Therefore, the first priority were the bright,

face-on and medium sized galaxies NGC1058, NGC1637, NGC3310, NGC4625, and

NGC5474 of different morphological type with considerableamount of ancillary data

(like broad-band images in the UV, optical, infrared, HI andradio wavelengths) that

could be covered with few pointings.

The complete PINGS galaxy sample is reported in Table3.5 with their basic data,

column 1 refers to the NGC name of the galaxy, column 2 and 3 their equatorial coor-

dinates, column 4 their magnitude MB (de Vaucouleurs et al., 1991), their galaxy type

from de Vaucouleurs et al.(1991) is shown in column 5, the redshift of each galaxy

is displayed in column 6 and in column 7 their heliocentric radial velocities, column

8 gives the angular projected size at B25 mag arcsec−2. Finally, column 9 lists the

distance to the galaxy. These data were taken fromRosales-Ortega et al.(2010).

The galaxy sample was observed using the 3.5m telescope at Calar Alto Observatory

with the PMAS in PPAK mode with the V300 grating that covers the wavelength range

3700-7100A with a resolution of∼ 8 A FWHM at λ = 5500A(∼ 600 kms−1).

The aperture of each fiber (2.7 arcsec) covers a physical scale greater than 100 pc (in

diameter). A dithering method was used for objects with small angular size and larger

distances. The dithering observations were performed in the following way, a first

exposure was recorded and then two consecutive exposures with a small offset from

the first exposure of∆(RA, Dec)=(1.56, 0.78) and (1.56, -0.78) arcsec. This method

covers all the gaps of the original exposure and the object isspectroscopically sampled.

45

Ch

apter

3.

Galaxy

Sam

ples

and

Ob

servation

s

Table 3.5: Basic data of the PINGS galaxy sample

NameRA Decl MB Type z v Size D

[km/s] [arcmin] [Mpc]NGC628 01h36m41.8s 15d47m00.1s-19.9 SA(s)c 0.00219 657 10.5× 9.5 9.3NGC1058 02h43m30.0s 37d20m28.5s-18.3 SA(rs)c 0.00173 519 3.0× 2.8 10.6NGC1637 04h41m28.2s -02d51m28.9s-18.9 SAB(rs)c 0.00239 717 4.0× 3.2 12.0NGC2976 09h47m15.4s 67d54m59.0s-16.9 SAc pec 0.00008 24 5.9× 2.7 3.6NGC3184 10h18m17.0s 41d25m27.8s-19.9 SAB(rs)cd 0.00194 582 7.4× 6.9 11.1NGC3310 10h38m45.9s 53d10m12.2s-20.1 SAB(r)bc 0.00331 993 3.1× 2.4 17.5NGC4625 12h41m52.7s 41d16m26.3s-16.9 SAB(rs)m 0.00203 609 2.2× 1.9 9.0NGC5474 14h05m01.6s 53d39m44.0s-17.9 SA(s)cd 0.00098 294 4.8× 4.3 6.8NGC6643 18h19m46.4s 74d34m06.1s-19.8 SA(rs)c 0.00495 1485 3.8× 1.9 20.1NGC6701 18h43m12.5s 60d39m12.0s-20.8 SB(s)a 0.01323 3969 1.5× 1.3 57.2NGC7770 23h51m22.5s 20d05m47.5s-19.4 S0 0.01414 4242 0.8× 0.7 58.7NGC7771 23h51m24.9s 20d06m42.6s-20.8 SB(s)a 0.01445 4335 2.5× 1.0 60.8NGC7317 22h35m51.9s 33d56m41.6s-20.3 E4 0.02201 6603 1.1× 1.0 93.3

NGC7318A 22h35m56.7s 33d57m55.7s-20.5 E2 pec 0.02211 6633 0.9× 0.9 93.7NGC7318B 22h35m58.4s 33d57m57.3s-20.6 SB(s)bc pec 0.01926 5778 1.9× 1.2 82.0NGC7319 22h36m03.6s 33d58m32.6s-20.8 SB(s)bc pec 0.02251 6753 1.7× 1.3 95.4NGC7320 22h36m03.4s 33d56m53.2s-17.5 SA(s)d 0.00262 786 2.2× 1.1 13.7

46


For the purposes of this thesis I will use reduced IFS data from the PINGS project

(Rosales-Ortega et al., 2010). I here provide only a brief description of the reduc-

tion process. They used a combination of existing software packages for fiber IFS

data reduction process: R3D, E3D, IRAF and custom-built codes to generate a general

pipeline and visualization software known as PINGSoft (Rosales-Ortega, 2010).

1. Pre-reduction: CCD corrections (bias substraction, flat-fielding, combination of

the same pointing and cosmic ray elimination)

2. Identification of the location of the spectrum in the detector: The raw data con-

sists of a collection of spectra along the dispersion axis, following a nearly Gaus-

sian profile, but generally are not perfectly aligned due to the instrument configu-

ration, optical distortions and mechanical flexures makingnecessary the location

of each spectrum at each wavelength along the CCD. This is done identifying the

peaks along the dispersion direction, this is known as the trace.

3. Extraction of each individual spectrum: Performed by co-adding the flux within

an aperture around the trace. For the PMAS/PPAK data an adaptive iterative

method was performed in which an aperture of around 5 pixels is usually used.

4. Distortion correction: Additional to the fact that the grating spectrographs distort

the dispersed light, the dispersion may be distorted due to the placing of the

fibers in the pseudo-slit. A fiber-to-fiber distortion correction was done using

HeHgCd+ThAr arc lamp exposures of each observed position with the calibration

fibers. The peak intensity of a single emission line is tracedalong the cross-

dispersion axis and linearly shifted to a reference.

5. Determination of the wavelength solution: Identification of emission lines in the

arc lamps used before and applying a polynomial transformation. For the PINGS

instrumental set-up a good solution (rms∼0.2 A) was reached with 6 emission

lines and an order 4 polynomial function.

