A&A 423, 133-146 (2004)
DOI: 10.1051/0004-6361:20048007
P. Westera1 - F. Cuisinier1 - E. Telles2 - C. Kehrig2
1 - GEMAC, Observatório do Valongo/UFRJ,
Ladeira do Pedro Antônio, 43, 20.080-090 Rio de Janeiro, Brazil
2 -
Observatório Nacional,
Rua José Cristino, 77, 20.921-400 Rio de Janeiro, Brazil
Received 4 April 2003 / Accepted 5 May 2004
Abstract
We analyse the stellar content of a large number of HII galaxies from the continua and absorption features of their spectra using population synthesis methods, in order to gain information about the star formation histories of these objects.
We find that all galaxies of our sample contain an old stellar
population (1 Gyr) that dominates the stellar mass,
and in a majority of these we also found evidence for an
intermediate-age population
50 Myr apart from the
presently bursting, ionizing young generation
107 yr.
Key words: catalogs - stars: atmospheres - HII regions - galaxies: evolution - galaxies: starburst - galaxies: stellar content
HII galaxies are easily recognised from their prominent emission line spectra, very similar to those of HII regions (recombination lines of hydrogen and helium, as well as forbidden lines of elements like oxygen, neon, nitrogen, sulphur, and others, mainly in their first and second ionization stages). The continuum part of their spectra in the visible is much fainter, and mostly of stellar origin. HII galaxies show very intense star formation, which is responsible for the ionization of the gas and the subsequent emission lines. In most cases, HII galaxies possess old populations as well, that can generally be detected at a reasonable distance from their centers (Telles & Terlevich 1997).
For dwarf galaxies, which constitute a significant fraction of HII galaxies, the gas content is however too low for the star formation rate to have been sustained at the present level during their whole life. It is generally believed (e.g. Searle et al. 1973) that they spend most of their lives in a quiescent phase, and that the intense star formation phases in which they are encountered now are very short. The old population that is generally detected would then be the result of the accumulation of former bursts. Some exceptions may exist, like IZw18, where some authors say that the young bursting population is the only one (e.g. Papaderos et al. 2002), although others argue that a faint old underlying population does indeed exist, only detectable in the outskirts of the galaxy (e.g. Östlin 2000; Aloisi et al. 1999), and may be the result of an early low level continuous phase of star formation, as proposed by Legrand et al. (2000).
The bursting mechanisms are still unknown, although various have been proposed, of internal - (e.g. interaction of hot and cold gas phases, like in Tenorio-Tagle et al. 1999; see also Telles & Terlevich 1995) or external origin (e.g. tidal forces Salzer 1989; ram pressure Murakami & Babul 1999). The burst pattern is unclear as well: Does star formation occur simultaneously over the whole extent of the galaxy, or is the present star forming region formed by the accumulation of successive smaller star forming events, spread over the galaxy, over a short timescale?
Although stellar population synthesis analyses cannot give any
direct answer to the question of the origin of the bursts, they can
be quite helpful in bringing some insight in the recent star
formation history of these galaxies, and to a lesser extent in the
older one, and thus contribute to answering our second question,
e.g. what is the bursting pattern of HII galaxies? On this subject,
we already have some evidence that the recent star
formation is synchronised on scales of hundreds of parsecs rather
than self-propagated. This is what Telles et al. found from
a spatial-temporal analysis of optical and infrared surface
photometry of a sample of HII galaxies (Telles et al. 2004; Telles 2002).
It can also be seen from the H imaging atlas
of blue compact dwarfs of Gil de Paz et al. (2003).
Furthermore, stellar population synthesis allows us to put into
evidence old populations (e.g. older than 1 Gyr), although their
exact characteristics can be difficult to determine because of the
mixture with much younger populations.
