Stellar Populations as Building Blocks of Galaxies
Proceedings IAU Symposium No. 241, 2007
A. Vazdekis et alr., eds.
c© 2007 International Astronomical Union
DOI: 00.0000/X000000000000000X
Modelling the Near-IR Spectra of Red
Supergiant-dominated Populations
Ariane Lançon1, Jay S. Gallagher2, Richard de Grijs3,
Peter Hauschildt4, Djazia Ladjal5, Mustapha Mouhcine6,
Linda J. Smith7, Peter R. Wood8, Natascha Förster Schreiber9
1Observatoire de Strasbourg (UMR 7550), 11 rue de l’Université, 67000 Strasbourg, France
email: lancon@astro.u-strasbg.fr
2Dept. of Astronomy, 5534 Sterling, University of Wisconsin, Madison, WI 53706, USA
3Dept. of Physics & Astronomy, University of Sheffield, Hicks Building, Honusfield Rd.,
Sheffield S3 7RH, UK
4Hamburger Sternwarte, Gojenbergsweg 112, 21029 Hamburg, Germany
5Institute of Astronomy, Katholieke Universiteit, Celestijnenlaan 200B, 3001 Leuven, Belgium
6Astrophysics Research Institute, Liverpool John Moores University, Twelve Quays House,
Egerton Wharf, Birkenhead, CH41 1LD, UK
7Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
8RSAA, Mt Stromlo Observatory, Cotter Road, Weston Creek, ACT 2611, Australia
9MPI für Extraterrestrische Physik, Giessenbachstrasse, 85741 Garching, Germany
Abstract. We report on recent progress in the modelling of the near-IR spectra of young stellar
populations, i.e. populations in which red supergiants (RSGs) are dominant. First, we discuss
the determination of fundamental parameters of RSGs from Phoenix model fits to their near-IR
spectra; RSG-specific surface abundances are accounted for and effects of the microturbulence
parameter are explored. New population synthesis predictions are then described and, as an
example, it is shown that the spectra of young star clusters in M82 can be reproduced very well
from 0.5 to 2.4µm. We warn of remaining uncertainties in cluster ages.
Keywords. galaxies: stellar content, galaxies: starburst, galaxies: star clusters, galaxies: indi-
vidual (M82), infrared: galaxies, infrared: stars, stars: supergiants
1. Introduction
Red supergiant stars (RSGs) provide most of the near-IR light emitted by young stellar
populations, such as those in starburst galaxies. As star forming environments tend to
be dusty, rest-frame optical analyses are incomplete (highly obscured populations are
missed) and it is crucial to improve our understanding of spectra at longer wavelengths. In
the past, the near-IR analysis of young stellar populations has often been restricted to the
determination of the average properties of the dominant stars, such as their spectral types
or abundances. The subsequent interpretation of these results in terms of precise stellar
population ages and star formation histories remains an enormous challenge, as it requires
(i) a good understanding of the near-IR spectra of individual RSGs and (ii) adequate
stellar evolution tracks. We have started a programme that aims at providing state of
the art predictions for the emission of RSG-dominated populations and at characterizing
remaining uncertainties. Currently, the project focuses on wavelengths between 0.81 and
2.4µm and spectral resolutions of order λ/δλ = 103.
http://arxiv.org/abs/0704.0401v1
2 A. Lançon et al.
2. Empirical and synthetic spectra of red supergiants
In principle, synthetic stellar spectra are more practical for the prediction of galaxy
spectra than empirical ones, because theory allows us to sample parameter space without
biases. Lançon et al. (2007) show that modern theoretical spectra can reproduce the near-
IR (+optical) emission of giant stars well down to effective temperatures Teff ≃ 3400K,
but that they are not yet satisfactory at lower temperatures and higher luminosities. They
used new Phoenix models to compute spectra at the necessary resolution (0.1 Å before
smoothing), with solar abundances and with the RSG-specific abundances obtained as
the result of internal mixing along stellar evolution tracks; the models include some 109
individual molecular and atomic lines, assume spherical symmetry, and allow dust to form
if conditions are fulfilled. Model limitations include the assumptions of local thermal
equilibrium (LTE) and of hydrostatic equilibrium. A sample of 101 empirical spectra
covering wavelengths between 0.51, 0.81 or 0.90µm and 2.4µm was used for comparison
(Lançon & Wood 2000, Lançon et al. in preparation). The data were acquired with
CASPIR on the 2.3m ANU Telescope at Siding Spring and with SpeX at IRTF, Hawaii.
