Early-type galaxies colour gradient and their relation with global galactic properties

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Early-type galaxies colour gradient and their
relation with global galactic properties
V. Gonzalez-Perez1, F. J. Castander1 and G. Kauffmann2
1
2
Institut de Ciéncies de l’Espai (CSIC-IEEC), Campus UAB, F. de Cincies, Torre
C5 par-2, Barcelona 08193, Spain gonzalez@ieec.uab.es
Max-Planck-Institut für Astrophysik, D-85748 Garching, Germany
Summary. We have studied the colour gradients of 48175 early-type galaxies, at
0.02 ≤ z ≤ 0.12, with photometry in the g 0 , r0 , i0 , z 0 bands from the Sloan Digital
Sky Survey (SDSS) Data Release 4 (DR4). The selected galaxies have been classified
as early-type since their Sersic index is n ≥ 3. The distribution of colour gradients
does not follow a Gaussian due to an excess of galaxies in the tails. This excess has
been related with steep age gradients, AGN activity or an unusual dust content. The
median gradients of our sample are: −0.014, −0.004, −0.023, for the (g 0 −r0 ), (r0 −i0 ),
(i0 − z 0 ) colours, respectively. We find 15% of galaxies with positive gradients. The
relation between colour gradient and several galactic properties has been studied,
but no correlation has been found.
1 Introduction
The most widely accepted model on formation and evolution of structure is
the hierarchical model[12][2], based on a cold dark matter cosmology. It proposes that galaxies are the final result of the primordial density fluctuations
evolution. In particular, the hierarchical model states[8] that massive galaxies
assembled a high percentage of their mass in the recent past. Massive galaxies
are mainly early-type ones. These galaxies conform a very homogeneous group,
in the sense that their observational properties follow tight relations with little
dispersion[9]. They are characterised by having a dominant old stellar population, practically no gas and a minimal star formation rate[3]. Moreover, they
form a well defined red sequence[1]. All these features suggest a formation at
high redshift, z > 3, followed by passive evolution. This is exactly what the
monolithic collapse model of formation predicts[6]. Nevertheless, early-type
galaxies properties can also be reproduced by the hierarchical model if AGN
feedback is taken into account[8]. This feedback induces the end of star formation at high redshifts, but merging processes continue almost until today.
Therefore, although most stars in early-type galaxies were formed at z > 1,
they finished assembling at z < 1.
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V. Gonzalez-Perez et al.
Simulations within the hierarchical formation scenario have shown that the
formation and evolution processes determine the galactic internal structure[16].
Thus, the study of the internal variation of colour in galaxies, through colour
gradients, can be useful to understand such processes.
In this paper we study early-type galaxies colour gradients, their distribution
and relation with other galactic properties. We assume a flat cosmology with
Ω0 = 0.3 and h = H0 /100(Kms−1M pc−1 ) = 0.7.
2 The sample and its internal colour variation
From the SDSS DR4, we have selected galaxies with 0.02 ≤ z ≤ 0.12, good
photometry (according to flags), spectroscopic measurements, a petrosian
magnitude in r’-band: 14.5 < r 0 < 17.77 and a petrosian radius measured
with errors less than a factor of 2. We define early-type galaxies as those
with a Sersic index n ≥ 3, in g’,r’,i’ and z’ bands. This index is taken from
the NYU-VAGC catalog[4]. Our sample contains 48175 early-type galaxies.
Visual inspection of 90 random galaxies from our sample showed a 15% of
contamination by late-type, irregular and interacting galaxies.
Colour gradients are obtained from galaxy fluxes measured within circular
annuli. A minimum of four annuli is used, neither including the two inner
ones (most affected by seeing), nor the most noisy outer ones. The surface
brightness profile is obtained fitting a taut spline[7] to the cumulative profile and then differentiating that spline fit. In this way we obtain a flux associated with each different radii, from which magnitudes and colour profiles are calculated, taking into account observational errors, through Monte
Carlo realizations. A linear least-squares method is adopted to fit the derived
colour profiles. Colour gradients, 5(g−r) , 5(r−i) and 5(i−z) , are expressed
as 4(m1 − m2 )/ 4 (R/R50), where the radii are normalised by the radius
containing half of the total petrosian light in the r’ band. A global galactic (K+e)-correction is applied to magnitudes at each radii. This correction
is evaluated using spectra energy distributions generated with the PEGASE
galaxy evolutionary code[10].
3 Results and discussion
3.1 Distribution of colour gradients
The median colour gradients for our sample of early-type galaxies are: −0.014,
−0.004, −0.023, for the (g 0 − r0 ), (r0 − i0 ), (i0 − z 0 ) colours, respectively. This
shallow values reflect that the old stellar population that dominates earlytype galaxies is homogeneously distributed. Though, some extreme cases can
be found.
Early-type galaxies colour gradient
3
Fig. 1. Distribution of colour gradient: 5(g−r) (left), 5(r−i) (centre), 5(i−z) (right).
The dotted lines show the best Gaussian distribution fit. The dash line is the envelope of the sum of two Gaussians, that best fits the data.