6. Fiber-to-fiber transmission correction: An exposure of acontinuum and well-

illuminated skyflat is used to correct for transimission differences. A median

spectrum from all the spectra in a frame is obtained, and eachspectrum then is

divided by the median one.

47


7. Sky substraction: Elimination of the Earth’s atmosphereemission using the sky

fibers when possible (if they are not sampling the galaxy or foreground objects)

or supplementary sky exposures when needed.

8. Flux calibration: Spectrophotometric standard stars were observed for this pur-

pose. Since all the flux of the star do not fall in only one fiber,the observed

spectrum was obtained by adding the spectra from consecutive concentric spax-

els until a convergence limit was found.

9. Allocation of the spectrum to the sky position: The construction of the mosaic

was iterative begining with a master pointing (the one with the best observing

conditions, sky substraction, flux calibration and signal-to-noise) used as a refer-

ence and then adding consecutive pointing following the mosaic pattern.

10. Absolute flux re-calibration: Only for those galaxies (NGC 628, NGC 2976,

NGC 3184, NGC 4625 and NGC 5474) with multi-band photometry data avail-

able (Broad band: B, V, R and narrow band; Hα)

The final dataset of the 17 galaxies observed in the PINGS program comprises more

than 50 000 flux calibrated spectra. I will take advantage of the IFS technique used to

obtain these spectra to study the spatially resolved properties of the underlying stellar

population of the LTGs sample.

A spatial distribution of the stellar population and the gascomponent has already

been performed for the largest galaxy of the sample (NGC 628)by Sanchez et al.(2010)

and this will allow me to use it as a basis for the analysis to beperformed to the galaxies

of the rest of the sample.

3.2.2 Illustrative Selected Galaxies: NGC 1058 and NGC 1637

For a first approach to a complete population synthesis analysis only two galaxies of

the sample were selected: NGC 1058 and NGC 1637. These galaxies were selected

because they are the largest galaxies in the sample (note that NGC 628 has been al-

ready studied bySanchez et al., 2010) and the mosaic of each galaxy is complete. In

this context, complete means that it covers all the optical size of the galaxy defined by

the B-band 25 mag isophote. Given their relatively large angular size and good surface

48


coverage they can provide a spatially resolved stellar population study. In the case of

NGC 628, Sanchez et al.(2010) found an age gradient of the stellar populations be-

ing the central regions older than the outer ones. But they found an inversion of the

gradient at the centre of the galaxy (∼ 1 kpc). In the case of the stellar metallicity

it showed a weaker gradient, being the central regions slightly richer than the outer

ones. The oxygen abundance of the ionized gas follows nearlythe same distribution.

From their analysis of the ionized gas, they found that the ionization is stronger along

the spiral arms and more intense in the outer regions. An average oxygen abundance of

12+log (O/H) ∼ 8.7 and a moderate SFR∼ 2.4 M⊙ yr−1 were found by them. In gen-

eral, their results are consistent with an inside-out growth scheme. Their observations

are not affected by loss of spatial resolution due to gaps of the instrument, achieved

with the dithering mode during the observations. Good signal-to-noise is another rea-

son why these galaxies were chosen. Previous analysis of thenebular emission has been

performed byRosales-Ortega(2009) and this allows for comparisons with the synthe-

sis populations results. Also because they have ancillary data available and present

interesting features as explained below.

NGC 1058

This is a Seyfert 2 Sc galaxy in the Perseus constellation with a projected size of 3.0 x

2.8 arcmin at a distance of 10.6 Mpc. It was observed in three consecutive nights (7-

9 Dec 2007). The mosaic construction was a central position and one concentric ring,

covering most of the galaxy surface within one optical radius (B-band 25 mag isophote).

A representation of the mosaic overplotted to an optical image (B-band) from the Sloan

Digital Sky Survey (SDSS) is shown in Fig.3.4(a). The additional pointings 6 and 9

were performed to observe two HII regions. The final mosaic comprises a total of 7944

final individual spectra, covering an area of∼ 8.5 arcmin2. The aperture of one fibers

corresponds to a physical scale of 138.3 pc. In Fig.3.4(b)I show a visualisation of the

spaxels covering the galaxy.Rosales-Ortega(2009) performed an analysis of the gas

phase, by means of the integrated emission-line spectrum, deriving a dust extinction of

AV = 0.64, a gas metallicity oflog R23 = 0.53, a SFR(Hα) = 0.5 M⊙ yr−1, from the

L(Hα) = 0.65 × 1041 erg s−1 and SFR([OII]) = 0.9 M⊙yr−1 from the L([OII]) =

0.61 × 1041 erg s−1.

49


(a) PPAK pointings for NGC 1058 overplotted on the broadB-band SDSS image

(b) The small circles correspond to the size of individual fibers.

Figure 3.4: NGC 1058 image constructed from each of the PPAK pointings.

50

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An interesting object observed was a recently discovered supernova by the Lick

Observatory Supernova Search on august 15, 2007. SN2007gr is a type Ic supernova

(lack of hydrogen, helium and silicon absorption lines, emission lines [OII]3727, Hα,

[NII]6548, 6584 and [SII]6717, 6731) located at 24.8 arcsecwest and 15.8 arcsec north

of the galaxy’s nucleus (Chornock et al., 2007).

NGC 1637

This is a SAB distorted galaxy in Eridanus with a projected size of 4.0 x 3.2 arcmin. A

third well-defined arm is seen in optical images, HI, CO, NIR and 20 cm radio contin-

uum maps (Roberts et al., 2001). The galaxy was observed on 8-10 dec 2007. The mo-

saic was constructed with a central position and one concentric ring with 6 pointings.

The mosaic for the galaxy is shown in Fig.3.5(a)with 6951 final individual spectra

covering an area of∼ 7 arcmin2. The aperture of one fiber correspond to a physical

scale of 156.3 pc. A visualisation of the spaxel coverage of the galaxy is shown in Fig.