In this paper, we use the continuum spectra of a large and
homogeneous sample of HII galaxies to gain information
about their (star formation) histories. Similar studies
include the work done by Raimann et al. (1996), Cid Fernandes et al. (2003), and
Kong et al. (2003). Raimann et al. (1996) use a star cluster spectral base to
identify the stellar populations present in their sample. They
find that HII galaxies are typically age-composite stellar systems,
presenting important contributions from generations up to as old as
500 Myr, and they detect a significant contribution of populations with
ages older than 1 Gyr in two groups of HII galaxies. Cid Fernandes
et al. use three absorption line strength indices and two continuum
colours to place the spectra in an evolutionary diagram, whose axes
carry the contribution of a young ionizing (10 Myr), an
intermediate (100 Myr), and an old (
1 Gyr) population to the
total flux, as determined by comparing their indices with the same
indices in synthetic spectra of these ages. They also find
evidence for populations of all three age groups. With the same
algorithm as Cid Fernandes et al., but using more absorption lines
and the continuum fluxes at five wavelengths and a base of 35 star-cluster spectra by Bica (1988), Kong et al. (2003) find that blue
compact galaxies (many of which are HII galaxies) are typically
age-composite stellar systems with stars from all three age groups
contributing significantly to the 5870 Å continuum emission of
most galaxies in their sample.
In this work we follow a similar approach: we define six spectral indices and determine for each spectrum the combination of the synthetic spectra of an old - and a young/intermediate stellar population, for which the indices of the empirical spectrum are best reproduced. The synthetic spectra are produced by two widely used evolutionary synthesis codes, GISSEL (Bruzual & Charlot 1993; Charlot & Bruzual 1991; Bruzual & Charlot 2000) and STARBURST (Leitherer et al. 1999), one of which (GISSEL) implements the new BaSeL 3.1 stellar spectral library, (Basel standard Stellar Library 3.1) (Westera 2001; Westera et al. 2002), which was calibrated using photometric data of globular cluster stars to improve the reproduction of the continua of the spectra of low metallicity stars. The goal of performing the analysis with two different libraries was on the one hand to check the reliability of the results, and on the other hand to find out through comparison of the results if the BaSeL 3.1 stellar library is able to reproduce the spectra of stars and populations beyond the parameter range of the objects used for its calibration, e.g. if the library can also be used for young stars and populations.
The layout of this article is the following: in Sect. 2, the catalog of spectra analysed in this work is presented. Section 3 gives a detailed description of the method we used to analyse the spectra. In Sect. 4, we discuss the accuracy of the method and its ability to give meaningful results. The main results are discussed in Sect. 5. A summary and the main conclusions can be found in Sect. 6.
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Figure 1: Example of an HII galaxy spectrum (UM 69, taken on August, the 18th, 1998). |
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The data base of this work consists of a catalog of intermediate
resolution (
)
HII galaxy spectra in the range of 3700
to 7500 Å. It contains about 200 HII galaxy spectra observed with
high signal-to-noise at the 1.52 m telescope at the European
Southern Observatory (ESO) within the agreement between Brazil and
ESO. All spectra were observed with the same instrumentation and
reduced in a homogeneous way.
The apertures were centered on star forming knots, and our work thus presents a bias towards young populations (as a matter of fact like all the HII galaxies spectroscopic surveys made up to now). The apertures we chose had the size of a few typical seeing widths, generally encompassing several stellar clusters. We therefore do not expect to have pure single stellar populations, but rather local mixes. Another important point is that a significant fraction of the galaxies were observed in several apertures, so we do not get only the most prominent knot, but also secondary ones (contrary to other spectroscopic studies), where the young population(s) is (are) less dominant in the integrated light. Table A.1 gives our galaxy sample and measured spectral indices as described below. Column 1 lists the names of the spectra, consisting of the names of the galaxies, and, in those cases where the apertures were centered on a secondary knot, an indication between brackets about the position of the aperture, where "Cent'' stands for the centre of the galaxy, and the abbreviations "N'', "E'', "S'', and "W'' (and "NE'' etc.) indicate that the aperture was positioned at knots at the North, East, South or West of the galaxy. Column 2 gives the type of the spectra ("in'': integrated spectra, "re'': spectra of individual regions). For more details about the catalog, see Kehrig et al. (2004).
The spectra were corrected for redshift, and then for internal gas
extinction.
