Interpreting Galaxy Physical Properties Using Stellar Population Synthesis

TL;DR

This paper reviews how stellar population synthesis models are used to interpret galaxy properties from multi-wavelength data, emphasizing their reliability with limited photometry.

Contribution

It provides an in-depth analysis of SPS modeling techniques and assesses their effectiveness when only sparse photometric data is available.

Findings

SPS models can reliably infer galaxy properties with limited photometry.

Multi-wavelength data improves the accuracy of galaxy property estimation.

The thesis evaluates the limitations and robustness of SPS methods.

Abstract

Galaxy formation and evolution is one of the most active areas of research in astronomy. In recent times there have been several developments on the observational fronts particularly with the discovery of several relations between galaxy physical properties. The exact details of how they come about still remains to be understood. Such a development has been primarily possible due to a deluge of multi-wavelength data ranging from the ultra-violet (UV) to the radio, mainly due to wide field surveys e.g., the Sloan Digital Sky Survey (SDSS) in the optical. Meanwhile, simultaneous theoretical developments like a better understanding of dust attenuation and emission led to the development of techniques to extract information from the SEDs of galaxies, exploiting information from the far-ultraviolet (FUV) to the far-infrared (FIR). The substantial progress made in stellar evolution theory in the 1980s and 1990s paved the way for the latter approach to become the de facto standard in modeling the SEDs of galaxies. It became possible to synthesise a population of stars with a certain distribution and evolve it in time, keeping track of the emission from the stars, new star formation activity, gas enrichment with elements heavier than hydrogen and helium, and the absorption and re-emission from the interstellar dust. This technique, known as the stellar population synthesis (SPS), makes use of these multi-wavelength (UV to IR) data to generate a library of model SEDs. The observed SEDs can then be compared with such a library using statistical fitting techniques like the Bayesian statistics to infer the physical properties of galaxies. The main focus of this thesis is on the reliability of stellar population synthesis modelling when only limited photometry of a small number of wavelength bands is available. It is divided in two parts: elaborate understanding of SPS modelling (Part I) and...