3.5(a). Interesting features beside the third arm are an HI envelope, an optical centre

that differs from the kinematic one by 9 arcsec and a HI enhancement in regions with-

out prominent optical features. For this galaxy of the PINGSsample,Rosales-Ortega

(2009) performed an analysis of the gas phase, by means of the integrated emission-

line spectrum. They derived a dust extinction ofAV = 1.09, a gas metallicity of

log R23 = 0.41, a SFR(Hα) = 0.9 M⊙yr−1 from the L(Hα) = 1.09×1041 erg s−1 and

SFR([OII]) = 1.2 M⊙yr−1 from the L([OII]) = 0.84 × 1041 erg s−1.

51


(a) The small circles correspond to the size of individual fibers.

(b) PPAK pointings for NGC 1637 overplotted on the broadB-band DSS image

Figure 3.5: NGC 1637 image constructed from each of the PPAK pointings.

52

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Chapter 4

Preliminary Results and Future Work

In this Chapter, I present some preliminary results based onthe work already done on

the ETGs sample. At the end of the Chapter I will describe the work proposed to be

done in the PhD thesis.

4.1 ETGs sample

4.1.1 ETGs data reduction

Long-slit spectroscopy

The main reason to start the analysis with the ETGs sample is that they are apparently

simplier than LTGs, due to their almost passive evolution and their lack of gas and dust.

As part of the work already done is the reduction and calibration of the optical spectra

for the Virgo cluster sample. The reduction for the ETGs galaxy sample was done

with the standard procedures for long-slit spectroscopy inthe IRAF package (Image

Reduction and Analysis Facility). An overview of this process is:

1. Corrections due to the detector: BIAS (detector pedestalnoise) and FLAT (ilu-

mination differences).

Imagefinal =Image − BIAS

FLAT − BIAS(4.1)

2. Combination of the images with the same instrumental setup of the same object

and cosmic rays elimination.

53

Chapter 4. Preliminary Results and Future Work

3. 2D Wavelength calibration using the He-Ar lamp as reference.

4. Sky emission correction.

5. 2D flux calibration using spectrophotometric standard stars and the flux library

available with IRAF applying for the atmospheric extinction correction the Kitt

Peak curve.

6. 1D spectrum extraction of the galaxy sample and the Lick Standard Stars (LSS).

In Table4.1the aperture for the 1D spectrum extraction for each galaxy in the sample

is shown. The resulting spectrum was the one used in order to measure the Lick/IDS

indices, as detailed in Section4.1.2.

Table 4.1: Optical aperture for the extraction of the 1D spectra of the ETGs sample.

NGC seeing[arcsec] PA(SL) PA(LL) ∆Pixel ∆[arcsec]4339 1.70 23.5460 -59.9700 60 27.064365 2.02 17.5700 114.0500 60 27.064371 1.69 27.4764 -56.0400 110 49.614377 1.68 29.0440 -54.4800 40 18.044382 1.69 17.8512 -65.6700 130 58.634406 1.13 28.2400 -55.2800 150 57.34435 1.12 28.5200 -54.9900 140 53.484442 2.02 17.3100 113.7900 110 49.614473 1.69 29.0338 -54.4900 110 49.614474 1.68 29.3260 -54.2000 40 18.044486 1.45 28.0196 -55.5000 200 76.44550 1.13 28.5300 -54.9800 130 49.664551 1.68 28.5308 -54.9900 60 27.064564 1.66 27.0568 -56.4600 50 22.554570 1.66 25.3888 -58.1300 60 27.064621 2.02 17.2300 113.7100 50 22.554636 1.11 18.8500 -64.6600 150 57.34660 2.02 17.4200 113.8900 40 18.04

The calibrated optical spectra for all the galaxies in the sample are shown in Fig.

4.2, while in Fig. 4.1 some of the characteristic absorption lines present in the ETGs

spectra are labeled.

54

4.1. ETGs sample

Figure 4.1: Characteristic absorption lines present in an ETG spectrum, the symbol⊗ standsfor the telluric lines.

55

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Figure 4.2: Calibrated optical spectrum for the ETGs sample

56

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4.1. ETGs sample

Figure 4.2: Cont. Calibrated optical spectrum for the ETGs sample

57








Figure 4.2: Cont. Calibrated optical spectrum for the ETGs sample

58







4.1. ETGs sample

Optical photometric data

These measurements were done on HST images in order to recalibrate and correct the

optical spectra due to aperture differences before constructing the panchromatic SED.

For this purpose all the HST optical and calibrated images available for our galaxy

sample were obtained from the Multimission Archive at STScI(2009). The SPITZER

aperture was taken as the reference one, having an area of∼ 64 arcsec2 and since

the elliptical galaxies normally are symmetric we can use a circular aperture with an

equivalent SPITZER area:

r =

√

A

π= 4.54 arcsec.

For the available data, the plate scale of the instrument wasused to transform the equiv-

alent aperture from arcsec to pixels. These are showed in theTable4.2.

Table 4.2: Equivalent aperture radius in pixels for each instrument in the HST

instrumentplate scale equivalent aperture

mode [“/pixel] [pixels]WFPC1

WFC 0.102 45PC 0.043 105

WFPC2PC 0.0455 100

WF2,3,4 0.0966 45ACS

WFC 0.05 91HRC 0.0265 171SBC 0.032 142

The aperture photometry was done with the PHOT task in IRAF, following the next

steps:

1. Image combination for each galaxy with the same instrument and filter configu-

ration.

2. Cosmic ray elimination around the galaxy.

3. Measurement or header identification of the following parameters required for

the PHOT task:

59


(a) FWHM of the bright reference stars in each image.

(b) CCD readout noise in electrons.

(c) CCD gain in electrons/ADU.

(d) exposure time.

(e) filter.

(f) sky value.

4. Running the PHOT task with the proper parameters (aperture in pixels according

to the instrument and the ones mentioned above).