The latter was done by converting the absorption constants
as determined by Kehrig et al. (2004) into extinction constants
using
(Sampson 2003), then
correcting for systematic differential extinction between the
stellar populations and the gas employing
(Calzetti et al. 2000) (which
leads to
), and finally
dereddening the spectra using the extinction law of Fluks et al. (1994).
Figure 1 shows a typical corrected spectrum. Apart from the typical emission lines of an HII region, most spectra also show significant continuum contributions from a mixture of stellar populations. A closer examination of this continuum reveals that many of these spectra show signatures of young/intermediate populations (certain absorption lines, i.e. of hydrogen, and a blue continuum), as well as spectral properties of old populations (a 4000 Å break, and absorption lines of heavy elements like calcium, iron, and magnesium), which leads to the conclusion that many of the galaxies of the sample have undergone periods of star formation before the present ionizing massive stellar population. The goal of this work is to analyse the stellar content of these galaxies, and gain information about their star formation histories, using the continua and the most evident absorption features of their spectra.
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Figure 2: Illustration of the six indices using UM 69 (the spectrum shown in Fig. 1) as an example. The dashed lines show the limits of the bands. The bands that enter with a positive sign into the calculation of the respective index are shaded with dotted lines running from the upper left to the lower right, and the bands that have a negative sign are shaded with dotted lines running from the upper right to the lower left. For a more detailed description of the indices, see the text. |
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We wish to characterise the population mixture in our galaxies
using the sensitivity of their spectra to the properties of these
populations, e.g. abundances - or metallicity - and ages.
Although we could directly fit modeled spectra to the observed ones,
and evaluate the various population parameters (e.g. ages and
metallicities) as the ones corresponding to the "best-fitting'' model
spectrum, we prefer to proceed in a more conservative way, and use a set of
pre-defined indices, chosen for their sensitivity to the parameters we
want to derive. The fitting procedure is thus done to the indices, and
not to the raw spectra. This presents the advantage of emphasising only
useful features in the spectra, giving a zero weight to parts that
either are badly flux calibrated (e.g. wavelengths lower than
), are contaminated by emission lines from
the gas, or are very noisy, or simply provide redundant
information. Because of the finite (and relatively low) number of
indices, the maximum number of free parameters we adopt to
characterise our galaxies is constrained in a straightforward manner.
We define six indices, relatively independent from each other, quantifying
certain properties of the spectra, which are particularly suitable
for identifying and characterising the stellar populations present in the galaxies
(the shape of the continuum, the 4000 Å break D(4000), and certain
spectral (absorption) line strength indices).
Most of the indices are inspired by the indices defined by Worthey et al.
(Worthey 1994; Worthey et al. 1994) and carry the same names, and by analogy are
defined in the following way:
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(1) |
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(2) |
Table 1: Wavelength ranges of the positive - and negative bands of the indices, with the associated errors.
The continuum index is something like the B-R colour with
rectangular passbands. For some spectra, it was necessary to cut
out a few tens of Å due to contamination of the spectra by
telluric skylines. For the other indices, the wavelength ranges
may differ slightly from the
ranges commonly used, since we optimised them for the spectra of
our sample. The bands of the 4000 Å break were reduced to a
width of 50 Å each because of the calibration uncertainties of
the spectra downwards of
Å affecting the - band and the presence of the strong H
emission line
within the + band of the traditional definition of this index. Of
the H
line, only the wings are used, because the region
around the central wavelength of this line is dominated by the
emission line of the gas. The line strength indices are defined
such that absorption goes to positive values and emission to
negative ones. Since all our indices are absorption features, they
are in general positive. However, as we do not make any correction
for the inclination of the continuum, the wavelength localisation
of the various bandpasses may sometimes induce negative values, as
is for instance the case for H
.
We preferred not to make
such corrections and to use indices instead of equivalent widths,
because we prefer to use quantities that are more directly linked
to the observed spectra, with a minimum number of in-between steps.
The calculated indices of individual spectra are listed in Table A.1.