Below Teff ∼ 3400K, uncertain input line lists are a problem in the models (especially
for molecular bands around 1µm). At high luminosity (luminosity class Ia and Iab), the
main difficulty is to reproduce simultaneously extremely deep CN bands and the relative
strengths of the CO bandheads around 1.7µm and at 2.3µm. RSG-specific abundances
improve fits to the CN bands. Exploratory calculations show that values near 10 km/s for
the “microturbulence” (a 1D-model parameter that hides poorly understood 3D physical
phenomena) may be able to solve both problems (Fig. 1, top left). The calculation of a
new grid has been launched to explore this further. In the mean time, the study shows
that the population synthesis community still has to rely on empirical spectra for RSGs,
and it warns that the lack of satisfactory stellar models implies large uncertainties on
the derived fundamental parameters of the observed stars.
3. Population synthesis using averaged stellar spectra
In order to compute spectra of synthetic populations, we have constructed three se-
quences of average empirical spectra, corresponding to luminosity classes Ia, Iab and
Ib/II. Each subset was sorted into bins according to the estimated Teff , the spectra were
dereddened (an estimate of the reddening is provided by the model fits), and averages
were computed. The sequences shown in Fig. 1 (top right) account for varying micro-
turbulence in a preliminary way, based on the limited number of high microturbulence
models available to us at the time of this writing. We chose to flag any star with an initial
mass above 7M⊙ as a supergiant, which implies that the new spectra affect predictions
up to the age of about 75Myr (Fig. 1, middle left). We note that predictions vary signif-
icantly depending on the adopted evolutionary tracks; different authors predict different
red supergiant lifetimes, and main sequence rotation affects both the surface abundances
and the final red (and blue) supergiant numbers.
4. Star clusters in M82
The synthetic spectra of single stellar populations (SSPs) at solar metallicity are com-
pared with those of young star clusters in starbursts, such as M82-L and M82-F (Smith
& Gallagher 1999). The selected clusters are massive (well above 105M⊙), i.e. stochastic
effects due to an underpopulated RSG-branch are avoided. A few have well determined
optical ages (based on standard non-rotating evolutionary tracks). Figure 1 (middle right
Modelling Red Supergiant Populations 3
 3000 4000 5000
Age = 18 Myr
Av = 1
0.5 1.0 1.5 2.0 2.5
Age=18
Av=3.7
Rv=2.4
chi2=1.58934
1.0 1.5 2.0
Wavelength (micron)
12 CO
[FeII]
1.55 1.60 1.65 1.70
Wavelength (micron)
bad pixels
2.1 2.2 2.3
Figure 1. Top left: Spectrum of an M0Ia RSG compared with models with vmicroturb=2km/s
(top: 4200K, log(g)=-1, AV =4.4) and with vmicroturb=10 km/s (bottom: 4500K, log(g)=0,
AV =4.7; note the improved CN at 1.1µm and CO around 1.6 and 2.3µm). Top right: Param-
eters assigned to the new sequences of average spectra, superimposed on the solar metallicity
tracks of Bressan et al. (1993). Middle left: Comparison of a new SSP spectrum (black) with
the standard predictions of Pegase.2 (differences are largest between 10 and 20Myr). Middle
right: Best near-IR fit to the spectrum of cluster M82-L. The extinction law of Cardelli et al.
(1989) with RV =2.4 allows us to also reproduce the optical spectrum (from Smith & Gallagher
1999). The error spectrum and the χ2 weighting function are shown. Bottom: Zoom-ins of the
H and K windows.
4 A. Lançon et al.
and bottom) shows cluster L, the cluster observed with SpeX with the best signal-to-
noise ratio: an excellent fit is obtained over the whole available range in wavelength.
Such results make the new models valuable tools for purposes such as weak emission line
measurements. The χ2-test restricted to near-IR wavelengths not affected by strong tel-
luric absorption shows that age is formally determined to an accuracy of about ±10Myr.
