A Probabilistic Formulation for Stellar Population Synthesis

Mathematics – Logic

Scientific paper

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Stellar Populations, Galaxies

Scientific paper

Probability theory is used to provide a mathematical approach for the problem of synthesizing spectral properties of galaxies, using a base of simple stellar populations spanning a range of ages and metallicities. This technique, provides estimates for the population vector X, containing the contributions of different base elements to the integrated spectrum of a galaxy, as well as the extinction A_V. The estimates are given as probability distributions, allowing a quantitative understanding of the uncertainties involved. We analyze how well the synthesis procedure recovers the chemical enrichment and star formation histories as a function of (1) the observational errors; and (2) the set of observables used. We tested the ability of the sampling scheme to map the parameter space by means of extensive simulations and found that only for extremely low errors (S/N> 300) all 12 base components can be recovered accurately. The age-binned distribution, however, is well recovered even for S/N ratios as low as 30. We therefore conclude that the base reliably recovers the star formation history but it is not suitable for chemical evolution studies. As previous studies indicated, this difficulty is rooted on the internal structure of the base. We also found that synthesizing equivalent widths and colors produces better results than synthesizing only the equivalent widths, despite the inclusion of A_V as an extra parameter. As an application of the method we apply it to 24 of 55 galaxies observed by Kennicutt (1992). We also investigate the connection between the stellar populations and morphological and spectral types, finding an excellent overall consistency between these different types of information. Overall, we find that the statistical degeneracy, induced by the presence of errors in the input data, is a more serious problem than the algebraic degeneracy which happens when one synthesizes more parameters than observables.

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