The associated error was estimated by:

error =√

F lux/epadu + Aap ∗ σ2sky + A2

ap ∗ σ2sky/Asky (4.2)

beingepadu the CCD gain in e−/ADU, σsky the standard deviation computed by the

sky fitting algorithm,Asky the area where the sky is measured,Aap the aperture area

andF lux the measured flux within the aperture area.

The fluxes and errors measured within a 5 arcsec-radius circular aperture for each

galaxy in each available filter (and their central wavelength) are shown in Table4.3.

These fluxes were the one used in order to recalibrate the optical spectra of the ETGs

sample. This was done by rescaling the optical spectra with the flux at F555W (5442A),

when this filter image was not available we used F475W (4745A) or F547W (5460A).

Then, using the rest of the available fluxes a new calibrationfunction was constructed

and applied to the optical spectra. Besides the construction of the panchromatic SED,

the resulting optical spectrum was used to measure the set of25 spectral indices detailed

in the following Subsection. A similar process will be followed in order to recalibrate

the NIR spectra from the TNG with aid of the 2MASS or CANICA photometry.

4.1.2 ETGs Analysis

Lick/IDS Indices System

A spectral index measures the intensity of an interesting spectral feature. For this pur-

pose three wavelength intervals are defined:

60

4.1. ETGs sample

Table 4.3: HST photometric data, fluxes are in10−14 erg s−1 cm−2 A−1 units andλ is thecentral wavelength of the filter used.

NGC F300W F450W F475W F555W F547Wλ(A) 2993 4557 4745 5442 5460

F606W F658N F675W F702W F814W F850LP6001 6591 6717 6917 7995 9036

4339 - - - - - - - - - - - - - - -1.512±0.079 - - - - - - - - - - - - - - -

4365 - - - - - - - - - 2.978±0.194 - - -0.0±0.0 - - - - - - 3.019±0.245 3.228±0.265 - - -

4371 - - - - - - 1.724±0.112 - - - - - -1.938±0.106 - - - - - - - - - - - - - - -

4377 0.281±0.028 - - - 1.755±0.133 - - - - - -2.327±0.118 - - - - - - - - - - - - - - -

4382 - - - - - - - - - 4.859±0.325 - - -- - - - - - - - - - - - 4.452±0.374 - - -4406 - - - - - - - - - 3.102±0.206 - - -- - - - - - - - - - - - 3.214±0.287 - - -4435 - - - 2.387±0.203 - - - - - - - - -

0.0±0.0 - - - 3.479±0.226 - - - 3.638±0.283 - - -4442 0.448±0.041 - - - 3.289±0.239 - - - - - -- - - - - - - - - - - - - - - 4.002±0.3794473 0.618±0.054 - - - - - - 3.837±0.276 - - -- - - - - - - - - - - - 5.341±0.453 - - -4474 0.331±0.033 - - - - - - 1.359±0.087 - - -- - - - - - - - - 1.528±0.114 - - - - - -4486 0.441±0.045 - - - - - - - - - 2.972±0.184

3.168±0.171 - - - - - - - - - 3.753±0.316 - - -4550 0.242±0.023 - - - - - - 1.325±0.095 - - -

0.0±0.0 - - - - - - - - - 1.492±0.128 - - -4551 0.182±0.017 - - - 0.921±0.080 1.067±0.077 - - -- - - - - - - - - - - - - - - 1.120±0.1034564 0.372±0.033 - - - - - - 2.533±0.233 - - -- - - - - - - - - 2.560±0.209 - - - - - -4570 0.352±0.032 - - - - - - 3.142±0.202 - - -- - - - - - - - - - - - 3.487±0.297 - - -4621 - - - - - - - - - 4.069±0.332 - - -- - - - - - - - - - - - 4.819±0.408 - - -4636 - - - - - - - - - 2.231±0.136 - - -- - - 2.678±0.178 - - - - - - - - - - - -4660 - - - - - - - - - 3.234±0.213 - - -- - - - - - - - - - - - 3.332±0.273 - - -

61


Figure 4.3: Graphical representation of the three wavelength bands used for the index determi-nation for Hβ. The crossing solid line represents the pseudocontinuum defined in the text.

1. Central band covering the feature of interest

2. Blue and red bands that define the pseudocontinuum

And an example of these bands and the pseudocontinuum for theHβ index are shown

in Fig. 4.3.

There are two kind of indices:

Atomic: narrow features defined as a variation of the equivalent width measured in

Angstroms (A).

Ia =

∫ λc2

λc1

(

1 − S(λ)

C(λ)

)

dλ. (4.3)

Molecular: wider features that measure molecular bands in absorption defined as a

62

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4.1. ETGs sample

Table 4.4: The 25 spectral indices definitions

central band blue band red bandmin max min max min max Units Name

01 4142.125 4177.125 4080.125 4117.625 4244.125 4284.125 mag CN1

02 4142.125 4177.125 4083.875 4096.375 4244.125 4284.125 mag CN2

03 4222.250 4234.750 4211.000 4219.750 4241.000 4251.000A Ca422704 4281.375 4316.375 4266.375 4282.625 4318.875 4335.125A G430005 4369.125 4420.375 4359.125 4370.375 4442.875 4455.375A Fe438306 4452.125 4474.625 4445.875 4454.625 4477.125 4492.125A Ca445507 4514.250 4559.250 4504.250 4514.250 4560.500 4579.250A Fe453108 4634.000 4720.250 4611.500 4630.250 4742.750 4756.500A Fe466809 4847.875 4876.625 4827.875 4847.875 4876.625 4891.625A Hβ

10 4977.750 5054.000 4946.500 4977.750 5054.000 5065.250A Fe501511 5069.125 5134.125 4895.125 4957.625 5301.125 5366.125 mag Mg1