The average signal-to-noise of the spectra amounts to 12.8 at the level of the continuum around 5500 Å (for the signal-to-noise values of individual spectra, see Kehrig et al. 2004). Using the relation that the error in the average flux in a passband amounts to the error per pixel divided by the square root of the number of pixels, we can calculate the typical observational errors of the narrow-band indices, whereas the typical error of the continuum index is dominated by uncertainties in the absolute flux calibration. Following Cuisinier et al. (1996) and Kong et al. (2003), we adopt a value of 10% for these uncertainties. We list the typical observational error of each index in Table 1. They are also shown as error bars in Figs. 3 and 4.
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Figure 3:
Distribution of the sample spectra (symbols) in different
two-index planes compared with SSPs (lines). The solid lines
represent the evolutionary paths of SSPs of different metallicities
between
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Figure 4:
Distribution of the sample of spectra (symbols) in different
two-index planes compared with composite stellar populations
(lines). In relation to Fig. 3, the range of
the indices has been centered on the region where most of the
observed data lie. The solid lines represent the compositions of
an old population (age 5 Gyr,
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Figure 3 shows examples of how the spectra are
distributed in two-index planes compared to the same indices
calculated for simple stellar populations (SSPs) of a wide range of
ages (dashed lines) and metallicities (solid lines) from the
"BC99'' ("Bruzual & Charlot 99'') SSP library which will be
described later on in this section.
It can be seen that the observed indices (crosses) of the spectra
lie in the region where the SSPs of young and intermediate age can
be found (denoted by "young'' in Fig. 3), which
shows that young and intermediate age populations dominate the
spectra (but not necessarily the stellar mass of the galaxies). In
the panels showing the continuum index vs. H plane
(lower left), and the panel showing the 4000 Å break vs. H
plane (lower right), it is striking that the observed indices of many spectra lie outside the ranges occupied by
the SSP models, e.g. inside the loop in these ranges, another
indication that one single population alone cannot reproduce the
sample spectra adequately.
An indication that this can be remedied by combining populations of
different ages and metallicities can be seen in
Fig. 4. It shows the same two-index planes
as in Fig. 3 (with different scales), but here
the empirical indices are compared with composite stellar
populations. The composite populations are made up of an old
population with
and an age of 5 Gyr and, and a
young or intermediate one with
and different ages
ranging from 1 to 500 Myr (different dashed lines, increasing line
thickness means increasing age). The solid lines mean different
mass ratios between the two populations ranging from
My+i:
(only an old population) to 1:0 (only a
young or intermediate population), increasing line thickness means
decreasing My+i:
.
The main problem of single stellar
population models to explain the distribution of the observed data
in the two-indice planes is that for index combinations containing
,
the observed data fill a region where no models
are present, within a loop created in the models at young ages (see
Fig. 3, lower panels).
Combining young+intermediate and old populations in composite models
makes it possible to resolve this issue, filling in the loop, and
thus better reproducing the combination of indices of the sample
spectra than SSP models are able to do
(see Fig. 4, lower panels).
For these reasons, we decided to explore the stellar composition of
these galaxies by assuming
them to be made up of two stellar populations, an old, metal-poor
one, hereafter the "old population'', and a younger one (that is,
of young and/or intermediate age), which for simplicity will be
referred to as the "young+intermediate population''.
This is a simplification, for the young+intermediate population
will always contain the very young ionizing massive stellar
population (age
,
possibly mixed up with an
intermediate age population, which may consist of several
subpopulations (that we are unable to discern)). The old
population may also represent a combination of several, but old,
populations.
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Figure 5: Example of a "best fit''. The thin line represents the empirical spectrum (UM 137(W), taken on August, the 18th, 1998), the thick solid white line shows the best fit spectrum obtained using the "BC99'' library, and the thick dashed white line (which sometimes hides the solid line) shows the best fit using "Starburst''. |
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The star forming history of HII galaxies may be far more complex than what can be realistically modeled in a simple manner from their spectra. Hypotheses for star formation histories are various, as briefly mentioned in the introduction; a bursting mode followed by quiescent phases, continuous star formation but sustained at a low intensity extending far back in past, or a unique single event. Many of these scenarios, however, are indiscernible from the point of view of a spectral analysis using only integrated spectra, as was also noticed by Lilly & Fritze-von Alvensleben (2003). We thus have to limit ourselves to an arbitrary, simpler choice of populations whose properties we believe we are able to distinguish.