The colour gradient distributions are best fitted by the sum of two Gaussians. As can be observed in Fig.1 these distributions start to differ from a
Gaussian at their tails, finding more galaxies than expected for a normal distribution. Colour gradients are mainly due to metallicity gradients[21]. Age
gradients constitute their secondary origin and dust affect them marginally,
by steepening negative gradients [18]. In average, early-type galaxies have
negative metallicity gradients and positive but smaller, in absolute terms, age
gradients[19]. Thus, colour gradient distributions can be explained as the result of superimposing to the normal distribution of early-type galaxies some
galaxies with either an unusual age gradient or dust content. From the theoretical point of view, metallicity gradients, and therefore colour gradients, are
driven by the formation/evolution processes in a galaxy[16]. Galaxies formed
through minor mergers at high redshift have similar characteristics to those
within the monolithical collapse scenerio, in which galaxies form within a
deep potential well, producing gas to accumulate at the central regions. Thus,
galaxies formed in a process similar to a monolithical collapse should show
steeper negative gradients than those whose last major merger occurred at
z ≤ 3. In order to explain the wide colour gradient range, certain fraction of
early-type galaxies should have assembled most of their mass at high redshift.
We find that 15% of galaxies in our sample show a positive colour gradient, not
compatible with zero. Other studies at low redshift found up to 5% galaxies
with a positive gradient[21]. Positive colour gradients are probably associated
with AGN activity and steep age gradients[21]. The latter can be only explained if stars have formed recently in the galaxy. Studies on star formation
signatures in early-type galaxies find that 3% show Hα emission lines with
equivalent widths, EW, greater than 10Å [20](23% if EW greater than 2Å
[22]) and this percentage rises until the 30% if UV-optical colours are used
as probes of recent star formation activity[15]. Our result is compatible with
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V. Gonzalez-Perez et al.
these studies. At intermediate redshift, 0.37 < z < 0.83, 30% of field spheroids
show an unusual internal colour variation, that for most cases appears as a
bluer core[17]. Therefore, we find that the amount of early-type galaxies with
a positive colour gradient decreases with redshift. This evolution is consistent with the global star formation diminution predicted by the hierarchical
model[8].
3.2 Relation between colour gradients and other galactic
parameters
In order to be able to study differences between galaxies with extreme and
normal colour gradient values, we define three sub-samples that will be referred to as: negative, normal and positive. The negative and positive samples
contain galaxies with colour gradient values out of 3σ (considering their errors) from the Gaussian that best fits the gradients distribution. The rest will
belong to the normal sample. A Kolmogorov-Smirnov test shows that these
sub-samples are statistically different. For the three galactic sub-samples, we
have studied the possible relation between 5(g−r) and the following structural
parameters, taken from the SDSS MPA/JHU public data base:
•
•
•
•
•
•
•
redshift,z
stellar mass, log(M /M ) [13]
mass-luminosity ratio in z’ band, log(M/L) [13]
star formation rate, log(SF R /M /yr) [5]
SFR-stellar mass ratio, log(SF R/M ) [5]
r’-band weighted age, log(age /yr) [11]
stellar metallicities, log(Z /Z ) [11]
These parameters are accessible for most galaxies in the SDSS DR4, except
the age and the metallicity that are only calculated for SDSS DR2 galaxies.
For all the cases, the Spearman index is | rS |≤ 0.1 with a significance greater
than 0.2. Thus, no clear correlation has been found. Pure monolithic collapse
models predict that metallicity gradients depend on the galactic mass[6]. This
dependency, if exists, should also be seen for colour gradients, but this is not
the case.
The studied parameters median values are similar for the three sub-samples
of galaxies (see table 1). Nevertheless, galaxies in the positive sample tend to
be less massive and with a stellar population slightly younger. Both positive
and negative samples have higher SFR per mass unit, with respect to the
normal one. In the case of the negative sample, which contains slightly more
massive galaxies, this produces its median SFR to be higher than expected.
Star formation bursts can be traced by the characteristic spectral features that
they produce, as for example the Balmer absorption line HδA joined with the
4000Å break [14]. Using these parameters we find that only 8% of galaxies in
the normal sample show evidences of a burst during the past 2 Gyr. This percentage raises up to a 13% and a 38% for the negative and positive samples,
Early-type galaxies colour gradient
5
Table 1. Median values of some galactic properties for the negative, normal and
positive samples, defined in Sec.3.2
z
log(M )
log(M/L)
log(SF R)
log(SF R/M )
log(Age)
log(Z)
Negative
Normal
Positive
+0.027
0.080−0.028
+0.27
10.80−0.35
+0.098
0.197−0.12
+0.43
0.051−0.75
+0.35
−10.72−0.74
+0.12
9.77−0.25
+0.17
−1.61−0.30
+0.027
0.083−0.027
+0.34
10.71−0.36
+0.10
0.18−0.13
+0.57
−0.34−0.83
+0.49
−11.03−0.87
+0.085
9.843−0.24
+0.16
−1.63−0.20
+0.028
0.078−0.033
+0.44
10.52−0.55
+0.14
0.11−0.19
+0.62
−0.22−0.96
+0.63
−10.64−1.1
+0.21
9.67−0.65
+0.26
−1.64−0.37
respectively, reassuring the tendency of the median values.