12 5154.125 5196.625 4895.125 4957.625 5301.125 5366.125 mag Mg2

13 5160.125 5192.625 5142.625 5161.375 5191.375 5206.375A Mgb

14 5245.650 5285.650 5233.150 5248.150 5285.650 5318.150A Fe527015 5312.125 5352.125 5304.625 5315.875 5353.375 5363.375A Fe533516 5387.500 5415.000 5376.250 5387.500 5415.000 5425.000A Fe540617 5696.625 5720.375 5672.875 5696.625 5722.875 5736.625A Fe570918 5776.625 5796.625 5765.375 5775.375 5797.875 5811.625A Fe578219 5876.875 5909.375 5860.625 5875.625 5922.125 5948.125A NaD

20 5936.625 5994.125 5816.625 5849.125 6038.625 6103.625 mag TiO1

21 6189.625 6272.125 6066.625 6141.625 6372.625 6415.125 mag TiO2

22 4083.500 4122.250 4041.600 4079.750 4128.500 4161.000A HδA

23 4319.750 4363.500 4283.500 4319.750 4367.250 4419.750A HγA

24 4091.000 4112.250 4057.250 4088.500 4114.750 4137.250A HδF

25 4331.250 4352.250 4283.500 4319.750 4354.750 4384.750A HγF

63


flux ratio expressed in magnitudes.

Im = −2.5 log

∫ λc2

λc1

S(λ)/C(λ)

λc2 − λc1

dλ. (4.4)

Hereλc1 andλc2 are the central band wavelength limits inA, S(λ) is the object

spectrum andC(λ) is the linearly interpolated pseudocontinuum.

C(λ) = Sbλr − λ

λr − λb

+ Srλ − λb

λr − λb

, (4.5)

where

Sb =

∫ λb2

λb1

S(λ)dλ

λb2 − λb1

,

λb =λb1 + λb2

2,

Sr =

∫ λr2

λr1

S(λ)dλ

λr2− λr1

,

λr =λr1

+ λr2

2,

whereλb1 andλb2 are the blue band limits andλr1andλr2

are the red band limits.

In the Table4.4 I list the wavelength limits for each band (central, red and blue),

the name of the index and its units. The most up-to-date wavelength definitions for the

indices were taken fromDr. Guy Worthey, Washington State University(2007). The

Fig. 4.4 shows the optical spectra of the galaxy sample and the central bands of the

Lick/IDS indices, the number labeling each index are the same of the Table4.4.

The Lick/IDS system consists of spectra of stars, clusters and galaxies observed be-

tween 1972 and 1984 at the Lick Observatory with a Cassegrainspectrograph in the

wavelength range between 4000-6400A and∼ 8 A resolution. This observations

were not flux calibrated, and are reported at a zero velocity dispersionσ. On the other

hand, our observations were done at the OAGH Observatory with a Boller and Chivens

spectrograph in the wavelength range between 3800-7000A and a∼ 7 A resolu-

tion and are flux calibrated. In order to compare both systemswe must convert our

observational (instrumental) indices to the Lick/IDS system. The first step to achieve

an accurate transformation between the systems is the observation of a sample of Lick

Standard Stars (LSS). Then the transformation can be done following the next steps:

64

4.1. ETGs sample

Figure 4.4: Central bands of the Lick/IDS indices overplotted to the optical spectra of the ETGssample.

1. Our observations must have the same resolution as the Lick/IDS system.

2. Velocity dispersionσ correction.

3. Linear correlation and transformation coefficients

The LSS sample and the transformation steps are described inmore detail in the

following Subsections.

Lick Standard Stars Sample (LSS)

In order to compare our spectral indices to previous resultswe must convert our in-

strumental indices to the Lick/IDS system. This transformation was done following

the suggestions given byDr. Guy Worthey, Washington State University(2007). To

65

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standarize our instrumental system 35 Lick Standard Stars (LSS) were observed in two

observing runs: october 2004 and april 2006, with the same spectrograph configuration

used to observe the ETGs sample. Due to the nature of the ETGs sample, the LSS sam-

ple correspond to the spectral classes F, G and K. The basic data of the LSS sample is

shown on Table4.5, where column 1 is the star name under the Henry Draper (HD) cat-

alogue, columns 2 and 3 are their celestial coordinates, column 4 their visual apparent

magnitude, column 5 is their radial velocity and the last column is their spectral class

according to Harvard classification. The reduction processfor the LSS spectra was the

standard for long-slit spectroscopy detailed in Section4.1.1.

Lick/IDS system resolution

The Lick/IDS system has a variable resolution, in Table4.6this resolution is given as a

function of wavelength (Worthey & Ottaviani, 1997).

Then using the IDL routine BROADENIRREGULAR created by E. Bertone1 our

optical spectra was broadened according to the data on Table4.6. The routine uses a

Gaussian kernel because the instrument dispersion can be described with a Gaussian.

g(x) =1√2πσ

exp

(

(x − µ)2

2σ2

)

. (4.6)

In our caseµ runs in wavelength and

σ =

√

FWHM2Lick − FWHM2

Cananea

2.354820045. (4.7)

This routine was applied to all our observations (galaxy sample and LSS) and after this

we got our observations in the Lick/IDS resolution. The 25 spectral indices defined

in Table4.4 are measured in these new spectrum. In Table4.7 these instrumental in-

dices are shown for each galaxy in the Virgo cluster sample. It is important to remind

that these indices are not in the Lick/IDS system yet and alsothe velocity dispersion

correction was not applied, this is work in progress.