Within this choice, it is not possible to determine more than only a
few parameters, and the results found using only two populations
already furnish interesting results about the formation histories of
the sample galaxies.
For the five parameters My+i:
(the mass relation between the
young+intermediate - and the old population),
/
(the ages of each population), and
/
(the respective metallicities), we took into consideration the possible
values given in Table 2.
Note that only two of these parameters, My+i:
and
,
are free (thus to be determined in this work), and the
discussion about the solutions will mainly consist of interpreting
the values found for these two parameters. The metallicity of the
young population is given by the
values of the gas as
determined from the emission lines by Cuisinier et al. (2004) in a
parallel article to this one, which deals with the emission part of
the spectra, as the young population should be more or less coeval
with the gas, whose metallicity is the metallicity attained now by
these galaxies (Cuisinier et al. 2004; Pagel et al. 1992).
Table 2: Possible values of the population parameters.
In those cases where
The best fits were performed using two different libraries of SSPs
in order to determine the reliability of the results. Another
by-product of this study is to test if the new synthetic stellar
spectral library BaSeL 3.1, which was calibrated using globular
cluster photometrical data to improve the reproduction of
the continuum contribution of spectra of low metallicity stars
(
), can be used for young or
intermediate stars and populations, thus for objects outside the
parameter range of the objects used for its calibration. The first
SSP library (hereafter the "BC99'' library) was
produced using the Bruzual and Charlot 2000 Galaxy Isochrone
Spectral Synthesis Evolution Library (GISSEL) code
(Bruzual & Charlot 1993; Charlot & Bruzual 1991; Bruzual & Charlot 2000), implementing the Padova
2000 isochrones (Girardi et al. 2000) combined with the BaSeL 3.1
"Padova 2000'' stellar library. We used a Salpeter initial mass
function (IMF) from 1 to 100
,
to be able to make direct
comparisons with the second SSP library, from now on called the
"Starburst'' library, which uses the same IMF. The "Starburst''
library consists of spectra from the STARBURST99 data package
(Leitherer et al. 1999) using the option of including nebular continuum
emission (Fig. 1 on the STARBURST99 web site). It implements the
predecessor of the BaSeL 3.1 library, the widely used BaSeL 2.2
library (Lejeune et al. 1998,1997), and for stars with strong
mass loss the Schmutz et al. (1992) extended model atmospheres, combined
with the Geneva isochrones
(Meynet et al. 1994; Charbonnel et al. 1993; Schaller et al. 1992; Schaerer et al. 1993b,a). Apart from
the implementation of different isochrones and stellar libraries,
one of the main differences between the "BC99'' and the
"Starburst'' libraries lies in the inclusion of the nebular
continuum emission under the hypothesis of optical thickness of the
nebulae, e.g. that all photons with wavelengths below 912 Å are
absorbed. This affects the spectra of young populations (up to 10 Myr) shortward of 4500 Å. For the old population, the "BC99''
spectrum was used, since the Starburst99 data package only contains
spectra up to 900 Myr.
The best fits were performed by minimising the quantity
In the end, a selection of acceptable solutions was made. All spectra which had a too bad signal-to-noise or a strange shape, indicating calibration problems in the data reduction, were eliminated from the sample. This selection was done by eye. Figure 5 shows an example of an accepted fit.
