TESTING STELLAR POPULATION SYNTHESIS MODELS WITH SLOAN DIGITAL SKY SURVEY COLORS OF M31's GLOBULAR CLUSTERS
- Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States)
- School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ (United Kingdom)
- Eureka Scientific, Inc., 2452 Delmer Street, Suite 100, Oakland, CA 94602 (United States)
Accurate stellar population synthesis models are vital in understanding the properties and formation histories of galaxies. In order to calibrate and test the reliability of these models, they are often compared with observations of star clusters. However, relatively little work has compared these models in the ugriz filters, despite the recent widespread use of this filter set. In this paper, we compare the integrated colors of globular clusters in the Sloan Digital Sky Survey (SDSS) with those predicted from commonly used simple stellar population (SSP) models. The colors are based on SDSS observations of M31's clusters and provide the largest population of star clusters with accurate photometry available from the survey. As such, it is a unique sample with which to compare SSP models with SDSS observations. From this work, we identify a significant offset between the SSP models and the clusters' g - r colors, with the models predicting colors which are too red by g - r {approx} 0.1. This finding is consistent with previous observations of luminous red galaxies in the SDSS, which show a similar discrepancy. The identification of this offset in globular clusters suggests that it is very unlikely to be due to a minority population of young stars. The recently updated SSP model of Maraston and Stroembaeck better represents the observed g - r colors. This model is based on the empirical MILES stellar library, rather than theoretical libraries, suggesting an explanation for the g - r discrepancy.
- OSTI ID:
- 21580009
- Journal Information:
- Astrophysical Journal, Vol. 737, Issue 1; Other Information: DOI: 10.1088/0004-637X/737/1/5; ISSN 0004-637X
- Country of Publication:
- United States
- Language:
- English
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