Metaheuristics for modelling low-resolution galaxy spectral energy distribution

Abstract

Astrophysics is entering in a new epoch characterized by a huge increment of the volume of data accessible. Consequently, scientists are modifying their traditional data analysis and simulation procedures to adapt them to this circumstance. As part of this increment, it should be underlined the number of high-quality galaxy spectra produced by the new instruments. Galaxy spectra are important in Astrophysics since they encode essential information, as the age and the metallicity, of the constituent stellar populations. These galaxy spectra can be modelled based on Simple Stellar Population. This procedure allows understanding the present state of the galaxy, and also inferring the evolution of the whole stellar system. However, this modelling requires to combine adequately more than one Simple Stellar Population to reproduce the galaxy spectral energy distribution. In order to deal with this modelling process, metaheuristics techniques are suitable, and for this reason, in this work diverse metaheuristics are implemented and tested to model the low resolution Spectral Energy Distribution of the M110 galaxy. The final purpose of this work is to pave the way to create and deliver a code based on metaheuristics techniques able to fit the Spectral Energy Distribution of a galaxy as a combination of predefined Simple Stellar Populations Spectra. © 2014 Springer International Publishing.