Because of strong reddening, the optical age of cluster L cannot be determined as well
as that of cluster F: 50-70Myr (Gallagher & Smith 2001, McCrady et al. 2005, Bastian
et al. 2007). For F, our current models provide a near-IR age range of 32 to 46Myr.
This small but nevertheless significant disagreement calls for several comments. (i) Be-
fore accounting for luminosity-dependent microturbulence, we found a near-IR age of 10
to 20Myr; we hope that our next generation of synthetic stellar spectra will significantly
reduce uncertainties originating in uncertain fundamental parameters of stars. (ii) The
spectrum used for optical age-dating and our near-IR spectrum have different slopes in
the region of overlap. This suggests slightly different positions were observed: the ob-
scuration across M82-F is not at all uniform. In addition, a younger cluster located at
very small projected distance might contaminate the near-IR data. (iii) Modified stellar
tracks (e.g. including rotation) might affect optical ages as well as near-IR ones.
5. Conclusions
The spectra of young stellar populations at solar metallicity, observed at R∼ 103, can
now be modelled well from the optical through the near-IR. Nevertheless, ages based on
near-IR spectra remain severely affected by uncertainties. They are due mainly to system-
atic errors, which further work needs to characterize and reduce. Errors are associated on
one hand with the fundamental parameters of red supergiant stars (theoretical spectra,
microturbulence, surface abundances of C, N and O, non-LTE, variability, winds, giant-
supergiant transition), and on the other with evolutionary tracks (convection, opacities,
rotation, binarity, effects of a dense environment). We expect rapid progress in stellar at-
mosphere models to provide us with tools to test stellar tracks further. Complete optical
and near-IR spectra of massive clusters such as those of M82 are useful test cases for the
identification and correction of systematic errors, but even they are not trivial to exploit
(due to inhomogeneous background populations and extinction, mass segregation, etc.).
References
Bastian, N., Konstantopoulos, I., Smith, L.J. & Gallagher, J.S. 2007, MNRAS in press
Cardelli, J.A., Clayton, G.C. & Mathis, J.S. 1989 ApJ 345, 245
Gallagher, J.S. & Smith, L.J. 1999 MNRAS 304, 540
Lançon, A. & Wood, P.R. 2000, A&AS 146, 217
Lançon, A., Hauschildt, P., Ladjal, D. & Mouhcine, M. 2007, A&A in press
McCrady, N., Graham, J.R. & Vacca, W.D. 2005 ApJ 621, 278
Smith, L. J. & Gallagher, J. S. 2001 MNRAS 326, 1027
Discussion
Gustafsson: Do the models with high microturbulence include turbulent pressure in a
consistent way?
Lançon (after discussion with P.H. and H. Lamers): No. But the microturbu-
lent velocities required to reproduce the spectra with 1D models are supersonic, which
suggests that the actual process is not microturbulence... Therefore it is unclear how to
relate this parameter of 1D models to pressure.
	Introduction
	Empirical and synthetic spectra of red supergiants
	Population synthesis using averaged stellar spectra
	Star clusters in M82
	Conclusions

  We report on recent progress in the modelling of the near-IR spectra of young
stellar populations, i.e. populations in which red supergiants (RSGs) are
dominant. First, we discuss the determination of fundamental parameters of RSGs
using fits to their near-IR spectra with new PHOENIX model spectra;
RSG-specific surface abundances are accounted for and effects of the
microturbulence parameter are explored. New population synthesis predictions
are then described and, as an example, it is shown that the spectra of young
star clusters in M82 can be reproduced very well from 0.5 to 2.4 micrometers.
We warn of remaining uncertainties in cluster ages.

Introduction
Red supergiant stars (RSGs) provide most of the near-IR light emitted by young stellar
populations, such as those in starburst galaxies. As star forming environments tend to
be dusty, rest-frame optical analyses are incomplete (highly obscured populations are
missed) and it is crucial to improve our understanding of spectra at longer wavelengths. In
the past, the near-IR analysis of young stellar populations has often been restricted to the
determination of the average properties of the dominant stars, such as their spectral types
or abundances. The subsequent interpretation of these results in terms of precise stellar
population ages and star formation histories remains an enormous challenge, as it requires
(i) a good understanding of the near-IR spectra of individual RSGs and (ii) adequate
stellar evolution tracks. We have started a programme that aims at providing state of
the art predictions for the emission of RSG-dominated populations and at characterizing
remaining uncertainties. Currently, the project focuses on wavelengths between 0.81 and
2.4µm and spectral resolutions of order λ/δλ = 103.