A major concern in our method stems from the fact that the
spectra of our sample have a higher resolution than the spectra in
the "BC99'' and "Starburst'' libraries. Whereas the sample
spectra have a resolving power of
,
the synthetic
spectra have only around
in the optical. However,
degrading our spectra to this resolution would significantly
reduce the amount of information they hold, particularly in the
H
index, for which the contamination of the
H
emission line would increase dramatically. As this
line is in general much stronger than the absorption line which
the index is trying to quantify, it would dominate the index after
a degradation. Correcting for the contribution of the emission
line using an estimate of the H
flux based on the
fluxes of other Balmer lines would still leave us with an error as
large as the error of this estimate, which is much larger than the
variation of the index itself. For this reason, we decided to
study the effect of resolution on the fits rather than to degrade
our sample spectra. This study was done by performing the best
fits on synthetic high-resolution spectra of known ages. The
synthetic spectra, in the following called the "BC-2000''
synthetic SSP spectra, were again produced with the GISSEL
software using the same input parameters (IMF, stellar
evolutionary tracks) as for the "BC99'' library but this time
implementing the BC-2000 (Bruzual & Charlot 2000) stellar
library. This is a library of empirical stellar spectra, mainly
from a catalog assembled by Pickles (1998), with higher
resolution than the theoretical libraries (
), but
containing only solar metallicity stars. For a more detailed
description of the BC-2000 stellar library, see
Bruzual & Charlot (2003,2000). We then determined the ages of
these spectra in the same way as we determined the population
properties of the HII galaxy spectra: by minimising the
defined in Eq. (3)
(using a signal-to-noise value of 12.8 for the estimate of the
errors
of the BC-2000 spectra, which corresponds
to the average signal-to-noise of the HII galaxy spectra)
for "BC99'' and "Starburst'' SSPs of solar metallicity, and
considering ages of 1, 2, 5, 10, 20, 50, 100, 200, and 500 Myr.
In Fig. 6, the best
fitting ages obtained in this way are shown as a function of the
age of the original "BC-2000'' SSP ages. In spite of the
different resolutions of the "BC-2000'' (input) spectra and the
spectra used to fit the ages ("BC99'' and "Starburst''), the
ages are well reproduced with a slight tendency to favour young or
intermediate ages. We conclude from this that the higher
resolution of the empirical spectra does not pose greater problems
for the fitting procedure and for the accuracy of the parameters
we wish to determine. For these reasons,
we preferred not to degrade the spectra of our sample to the
"BC99'' and "Starburst'' resolution.
To check how useful our indices are for deducing population mass ratios and ages from our spectra we performed various tests with the observed indices and derived parameters.
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Figure 6: Ages of the best fits performed on "BC-2000'' synthetic SSPs as a function of their ages. The solid line shows the best fits using the "BC99'' library, and the dashed line shows the best fits using "Starburst''. The dotted line represents identity. |
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After rejection of all spectra that presented strange behaviour of the fitted model spectra, solutions were found for 123 spectra from 78 different galaxies.
Performing the best fits while varying the indices by their typical
observational errors (as listed in Table 1) showed that
in the worst case (if the errors in all indices conspire), they can
modify the solutions by around one step (a factor of 3) in
My+i:
or two steps (a factor of
5) in
.
For most spectra, however, the errors will
not conspire, as they are random and not correlated,
so the statistical properties of the sample discussed
in this section should not be too affected by the observational
errors. The solutions are presented in Table A.2.
We will first investigate how these results depend upon the
different indices of the galaxy spectra. My+i:
correlates (weakly) with the continuum index and with D(4000),
but not with the other indices (not shown here). Figure 7
shows the correlations of the indices with the derived age of the
young+intermediate population. It correlates with D(4000) (upper
middle) and (weakly) with the continuum index (upper left) and H
(lower left). For the continuum index, the trend reverses at
Myr, where the
nebular emission starts to influence the continuum (for very young
ages it even dominates the spectra below 3600 Å).
The other indices correlate only weakly (if at all) with
.
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Figure 7: The ages of the young+intermediate population as a function of the indices of the spectra. The crosses represent the solutions found using "BC99'', and the squares represent the "Starburst'' solutions. The typical errors in the indices are shown as error bars in the upper left corners of the different panels. |
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The examination of how well the indices of the galaxy spectra are
being reproduced in the fits yields the answer that could be
expected from the typical observational errors of each index
(Fig. 8): the 4000 Å break is well
reproduced in the best fit spectra, and the continuum index
a bit less well (but acceptably). The
and H
indices represent the worst cases of our
adopted fit indices: our fit values present some correlation with
the observed values, but with a systematic tendency to an
underestimation of
and an overestimation of H
.
For H
,
this is due to the fact that
the models only predict values above
0.03. This can also
be seen in the lower panels of Fig. 4.
A possible explanation is that the underlying population in some
of the galaxies could be older than 5 Gyr, which would lead to
lower values of H
.