Velocity dispersion correction

This correction is necessary because the stellar components of the galaxy are moving

with different velocities affecting the integrated spectra. This effect is seen as a broad-

1 private communication (2007)

66

4.1. ETGs sample

Table 4.5: Basic Data of the Lick Standard Stars sample

name RA [hms] DEC [dms] V v [km/s] Spectral typeHD 004656 00 46 05.113 +07 18 47.934.43 32.3 K5 IIIHD 006203 01 00 30.792 -05 06 12.945.43 15.3 K0 III-IVHD 010380 01 38 49.559 +05 14 07.134.44 0.4 K3 IIIb Ba0.1HD 012929 02 04 20.917 +23 13 37.072.00 -14.2 K2 IIIa,b Ca-1HD 017709 02 48 25.535 +34 51 19.204.53 14.3 K7 IIIHD 019476 03 06 06.756 +44 40 10.213.80 29.2 K0 IIIHD 020893 03 19 52.271 +20 33 52.255.09 2.3 K3 IIIHD 101501 11 38 25.282 +34 29 02.885.33 -5.4 G8 VHD 102328 11 44 15.620 +55 54 22.945.27 1.7 K3 IIIHD 102870 11 48 05.387 +02 02 47.613.61 4.6 F9 VHD 140573 15 41 48.151 +06 34 53.932.65 2.9 K2 IIIb CN1Fe4143-1HD 141144 15 44 54.60 +01 41 59.5 6.55 — K0IIIHD 142091 15 49 20.761 +35 48 41.154.82 -24.0 K1 IVaHD 142373 15 50 56.688 +42 35 25.794.62 -55.4 F8 VFe-2Hd-1HD 142860 15 54 08.453 +15 49 24.773.85 6.7 F6 VHD 165760 18 04 54.790 +08 43 33.794.64 -3.2 G8 IIIHD 167042 18 09 30.065 +54 16 15.735.95 -15.8 K1 IIIHD 168775 18 18 06.453 +36 02 27.364.33 -22.3 K2 IIIab CN1HD 172401 18 37 16.039 +08 41 11.196.99 — K0 IIIHD 175743 18 53 53.709 +18 02 29.035.69 44 K1 IIIHD 184406 19 31 38.752 +07 16 16.894.45 -23.9 K3 IIIbHD 199580 20 54 57.777 +42 41 57.15 7.9 -19.4 K1 IVHD 201626 21 07 48.319 +26 24 38.03 8.0 -145.7 K2HD 210027 22 04 40.836 +25 06 00.713.76 -4.3 F5 VHD 216385 22 49 51.922 +09 34 08.985.16 11.6 F7 IVHD 218527 23 06 07.193 +01 51 18.975.40 -17.8 G8 III-IVHD 219134 23 10 51.875 +56 53 31.355.56 -17.8 K3 VHD 222368 23 37 22.603 +05 21 18.604.13 5.0 F7 VHD 224930 23 59 33.187 +26 49 02.925.75 -36.2 G2 VHD 88230 10 08 19.102 +49 42 29.176.59 -26.1 K2 VeHD 88284 10 08 08.945 -12 06 22.553.61 19.4 K0 III CN1HD 90508 10 24 59.304 +49 03 09.216.44 -6.6 F9 VHD 95272 10 57 20.138 -18 01 55.624.08 46.8 K0 IIIHD 97907 11 13 15.007 +13 34 50.275.32 18.1 K3 IIIHD 98230 11 15 31.26 +31 48 39.7 4.87 -15.9 G0 V + G0 V

67


Table 4.6: Lick/IDS FWHM

wavelength [A] FWHM [ A]

4000 11.54400 9.24900 8.45400 8.46000 9.8

ening of the spectral lines. In order to compare our instrumental spectral indices with

the Lick/IDS system we have to report our obervations toσ = 0. The broadening

of the spectral lines due to the velocity dispersion can be represented by a Gaussian

with σ = σgalaxy. The central velocity dispersion and their associated estimated error

for each galaxy in the Virgo cluster sample are shown in Table4.8. These values were

taken fromHyperleda(2010). Each stellar spectrum (LSS) was convolved with a Gaus-

sian withσ running from 0 to 500 km/s at 10 km/s steps. For each of this newspectrum

the 25 spectral indices set was measured. By plotting the stellar spectral indices at dif-

ferent velocity dispersion we can select the closer value ofthe index measured for a

LSS to the one measured for each galaxy in the sample. Then, aninterpolation is done

from the index value for the galaxy atσgalaxy to σ = 0. This interpolation is not yet

applied to the indices shown in Table4.7.

Transformation coefficients

To finally transform our observational indices to the Lick/IDS system (previously cor-

rected for velocity dispersion effects) we must obtain the transformation coefficients.

This can be done by plotting the instrumental indices at Lick/IDS resolution against

the reported indices by Worthey2 for the Lick Standard Stars. This plot shows a lin-

ear correlation from which the transformation coefficientscan be derived by minimiz-

ing the least absolute deviation method. If we have the data points: (xi, yi) where

i = 1, 2, . . . , n were are looking for a functionf(xi) ≈ yi. In our case this functionf

must be linearf(x) = bx + a with a andb that minimizes:

S =

n∑

i=1

|yi − f(xi)| (4.8)

2 http://astro.wsu.edu/ftp/WO97/export.dat

68

4.1. ETGs sample

The advantage of using this method resides in the fact that isinsensitive to outliers.

The linear correlation for each index are presented in the Fig. 4.5 and the values of

the transformation coefficients are presented in Table4.9, where the Column 1 lists the

identification number for each index, Column 2 and 3 are the A and B coefficients and

Column 4 lists the absolute deviation as shown in Eq.4.8. The A and B coefficients are

applied to the spectral indices corrected for velocity dispersion and after this we have

them in the Lick/IDS system.

Error Estimation

For estimating the associated error of the spectral indiceswe used a Monte Carlo Tech-

nique. From the original spectrum the standard deviation ismeasured for bins of 7A in

function of the monochromatic fluxFλ

σλ =√

< F 2λ > − < Fλ >2

A random number between±σλ is added to the original spectrum, creating a new

set of 200 spectra. To each one of this new spectra the 25 spectral indices were mea-

sured. For each spectral index an histogram was constructedand assuming a Gaussian

distribution its standard deviation was defined as the error. We must include the error

associated to the transformation between the instrumentaland Lick/IDS systems that is

a constant for each index.

Then the combination of some Lick/IDS indices with a stellarpopulation model will

provide stellar population ages, metallicities and relative abundances. Also future work

will be done in order to study the gradients (seen as the spatial variation) of the stellar

population. This will be done following the procedure givenby Rampazzo et al.(2005)

where the set of 25 spectral indices where measured at different galactocentric distances

by means of concentric apertures along the slit.

