Received 02nd April 1998
"The Magellanic Clouds and Other Dwarf Galaxies
of the Bonn/Bochum-Graduiertenkolleg
The star formation history of Leo I
Aparicio2, Wendy Freedman1,
Giampaolo Bertelli3,4, and Cesare Chiosi3
813 Santa Barbara St. Pasadena CA 91101 USA
de Canarias, E-38200 La Laguna, Canary Islands, Spain
3Dipartimento di Astronomia
dell'Università di Padova, Vicolo dell'Osservatorio 5, I-35122- Padova,
National Council of Research, CNR-GNA, Rome, Italy
We present results on the star formation history of the Local Group
dSph galaxy Leo I, obtained through the analysis of its deep
color-magnitude diagram (CMD)
using model CMDs computed from stellar evolutionary models.
Our results show unambiguously that Leo I experienced a major increase
of its star formation rate from about 6 Gyr ago to 2 Gyr ago.
Some prior star formation possibly ocurred in another discrete episode of
enhanced activity lasting 2-3 Gyr.
Finally, a low level of star formation continued until 500-200 Myr ago.
Leo I presents an enigmatic system with unique characteristics among
Local Group galaxies.
From its morphology and similarity to other dSph in terms of its lack of
detectable quantities of H I (Knapp et al. 1978), it
would be considered a dSph galaxy.
With the exception of Leo I, an old stellar population traced by a
horizontal-branch (HB) has been clearly observed in all the other dSph galaxies
satellites of the Milky Way, regardless of their subsequent star formation
In this respect Leo I is an unusual galaxy, displaying a well-populated red
clump indicative of a large fraction of intermediate-age stars, but no evident
We are analyzing very deep F555W (V) and F814W (I)
data using model color-magnitude diagrams (CMDs) to obtain the SFH
of Leo I.
Because the data are deep enough to reach the magnitude expected for the oldest
turnoffs, we are able to exploit our analysis method to the maximum of its
As a result, we are obtaining a SFH with unprecedented detail, even for
the earliest epoch of Leo I's evolution.
2. The data
WFPC2 HST V (F555W) and
I (F814W) data in one 2.6' × 2.6' field in Leo I
were obtained on March 5, 1994.
At the time of the observations the camera was still operating at the higher
temperature of -77.0°C.
Three deep exposures with both F555W (V) and F814W (I) filters
(1900 s and 1600 s, respectively) were taken.
To ensure that the brightest stars were not saturated, one shallow exposure
with each filter (350 s in F555W and 300 s in F814W) was also
Photometry of the stars in Leo I was measured using the set of
DAOPHOT II/ALLFRAME programs developed by Stetson (1994), and the final
photometry in the Johnson-Cousins system was calibrated using the ground-based
photometry obtained by Lee et al. (1993).
In Fig. 1 we present the
[(V-I)0, MI] CMD for Leo I based on
the three wide field chips.
It contains a total of 28 000 stars with small photometric errors
(σ ≤ 0.2, chi < 1.6 and -0.5 ≤ sharp ≤ 0.5).
For a more complete description of the data reduction and a discussion of the
features present in the CMD, see Gallart et al. (1998a; G98a hereinafter).
3. Computing the star formation history
Our goal is to reconstruct the SFH of Leo I from the information in
The method we are using is based on the comparison of a large number of model
CMDs, computed assuming different SFHs, with the observed CMD.
For our purposes, we consider the SFH to be a function of time defined by
the star formation rate, ψ(t), the chemical enrichment law,
Z(t), and the initial mass function (IMF).
We are currently analyzing a large number of models incorporating different
In each case, a given Z(t) compatible with the data and a given
IMF are assumed; then, the ψ(t) that produces the best agreement
with the data is searched for.
The details of this work and the definitive results will be presented
in Gallart et al. (1998b; G98b hereinafter).
Here, we present the results obtained for ψ(t) using a
representative set of models characterized by a given pair of IMF and
The model CMDs are calculated using a recent version of our synthetic CMD code,
and performing a simulation of observational effects in a way similar to that
described in Gallart et al. (1996a,b) and Aparicio et al. (1997a,b).
To compare the model CMDs with the observed CMD, we have followed an approach
similar to that of Aparicio et al. (1997b), who analyzed the dwarf galaxy
Here, only one model CMD, with a constant star formation rate as a function of
time has been computed for each pair of Z(t) and IMF.
Then, this CMD has been divided into a number of age intervals to obtain what
we will call partial models, ψi, which are simply
a set of step functions with the same star formation rate per unit of time
extended to a given period of time.
These models are combined to produce what we call global models, which
are used to search for the ψ(t) best representing the data by
comparing them with the observed CMD via star counts in several regions of
the CMD (see Fig. 2).
Global models have arbitrary ψ(t) functions produced by combining
fractions of stars of each partial model.
They do not need to be explicitly computed.
Once the number of stars with which each partial model populates each of
the regions defined in the CMD is known, the number of stars that populate
that region for a given global model can be directly obtained as a linear
combination of the form:
where Ng,j is the number of stars in region j for
the global model, Ni,j is the same number corresponding to
partial model i, ai are the coefficients defining
the global model and m is the number of partial models used.
The Ng,j values are all that is needed to compare the global
models with observations.
An arbitrarily large number of global models can be calculated by just changing
for a given set of k values of ai, the number of
global models calculated is km.
