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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.
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
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 ellip
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 metallicit
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 inpu
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, hi