Panchromatic SED Construction

The data presented in the Section3.1.2were used to construct the panchromatic SED

of each galaxy of the Virgo cluster sample with observed spectra and reported photom-

etry. These SED are presented in the Fig.4.6. In each plot the black thick solid lines

69

Ch

apter

4.

Prelim

inary

Resu

ltsan

dF

utu

reW

ork

Figure 4.5: Correlation plots for each one of the 25 Lick/IDSindices. The solid line indicates the linear correlation for each index.

70

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4.2. Future Work

are the observed spectra: optical (OAGH) and infrared (TNG and SPITZER), and the

triangles are photometric points from GALEX, HST and 2MASS.Only for comparison

I overplotted an old metal rich (10 Gyr, Z=0.02) simple stellar population model (green

thin line) provided by A. Bressan3 As a result of these plots it is evident (specially at

UV or IR wavelengths) that a unique SSP is not a good assumption for all the ETGs,

making necessary a reconsideration of this assumption by the construction of the SEDs

by combining several SSPs.

The work already done for the ETGs sample provide us of the reduced and calibrated

optical spectra, for which the spectral indices in the Lick/IDS system were measured

in order to characterize the stellar populations. In order to construct the panchromatic

SED for these galaxies the optical spectrum has been corrected for aperture differ-

ences by means of broad-band photometry. The correction forthe NIR wavelength is

not finished because broad-band observations were not available for all the galaxies in

the sample. In order to achieve it, observational runs are inprogress at OAGH with

CANICA.

4.2 Future Work

Only preliminary results are available for the ETGs sample,but by the end of the work

of this thesis the following results will be provided:

Virgo Sample (ETGs): Some of the results expected for this sample are

1. Fully calibrated panchromatic SED for the ETGs sample of the Virgo clus-

ter.

2. Spectral indices in the Lick/IDS for all the galaxies in the sample for differ-

ent apertures in order to determine gradients following theprocedure given

by Rampazzo et al.(2005).

PINGS Sample (LTGs): Some of the results expected for this sample are

1. Spatially resolved stellar population synthesis study for the selected galax-

ies of the sample (NGC 1058 and NGC 1637) that will be extendedto the


71


Figure 4.6: Panchromatic SED of the ETGs in the Virgo Clustersample. The black solidlines are the optical (OAGH) and infrared (TNG and SPITZER) spectra, the triangles are thephotometric points from GALEX, HST and 2MASS. The green lineis a SSP with an age of 10Gyr and solar metallicity Z=0.02.

72

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4.2. Future Work

Figure 4.6: Cont. Panchromatic SED of the ETGs in the Virgo Cluster sample

73








Figure 4.6: Cont. Panchromatic SED of the ETGs in the Virgo Cluster sample

74






4.2. Future Work

remaining galaxies of the sample.

2. Construction of the 2-D map of the Star Formation History for the selected

galaxies.

A panchromatic study of the same sample will be started with NIR photometry

(JHK) using CANICA/OAGH in order to study the older population and to trace extinc-

tion maps. From the detailed analysis of the stellar populations we expect to provide

hints on the formation process and evolution of the galaxiesin the samples.

A schematic and adaptable working plan to be followed for theaccomplishment of

the stellar populations analysis along the Hubble sequenceis shown in Table4.10. The

working plan is divided by semesters and by galaxy sample. A report of the advances

will be presented for each semester.

75

Ch

apter

4.

Prelim

inary

Resu

ltsan

dF

utu

reW

ork

Table 4.7: Instrumental indices for the galaxies in the Virgo cluster sample.

NGC CN1 CN2 Ca4227 G4300 Fe4383 Ca4455 Fe4531 Fe4668 Hβ Fe5015 Mg1 Mg2

4339 0.0616 0.0910 1.1548 5.0351 4.8174 0.5909 3.4751 5.4475 2.0387 4.5509 0.1256 0.27354365 0.1217 0.1388 0.4496 4.3920 2.0241 0.4059 1.0744 3.2232 1.5195 3.1906 0.1085 0.25654371 0.0719 0.0877 0.7097 5.4546 3.5585 -0.0049 2.5625 5.9011 2.0833 6.1992 0.1109 0.25814377 0.0411 0.0594 0.9539 5.1135 4.6910 1.1122 2.9563 5.2669 1.6326 4.5207 0.1002 0.21764382 0.0376 0.0623 0.6449 4.4923 1.7218 0.6923 2.1225 5.4979 2.0451 4.7919 0.0643 0.19134406 0.1125 0.1397 0.9155 5.7460 4.5559 0.7837 3.1437 7.1469 1.6295 4.5975 0.1361 0.30554435 0.0190 0.0383 0.6811 4.2245 3.4532 0.4758 2.8667 5.1003 1.9227 5.0036 0.0963 0.23434442 0.0791 0.0893 0.3221 4.0622 3.3574 0.5597 1.5219 3.7569 1.0630 3.5136 0.1226 0.26584473 0.0515 0.0771 0.6820 5.0849 4.5839 0.6784 2.7070 6.3163 1.7174 4.7872 0.0908 0.23264474 0.0348 0.0536 0.9597 4.4529 3.7641 0.4530 2.9157 5.6054 1.9311 4.7360 0.0683 0.19824486 0.1613 0.1919 0.7853 5.5576 3.6700 0.7597 3.2508 7.3309 0.3935 3.5793 0.1745 0.34154550 0.0224 0.0432 0.4415 4.4215 4.5762 0.5493 2.9794 6.0217 2.0375 5.8683 0.1010 0.25644551 0.0139 0.0332 0.6055 4.4294 4.9282 -0.0767 1.9995 5.5887 1.6128 4.7028 0.0851 0.22924564 0.0676 0.0663 0.8957 4.8933 4.5650 0.6813 3.0452 7.6485 1.5387 4.9770 0.1148 0.26684570 0.0757 0.0944 0.8363 5.3851 3.8914 0.7523 3.3158 7.2154 1.6724 4.8784 0.1284 0.28324621 0.1336 0.1474 0.4227 4.2083 3.5206 0.5421 1.3633 3.9753 0.7869 2.0798 0.1092 0.26954636 0.0555 0.0714 0.4243 2.6685 1.5837 -0.1840 1.2743 3.3618 0.7368 2.2358 0.0844 0.16424660 0.0873 0.0975 0.2431 3.8403 0.9425 0.0884 0.7775 2.1990 1.7095 2.6331 0.1212 0.2553

76

4.2

.F

utu

reW

ork

Table 4.7: Instrumental indices for the galaxies in the Virgo cluster sample.