The total star formation rate corresponding to each global model is then:
where ψi is the value of the star formation rate
corresponding to the partial model i and l results from
normalization to the observed data.
The comparison between model and observed CMDs is done through star counts in
a number of CMD regions (see Fig. 2)
chosen to sample stars of different ages or in specific stellar evolutionary
We calculate the χ2 statistic of the star distribution in
the r regions of the observed CMD and each global model as
the indicator of the goodness of fit.
[Click here to see Fig. 1 and 2!]
4. The particular case of Leo I. Comparison of the models
with the data
A model CMD with a constant star formation rate from 15 Gyr ago to
the present, from which the partial models were obtained, was computed using
the Padova stellar evolutionary models (Bertelli et al. 1994), the IMF derived
by Kroupa et al. (1993) and the simple case of constant
Z(t) = 0.0004 (see G98a for a discussion of this case).
We divided the model CMD into 9 partial models delineated by the age steps
15.0, 10.0, 8.0, 6.3, 4.0, 2.0, 1.0, 0.5, 0.2 and 0.01 Gyr ago and
employed a set of 10 ai coefficients.
We obtained the SFH shown in Fig. 3
(dashed thin line) as the average of approximately 3000 models with the lowest
values for χ2.
In a second step, we refined our solution by again using 10 values for each
of the ai coefficients, but choosing them this time around
each average ai coefficient obtained in the first step.
This improved the resolution with which the values of ψ(t) could be
estimated for each time interval.
The result is shown in Fig. 3
(solid thick line), where about 3000 models (with lower values of
χ2) have again been averaged.
In both cases, the error bars represent the σ of the ai
values averaged to obtain ψ(t) for the time interval corresponding
to the partial model.
Assuming the SFH in Fig. 3, the
number of stars in each box are reproduced within a maximum error of 20%
except for the box containing the HB and the one right below it
(Fig. 2), for which the error is
The number of sub-giant stars around 1 Gyr in age is only one-fifth the
number needed to reproduce the 48 stars observed in the HB area.
This is due to the fact that ≅15 Gyr old stars with Z = 0.0004
do not produce a blue HB in the Padova models, and indicates that a lower
metallicity is required for the old stars.
When a lower metallicity is assumed for them, a ψ(t) within a factor
of two of the one in Fig. 3 at the
oldest epoch produces enough stars (G98b) in the HB area.
Fig. 4 shows the model CMD computed
with the SFH represented in Fig. 3.
It can be compared with the observed CMD in
The overall agreement is remarkably good, and some of the differences may be
due to known weaknesses in the models discussed in G98a.
These effects have been taken into account when comparing the models with
[Click here to see Fig. 3 and 4!]
5. Conclusion. The SFH of Leo I
Fig. 3 (solid thick line) shows
the best solution for the SFH of Leo I obtained under the assumption of
a constant Z(t) = 0.0004 and the Kroupa et al. (1993) IMF.
The main characteristics of the best solution obtained for ψ(t) are:
- A major increase in ψ(t) took place around 6 Gyr ago
(nearly an order of magnitude higher than the immediately preceding
epoch and about a factor of 5 higher than the average ψ(t)
from 15-6 Gyr ago), and lasted until about 2 Gyr ago, when
ψ(t) decreased again.
- Another epoch of increased ψ(t) seems to have occurred from
about 11 to 8 Gyr ago, with very little or no star formation
immediately before and after.
- Star formation appears to have continued at a low rate until about
200-500 million years ago.
This is necessary to account for the brightest stars in the main
sequence area, and the bright yellow stars at
[(V-I)0, MI] = (0.25, -2.0).
We are analyzing a larger number of scenarios that incorporate different
assumptions for the IMF and Z(t).
We expect to be able to constrain these using the same kind of analysis
described here and introducing additional considerations from the best values
of χ2 in the different scenarios.
Our preliminary results indicate that the general trend of the SFH is
maintained even if the IMF and/or the chemical enrichment law are changed
within reasonable limits.
For a more detailed discussion of the method and an in-depth analysis of
the Leo I SFH, see G98b.
We thank A. Sandage, D. Martínez-Delgado, Paul Hodge,
M. Mateo, P. Stetson, N. Suntzeff and I. Thompson for very
- Aparicio A., Gallart C., Bertelli G., 1997a, AJ 114, 669
- Aparicio A., Gallart C., Bertelli G., 1997b, AJ 114, 680
- Bertelli G., Bressan A., Chiosi C., Fagotto F., Nasi E., 1994,
A&AS 106, 275
- Gallart C., Aparicio A., Bertelli G., Chiosi C., 1996a, AJ 112, 1950
- Gallart C., Aparicio A., Bertelli G., Chiosi C., 1996b, AJ 112, 2596
- Gallart C., et al., 1998a, submitted to ApJ (G98a)
- Gallart C., Aparicio A., Freedman W.L., Bertelli G., Chiosi C., 1998b,
in prep. (G98b)
- Knapp G.R., Kerr F.J., Bowers P.F., 1978, AJ 83, 228
- Kroupa P., Tout C.A., Gilmore G., 1993, MNRAS 262, 545
- Lee M.G., Freedman W.L., Mateo M., Thompson I., Roth M., Ruiz M.-T.,
1993, AJ 106, 1420
- Stetson P.B., 1994, PASP 106, 250
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|First version: ||15th||August,||1998
|Last update: ||27th||September,||1998
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