http://arxiv.org/abs/0704.0401v1
2 A. Lançon et al.
2. Empirical and synthetic spectra of red supergiants
In principle, synthetic stellar spectra are more practical for the prediction of galaxy
spectra than empirical ones, because theory allows us to sample parameter space without
biases. Lançon et al. (2007) show that modern theoretical spectra can reproduce the near-
IR (+optical) emission of giant stars well down to effective temperatures Teff ≃ 3400K,
but that they are not yet satisfactory at lower temperatures and higher luminosities. They
used new Phoenix models to compute spectra at the necessary resolution (0.1 Å before
smoothing), with solar abundances and with the RSG-specific abundances obtained as
the result of internal mixing along stellar evolution tracks; the models include some 109
individual molecular and atomic lines, assume spherical symmetry, and allow dust to form
if conditions are fulfilled. Model limitations include the assumptions of local thermal
equilibrium (LTE) and of hydrostatic equilibrium. A sample of 101 empirical spectra
covering wavelengths between 0.51, 0.81 or 0.90µm and 2.4µm was used for comparison
(Lançon & Wood 2000, Lançon et al. in preparation). The data were acquired with
CASPIR on the 2.3m ANU Telescope at Siding Spring and with SpeX at IRTF, Hawaii.
Below Teff ∼ 3400K, uncertain input line lists are a problem in the models (especially
for molecular bands around 1µm). At high luminosity (luminosity class Ia and Iab), the
main difficulty is to reproduce simultaneously extremely deep CN bands and the relative
strengths of the CO bandheads around 1.7µm and at 2.3µm. RSG-specific abundances
improve fits to the CN bands. Exploratory calculations show that values near 10 km/s for
the “microturbulence” (a 1D-model parameter that hides poorly understood 3D physical
phenomena) may be able to solve both problems (Fig. 1, top left). The calculation of a
new grid has been launched to explore this further. In the mean time, the study shows
that the population synthesis community still has to rely on empirical spectra for RSGs,
and it warns that the lack of satisfactory stellar models implies large uncertainties on
the derived fundamental parameters of the observed stars.
3. Population synthesis using averaged stellar spectra
In order to compute spectra of synthetic populations, we have constructed three se-
quences of average empirical spectra, corresponding to luminosity classes Ia, Iab and
Ib/II. Each subset was sorted into bins according to the estimated Teff , the spectra were
dereddened (an estimate of the reddening is provided by the model fits), and averages
were computed. The sequences shown in Fig. 1 (top right) account for varying micro-
turbulence in a preliminary way, based on the limited number of high microturbulence
models available to us at the time of this writing. We chose to flag any star with an initial
mass above 7M⊙ as a supergiant, which implies that the new spectra affect predictions
up to the age of about 75Myr (Fig. 1, middle left). We note that predictions vary signif-
icantly depending on the adopted evolutionary tracks; different authors predict different
red supergiant lifetimes, and main sequence rotation affects both the surface abundances
and the final red (and blue) supergiant numbers.
4. Star clusters in M82
The synthetic spectra of single stellar populations (SSPs) at solar metallicity are com-
pared with those of young star clusters in starbursts, such as M82-L and M82-F (Smith
& Gallagher 1999). The selected clusters are massive (well above 105M⊙), i.e. stochastic
effects due to an underpopulated RSG-branch are avoided. A few have well determined
optical ages (based on standard non-rotating evolutionary tracks). Figure 1 (middle right
Modelling Red Supergiant Populations 3
 3000 4000 5000
Age = 18 Myr
Av = 1
0.5 1.0 1.5 2.0 2.5
Age=18
Av=3.7
Rv=2.4
chi2=1.58934
1.0 1.5 2.0
Wavelength (micron)
12 CO
[FeII]
1.55 1.60 1.65 1.70
Wavelength (micron)
bad pixels
2.1 2.2 2.3
Figure 1. Top left: Spectrum of an M0Ia RSG compared with models with vmicroturb=2km/s
(top: 4200K, log(g)=-1, AV =4.4) and with vmicroturb=10 km/s (bottom: 4500K, log(g)=0,
AV =4.7; note the improved CN at 1.1µm and CO around 1.6 and 2.3µm). Top right: Param-
eters assigned to the new sequences of average spectra, superimposed on the solar metallicity
tracks of Bressan et al. (1993). Middle left: Comparison of a new SSP spectrum (black) with
the standard predictions of Pegase.2 (differences are largest between 10 and 20Myr). Middle
right: Best near-IR fit to the spectrum of cluster M82-L. The extinction law of Cardelli et al.