It is also interesting to check the presence of AGNs in the samples. We consider
galaxies with any kind of nuclear activity, according to the SDSS MPA/JHU
data base[5], to be AGNs. The presence of AGNs is: 16% for the normal sample, 56% for the negative one and 34% for the positive sample. Less than 30%
of the AGNs had a recent star formation burst.
These results suggest that steep gradients, specially positive ones, are mainly
due to recent star formation episodes. This can be seen as a signature of the
continuous formation of early-type galaxies until now, proposed by the hierarchical formation model. AGN activity seems to be more present in galaxies
with steep negative gradients. Nevertheless, it should be taken into account
that contaminating galaxies can be raising the percentage of extreme gradients.
4 Conclusions
We have studied the internal colour variation in early-type galaxies using
the SDSS DR4. Early-type galaxies are defined as those with a Sersic index
n ≥ 3. Selcted galaxies are nearby, 0.02 ≤ z ≤ 0.12, have good photometry
and their spectra have been measured. The median gradients are: −0.014,
−0.004, −0.023, for the (g 0 − r0 ), (r0 − i0 ), (i0 − z 0 ) colours, respectively. These
colour gradients do not follow a Gaussian distribution, due to the higher number of galaxies at the tails. A 15% of early-type galaxies have positive colour
gradient. This amount of galaxies is higher than what was found by other
colour gradients studies[20] (maybe due to contamination by different galaxy
type) but it is in consonance with studies on star formation activity[15]. Studies at intermediate redshift[17], found 30%, therefore, our result suggest that
the fraction of young stars in the centre and/or AGN activity decreases with
redshift.
Three subsamples of early-type galaxies have been defined, in order to study
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V. Gonzalez-Perez et al.
separately galaxies with normal shallow colour gradients from those with steep
ones. For any of these sub-samples, no correlation has been found between
5(g−r) and the following galactic properties: redshift, stellar mass, mass to
luminosity ratio, SFR, SFR-stellar mass ratio, age and metallicity. With respect to the normal sample, galaxies with extremely steep gradients are likely
to contain a higher percentage of young stars, related with signatures of recent
episodes of star formation and/or AGN activity.
Further work is needed for a robust determination of the the exact origin of
extreme colour gradient values and to study systematics.
Acknowledgements
We thank I. Ribas, J. Lucey and R. Smith for their helpful comments and
encouragement. VGP acknowledge receipt of CSIC FPI scholarship.
References
1. M. L. Balogh, I. K. Baldry, R. Nichol, C. Miller, R. Bower, and K. Glazebrook.
APJL, 615:L101–L104, 2004.
2. C. M. Baugh, S. Cole, and C. S. Frenk. MNRAS, 283:1361–1378, 1996.
3. M. Bernardi et al. AJ, 125:1817–1848, 2003.
4. M. R. Blanton et al. AJ, 129:2562–2578, 2005.
5. J. Brinchmann, S. Charlot, S. D. M. White, C. Tremonti, G. Kauffmann,
T. Heckman, and J. Brinkmann. MNRAS, 351:1151–1179, 2004.
6. C. Chiosi and G. Carraro. MNRAs, 335:335–357, 2002.
7. C. de Boor. A practical guide to splines. Applied Mathematical Sciences, New
York: Springer, 1978, 1978.
8. G. De Lucia, V. Springel, S. D. M. White, D. Croton, and G. Kauffmann.
MNRAS, 366:499–509, 2006.
9. S. Djorgovski and M. Davis. APJ, 313:59–68, 1987.
10. M. Fioc and B. Rocca-Volmerange. A&A, 326:950–962, 1997.
11. A. Gallazzi, S. Charlot, J. Brinchmann, S. D. M. White, and C. A. Tremonti.
MNRAS, 362:41–58, 2005.
12. G. Kauffmann, S. D. M. White, and B. Guiderdoni. MNRAS, 264:201–+, 1993.
13. G. Kauffmann et al. MNRAS, 341:33–53, 2003.
14. G. Kauffmann et al. MNRAS, 341:54–69, 2003.
15. S. Kaviraj et al. In press, astro-ph/0601029.
16. C. Kobayashi. MNRAS, 347:740–758, 2004.
17. F. Menanteau, R. G. Abraham, and R. S. Ellis. MNRAS, 322:1–12, 2001.
18. R. Michard. A&A, 441:451–464, 2005.
19. P. Sánchez-Blázquez, J. Gorgas, and N. Cardiel. A&A, 457:823–839, 2006.
20. N. Tamura and K. Ohta. MNRAS, 355:617–626, 2004.
21. H. Wu, Z. Shao, H. J. Mo, X. Xia, and Z. Deng. APJ, 622:244–259, 2005.
22. Y. Zhao, Q. Gu, Z. Peng, L.and Luo X. Shi, and Q. Peng. ChJAA, 6:15–24,
2006.
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