However, the trends in
and H
are
unlikely to influence the statistical properties of our overall
results in a systematic manner, as they drive the parameter My+i:
in opposite directions, as well as the age of the young+intermediate population.
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Figure 8: The indices of the empirical spectra vs. the same indices of the synthetic spectra (thus the reproduction of these indices). The crosses represent the solutions found using "BC99'', and the squares represent the "Starburst'' solutions. The lines represent identity (perfect reproduction). The typical errors in the observed indices are shown as error bars in the upper left corners of the different panels. |
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To determine to what amount these results depend on the SSP library
(and thus on the stellar library) that was used, it is necessary to
compare the results obtained with the two different libraries for the
same spectra.
Figure 9 shows the agreement between the best fits made
with the two libraries for the My+i: ratio, and
Fig. 10 shows the same for the
.
In most cases, the two libraries yield the same value for My+i:
,
and this parameter differs significantly between
the two libraries only in three cases.
In these three cases, either the "BC99'' - or the "Starburst''
solution predicts the existence of only a young+intermediate
population (My+i:
:0), whereas the other library
predicts a significant old population (My+i:
:1 or 1:30).
A closer look at these spectra does not reveal why the fits with the
two libraries yield such different results. In spite of the completely
different population parameters, the best fitting composite model
spectra of the "BC99'' and "Starburst'' solutions look very similar.
In almost half of the cases however, the two libraries yield
identical results, and in most of the rest the solutions are similar
enough.
The two libraries also do not show any systematic differences in the
indices calculated from the best fit spectra
(see Fig. 11).
The similarities between the solutions found with the two libraries
are also confirmed when comparing the
(Fig. 12).
Thus, for the vast majority of the spectra,
the solutions found with both libraries show good
agreement in all three: the population parameters found, the
reproduction of the indices, and ,
which gives us
confidence in the solutions and in our general conclusions.
Given all these similarities, it is not possible to conclude from
this study alone if the BaSeL 3.1 stellar library does a better job
at reproducing spectra than its predecessor. It is encouraging that
the two SSP libraries yield results of comparable quality, even though
the "Starburst'' library has additional features implemented (nebular
continuum emission, inclusion of the Schmutz model atmospheres for stars
with strong mass loss) aimed at a better reproduction of the spectra of
young+intermediate populations.
Further studies, aimed more directly at the properties for which the
BaSeL 3.1 library was designed (a better reproduction of the continuum
contribution of low metallicity stellar spectra)
will be necessary to clarify this point.
The composition of HII galaxies may be far more complex than just the two young+intermediate and old populations we are using in our modeling - as we stated earlier, they can have a far more complicated star forming history, not only in time but also in its spatial distribution. Our modeling represents our lack of ability to segregate more than only a few stellar populations with very distinct ages. It is in particular very hard to differentiate old populations because their spectrophotometric properties are so similar (Lilly & Fritze-von Alvensleben 2003); that is the reason why we grouped them all in a generic old population, but we have to keep in mind that we have very little insight in the constitution of this generic old population.
Nevertheless, some star forming history scenarios can clearly be ruled out from the point of view of our modeling, such as extreme limiting scenarios presenting one single population, either only old or only young.
In this section, we will discuss various possible star forming histories in the light of our modeling.
We were able to derive mass ratios between the young+intermediate
and the old populations. Figure 13 shows how these mass
ratios are distributed. The upper panel is a histogram of the best
fitting My+i:
of all apertures for all galaxies for which
solutions were found, and the lower panel is a histogram made up of
one My+i:
value (the lowest one found) per galaxy, in
order to emphasise the old stellar component.
![]() |
Figure 9:
The number of cases, in which a certain value (x) of My+i:![]() |
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Figure 10:
The number of cases, in which a certain (x) value of
![]() |
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Our study indicates that in terms of mass, the old population is
overwhelmingly dominant, by a factor of 100 in most
of the apertures in all galaxies (the peaks at
My+i:
of Fig. 13).
For the one galaxy where the integrated spectrum yielded
only a young+intermediate population (DDO155) we were able to
obtain evidence for an old population in other apertures.
