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Register a new userStellar population synthesis diagnostics
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Y.K. Ng
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A quantitative method is presented to compare observed and synthetic colour-magnitude diagrams (CMDs). The method is based on a chi^2 merit function for a point (c_i,m_i) in the observed CMD, which has a corresponding point in the simulated CMD within n*sigma(c_i,m_i) of the error ellipse. The chi^2 merit function is then combined with the Poisson merit function of the points for which no corresponding point was found within the n*sigma(c_i,m_i) error ellipse boundary. Monte-Carlo simulations are presented to demonstrate the diagnostics obtained from the combined (chi^2, Poisson) merit function through variation of different parameters in the stellar population synthesis tool. The simulations indicate that the merit function can potentially be used to reveal information about the initial mass function. Information about the star formation history of single stellar aggregates, such as open or globular clusters and possibly dwarf galaxies with a dominating stellar population, might not be reliable if one is dealing with a relatively small age range.
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We review the main stellar features observed in starburst spectra from the UV to the near-IR and their use as fundamental tools to determine the properties of stellar populations from integrated spectra. The origin and dependence of the features on stellar properties are discussed, and we summarise existing modeling techniques used for quantitative analysis. Recent results from studies based on UV, optical and near-IR observations of starbursts and active galaxies are summarised. Finally, we briefly discuss combined starburst + photoionisation models including also observations from nebular emission lines. The present review is complementary to the recent summary by Schaerer (2000) (http://xxx.lpthe.jussieu.fr/abs/astro-ph/0007307) discussing more extensively nebular analysis of starbursts and related objects.
We want to develop spectral diagnostics of stellar populations in the near-infrared (NIR), for unresolved stellar populations. We created a semi-empirical population model and we compare the model output with the observed spectra of a sample of elliptical and bulge-dominated galaxies that have reliable Lick-indices from literature to test if the correlation between Mg2 and CO 1.62 micron remains valid in galaxies and to calibrate it as an abundance indicator. We find that (i) there are no significant correlations between any NIR feature and the optical Mg2; (ii) the CaI, NaI and CO trace the alpha-enhancement; and (iii) the NIR absorption features are not influenced by the galaxys age.
Populations of massive stars are directly reflective of the physics of stellar evolution. Counting subtypes of massive stars and ratios of massive stars in different evolutionary states have been used ubiquitously as diagnostics of age and metallicity effects. While the binary fraction of massive stars is significant, inferences are often based upon models incorporating only single-star evolution. In this work, we utilize custom synthetic stellar populations from the Binary Population and Stellar Synthesis (BPASS) code to determine the effect of stellar binaries on number count ratios of different evolutionary stages in both young massive clusters and galaxies with massive stellar populations. We find that many ratios are degenerate in metallicity, age, and/or binary fraction. We develop diagnostic plots using these stellar count ratios to help break this degeneracy, and use these plots to compare our predictions to observed data in the Milky Way and the Local Group. These data suggest a possible correlation between the massive star binary fraction and metallicity. We also examine the robustness of our predictions in samples with varying levels of completeness. We find including binaries and imposing a completeness limit can both introduce $gtrsim0.1$ dex changes in inferred ages. Our results highlight the impact that binary evolution channels can have on the massive star population.
We present EzGal, a flexible python program designed to easily generate observable parameters (magnitudes, colors, mass-to-light ratios) for any stellar population synthesis (SPS) model. As has been demonstrated by various authors, the choice of input SPS models can be a significant source of systematic uncertainty. A key strength of EzGal is that it enables simple, direct comparison of different models sets. EzGal is also capable of generating composite stellar population models (CSPs) and can interpolate between metallicities for a given model set. We have created a web interface to run EzGal and generate observables for a variety of star formation histories and model sets. We make many commonly used SPS models available from this interface; the BC03 models, an updated version of these models, the Maraston models, the BaSTI models, and finally the FSPS models. We use EzGal to compare magnitude predictions for the model sets as a function of wavelength, age, metallicity, and star formation history. We recover the well-known result that the models agree best in the optical for old, solar metallicity models, with differences at the ~0.1 magnitude level. The most problematic regime for SPS modeling is for young ages (<2 Gyrs) and long wavelengths (lambda >7500 Angstroms) where scatter between models can vary from 0.3 mags (Sloan i) to 0.7 mags (Ks). We find that these differences are best understood as general uncertainties in SPS modeling. Finally we explore a more physically motivated example by generating CSPs with a star formation history matching the global star formation history of the universe. We demonstrate that the wavelength and age dependence of SPS model uncertainty translates into a redshift dependent model uncertainty, highlighting the importance of a quantitative understanding of model differences when comparing observations to models as a function of redshift.
Comparison with artificial galaxy models is essential for translating the incomplete and low signal-to-noise data we can obtain on astrophysical stellar populations to physical interpretations which describe their composition, physical properties, histories and internal conditions. In particular, this is true for distant galaxies, whose unresolved light embeds clues to their formation and evolution as well as their impact on their wider environs. Stellar population synthesis models are now used as the foundation of analysis at all redshifts, but are not without their problems. Here we review the use of stellar population synthesis models, with a focus on applications in the distant Universe.
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