Mgb Fe5270 Fe5335 Fe5406 Fe5709 Fe5782 NaD TiO1 TiO2 HδA HγA HδF HγF

3.6803 2.6171 1.3800 0.9291 0.5602 0.3782 2.5748 0.0244 0.0597 -2.0660 -6.0107 -0.3185 -1.50503.2297 1.2207 -0.0861 0.3926 0.3481 0.0363 3.8287 0.0233 0.0841 -1.7848 -4.6932 -0.6824 -1.70243.9647 2.6995 2.1580 1.3731 1.0915 0.6446 3.7417 0.0429 0.0898 -2.3812 -6.8752 -0.4851 -1.60883.4818 2.3034 1.8489 1.1064 0.7954 0.6051 1.9659 0.0335 0.0639 -1.6063 -5.9134 0.3019 -2.07143.4448 2.0289 0.8834 1.2215 0.9704 0.4629 3.1944 0.0405 0.0673 -0.2605 -3.7587 0.6439 -1.03504.4397 2.6291 1.3747 1.2730 0.9237 0.6642 4.2218 0.0389 0.0836 -2.0964 -7.2926 0.1104 -2.07683.5581 2.5011 1.7245 1.4752 1.1200 0.3233 2.8592 0.0028 0.0608 0.2893 -5.5780 1.0582 -1.79853.0585 1.8684 1.2146 0.5958 0.6606 0.1400 3.5014 0.0314 0.0808 -1.1746 -4.9181 -0.1970 -1.32843.9687 2.1903 0.5636 0.9160 0.6997 0.8999 3.3912 0.0453 0.0757 -0.4916 -5.6820 0.8360 -1.11513.4111 2.8343 1.1439 1.1214 1.0623 0.5424 1.7736 0.0301 0.0744 -1.1249 -5.3066 0.7035 -1.29574.4234 2.1250 1.0245 0.7577 0.5574 0.2879 4.3123 0.0311 0.0852 -1.8935 -7.8413 -0.8046 -3.12853.8238 2.6605 2.0962 1.1012 1.0298 0.8548 3.0102 0.0499 0.0966 -1.5894 -6.6969 -0.1938 -2.49073.8693 2.0918 0.6995 0.7182 0.7962 0.7451 3.0196 0.0306 0.0820 -1.1385 -6.8558 0.4339 -1.99744.2974 2.1812 0.6274 1.0717 0.5407 0.2083 4.6719 0.0149 0.0942 -0.4755 -6.6621 0.3687 -1.88784.2484 2.5814 2.0508 1.2379 0.2478 0.1400 4.3464 0.0155 0.0955 -1.8747 -6.4607 0.3129 -1.89323.4568 1.0016 -0.0250 0.4309 0.4541 0.1341 4.8509 0.0252 0.0907 -1.4908 -5.1463 -0.8734 -1.38692.2175 1.3852 0.6755 0.4659 0.4656 0.3136 2.0430 0.0175 0.0407 -0.8566 -3.6358 0.1289 -1.36422.9564 0.9633 0.0877 0.3887 0.5008 0.1347 2.8318 0.0186 0.0926 -1.1879 -3.9724 -0.1395 -1.5485

77


Table 4.8: Central velocity dispersion for the galaxy sample

name σ eσ

[km s−1] [km s−1]NGC4339 113.73 2.75NGC4365 256.15 3.33NGC4371 134.64 4.53NGC4377 144.06 9.8NGC4382 178.67 4.97NGC4406 235.01 3.04NGC4435 156.68 5.77NGC4442 186.73 8.65NGC4473 179.25 2.96NGC4474 87.67 4.03NGC4486 334.44 5.05NGC4550 96.42 4.16NGC4551 106.75 2.18NGC4564 157.4 3.1NGC4570 187.85 8.53NGC4621 225.15 3.23NGC4636 203.14 3.45NGC4660 188.59 3.46

78

4.2. Future Work

Table 4.9: Transformation coefficients

Index A B S1 0.009869 0.818802 0.0166892 0.000979 0.832564 0.0192433 0.069421 0.522971 0.1942674 0.107843 0.854220 0.3166765 -0.393729 0.858222 0.5176016 0.008392 0.440180 0.2341407 0.641915 0.592045 0.4462188 0.339604 0.880875 0.6015809 0.153286 0.898174 0.18282110 0.284715 0.844624 0.45234811 -0.020512 0.882045 0.00866312 -0.021166 0.957077 0.00718013 -0.121043 0.938143 0.23610214 -0.021916 0.880536 0.23434615 0.039937 0.727549 0.32210116 0.176319 0.617321 0.25391517 0.096817 0.789836 0.13253718 0.010941 0.726489 0.11184319 -0.072531 0.885038 0.17805320 0.001743 0.767047 0.00714121 0.005169 0.902520 0.00691722 0.473163 0.853874 0.84882223 -0.151009 0.947805 0.38379724 0.109053 0.898313 0.16807725 -0.315782 0.885442 0.305576

Table 4.10: General working plan for the accomplishment of the objectives

task First year Second year Third yearsemester A B A B A B

ETGs sampleLick indices and gradients *NIR spectra recalibration * *

LTGs samplePS model 1 *PS model 2 *

ComplementaryNIR observations * * * * * *advances report * * * * * *

writing * * *

79

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