Only in two cases that were observed in one aperture only (Tol1223-359
and UM 323) did the best fits yield no old population
(the sole points at My+i:
of panel b of
Fig. 13), albeit only in the fit using one of the two
libraries. In these cases, the fit with the other library did present a
(dominating) old population (see also Sect. 4.3),
so even in these dubious cases we have some evidence for an old
population.
It is however difficult to make any further statement on the nature of
the old population, except that it should be older than
1 Gyr, because spectral features are so similar after this
age, when compared to younger populations - which actually dominate
the spectra of these galaxies. Within this age limitation, the old
population could be anything: accumulation of former bursts, or a low
intensity, but long lasting continuous star formation episode.
Whatever the star forming history of the old population may be, the important point is that the sum of the early events of star formation turned much more gas into stars than the present one.
![]() |
Figure 11: Comparison of the indices of the solutions obtained with "BC99'' and "Starburst'' (crosses). The lines represent identity. |
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The only other free parameter of our study is the age of the
young+intermediate population. Figure 14 shows histograms
of the best fitting
of all spectra for which
solutions were found (upper panel), and of the oldest young+intermediate
population found in each galaxy (lower panel).
The young+intermediate population is a mixture of a certain young bursting population that is able to ionize the interstellar medium (age < 10 Myr) and - maybe - an intermediate age population (whose age could be anything between 10 Myr and 500 Myr).
It is noteworthy that a significant fraction of our galaxies (60%) present young+intermediate ages greater than 10 Myr (lower panel
of Fig. 14), indicating in these cases the very
existence of an intermediate age population in addition to the
ionizing massive stellar component which necessarily is younger than
10 Myr. Some individual differences exist between the fits with the
"Starburst'' and "BC99'' libraries, especially in the age
range from 5 to 50 Myr. However, in general the results are consistent, as could already
be seen at the end of the previous section.
As we stated earlier, we do not disentangle possible multiple events in the intermediate age population but only indicate its presence and its average age. Therefore, it does not appear in our modeling by itself, but rather in a weighted mean together with the young population - with weights that are difficult to determine. Despite these drawbacks, some points are, however, worth being stated. First, the mean age distribution of the young+intermediate population, although quite broad, is peaked around 10/20 Myr ("BC99'') and 50 Myr ("Starburst''), indicating that the mean age of the intermediate population should be at least of the same order.
To summarise, in 60% of the galaxies of our sample, we see an
intermediate population, whose mean age should be of the order of at
least 20/50 Myr and more likely
50 Myr.
![]() |
Figure 12:
Comparison of the ![]() |
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![]() |
Figure 13:
Histogram of the best fitting My+i:![]() ![]() |
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![]() |
Figure 14:
Histogram of the best fitting
![]() |
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In this work, we analyse the stellar content of a sample of HII galaxies, of which we have intermediate resolution (
)
and high enough signal-to-noise spectra with a wavelength range of 3700 to 7500 Å, using the continua and certain absorption features of the spectra.
To identify stellar populations in these galaxies and to
determine their properties (masses, ages, metallicities), we defined
six spectral indices (a continuum index and five indices inspired by
Lick indices as defined by Worthey et al. (1994); and Worthey (1994), but
optimised for the sample spectra).
In a best fit procedure, we then determined for each HII galaxy
spectrum the combination of two synthetic SSP spectra
(one of an old stellar population, and one of a young/intermediate age)
that best reproduces the indices of the empirical spectrum.
Although there are certainly more than just two populations in our galaxies, we justify our approach by the fact that we want to use a minimum set of free parameters to describe their observed spectral features.
The main results of the analysis are the following:
Acknowledgements
This work was supported by the Swiss National Science Foundation. Furthermore, we would like to thank the Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (Faperj) for the help on the infrastructure for this project. We also thank the group "Galaxies: Formation, Evolution, and Activity'' of the programme PRONEX of the Conselho Nacional de Desenvolvimento Cientifico Tecnológico in Brazil for travel expense allowances. Finally we are grateful to an anonymous referee whose comments greatly helped us to improve the presentation of this paper.
Table A.1: Indices of individual spectra.
Table A.2: Population parameters of individual spectra.