Using evolution strategies for automatic extraction of parameters for stellar population synthesis of galaxy spectra from sdss

ABSTRACT

In this work we employ Evolution Strategies (ES) to automatically extract a set of physical parameters (ages, metallicities, reddening and contributions) from a sample of galaxy spectra taken from Sloan Digital Sky Survey (SDSS) for stellar populations studies. We pose this parameter extraction as an optimization problem and then solve it using ES. The idea is to reconstruct each galactic spectrum from the sample by means of a linear combination of three different theoretical models of stellar population synthesis. This combination produces a model spectrum that is compared with the original spectrum using a difference function. The goal is to find a model that minimizes this difference, using ES as the algorithm to explore the parameter space.

REFERENCES

• 1: R. C. Fernandes, A. Mateus, L. Sodré, G. Stasin'ska, and J. Gomes. Semi-empirical analysis of sloan digital sky survey galaxies - i. spectral synthesis method. Monthly Notices of the Royal Astronomical Society, 358(2):363--378, April 2005

INDEX TERMS

Primary Classification:
  J. Computer Applications
  J.2 PHYSICAL SCIENCES AND ENGINEERING
      Subjects: Astronomy

Additional Classification:
  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization
          Subjects: Global optimization

General Terms:
Algorithms, Experimentation, Performance

Keywords:
fitting of spectra, global optimization