Binary-Star Spectral Fitting Based on Strategy Improved Genetic Algorithm

The essence of the binary-star spectral fitting is to search the parameter space corresponding to the comparison of observed and theoretical spectra, via techniques such as least square. Rapid and accurate fitting of spectra is very important for studying a huge number of galaxies. As a result of the complexities in extensive calculation for spectral fitting and its limited efficiency, the strategic improved genetic algorithm is used for binary-star spectral fitting by this paper, and the comparison to BS2fit algorithm and traditional genetic algorithm is also shown. The experimental results show that the improved genetic algorithm can increase the spectral fitting speed by 43.5% on average, which can possibly promote the application of stellar population synthesis method in astronomical researches obviously.