(1989) with RV =2.4 allows us to also reproduce the optical spectrum (from Smith & Gallagher
1999). The error spectrum and the χ2 weighting function are shown. Bottom: Zoom-ins of the
H and K windows.
4 A. Lançon et al.
and bottom) shows cluster L, the cluster observed with SpeX with the best signal-to-
noise ratio: an excellent fit is obtained over the whole available range in wavelength.
Such results make the new models valuable tools for purposes such as weak emission line
measurements. The χ2-test restricted to near-IR wavelengths not affected by strong tel-
luric absorption shows that age is formally determined to an accuracy of about ±10Myr.
Because of strong reddening, the optical age of cluster L cannot be determined as well
as that of cluster F: 50-70Myr (Gallagher & Smith 2001, McCrady et al. 2005, Bastian
et al. 2007). For F, our current models provide a near-IR age range of 32 to 46Myr.
This small but nevertheless significant disagreement calls for several comments. (i) Be-
fore accounting for luminosity-dependent microturbulence, we found a near-IR age of 10
to 20Myr; we hope that our next generation of synthetic stellar spectra will significantly
reduce uncertainties originating in uncertain fundamental parameters of stars. (ii) The
spectrum used for optical age-dating and our near-IR spectrum have different slopes in
the region of overlap. This suggests slightly different positions were observed: the ob-
scuration across M82-F is not at all uniform. In addition, a younger cluster located at
very small projected distance might contaminate the near-IR data. (iii) Modified stellar
tracks (e.g. including rotation) might affect optical ages as well as near-IR ones.
5. Conclusions
The spectra of young stellar populations at solar metallicity, observed at R∼ 103, can
now be modelled well from the optical through the near-IR. Nevertheless, ages based on
near-IR spectra remain severely affected by uncertainties. They are due mainly to system-
atic errors, which further work needs to characterize and reduce. Errors are associated on
one hand with the fundamental parameters of red supergiant stars (theoretical spectra,
microturbulence, surface abundances of C, N and O, non-LTE, variability, winds, giant-
supergiant transition), and on the other with evolutionary tracks (convection, opacities,
rotation, binarity, effects of a dense environment). We expect rapid progress in stellar at-
mosphere models to provide us with tools to test stellar tracks further. Complete optical
and near-IR spectra of massive clusters such as those of M82 are useful test cases for the
identification and correction of systematic errors, but even they are not trivial to exploit
(due to inhomogeneous background populations and extinction, mass segregation, etc.).
References
Bastian, N., Konstantopoulos, I., Smith, L.J. & Gallagher, J.S. 2007, MNRAS in press
Cardelli, J.A., Clayton, G.C. & Mathis, J.S. 1989 ApJ 345, 245
Gallagher, J.S. & Smith, L.J. 1999 MNRAS 304, 540
Lançon, A. & Wood, P.R. 2000, A&AS 146, 217
Lançon, A., Hauschildt, P., Ladjal, D. & Mouhcine, M. 2007, A&A in press
McCrady, N., Graham, J.R. & Vacca, W.D. 2005 ApJ 621, 278
Smith, L. J. & Gallagher, J. S. 2001 MNRAS 326, 1027
Discussion
Gustafsson: Do the models with high microturbulence include turbulent pressure in a
consistent way?
Lançon (after discussion with P.H. and H. Lamers): No. But the microturbu-
lent velocities required to reproduce the spectra with 1D models are supersonic, which
suggests that the actual process is not microturbulence... Therefore it is unclear how to
relate this parameter of 1D models to pressure.
	Introduction
	Empirical and synthetic spectra of red supergiants
	Population synthesis using averaged stellar spectra
	Star clusters in M82
	Conclusions
