Thesis Topic: Near-IR view of the Milky Way bulge


Thesis Supervisors: Marina Rejkuba




Over the past couple of decades the studies of resolved stellar populations have reached the maturity and became an established tool for the studies of star formation histories in nearby galaxies. They are used to determine the key physical parameters of galaxies, like age and the star formation history, the chemical composition and chemical enrichment history, the stellar initial mass function and the dynamical history of the system. The presence and frequency of different variable star populations within a galaxy provide additional clues and constraints to these parameters.

This thesis project is based on the multi-epoch near-IR observations of the Galactic bulge and the inner regions of the Milky Way coming from the public survey project VVV (Vista Variables in the Via Lactea), one of the six approved Public Surveys carried out with the VISTA survey telescope at Cerro Paranal in Chile. In its first two observing seasons (2010-2011) VVV has mapped ~300 sq.deg area in the Milky Way bulge and ~220 sq.deg in the adjacent disk in ZYJHKs broad-band filters, making the deepest and highest resolution map of the central parts of the Galaxy. Since then VVV continues with the multi-epoch monitoring of its 196 tiles in the bulge and 152 in the disk that will continue in 2015 and beyond. The survey goals and observing strategy are summarized in a paper by Minniti et al. (2010), and the first data release described in the DR1 paper (Saito et al. 2012). This rich dataset has already been used in several master and PhD theses and for example within the ESO/IMPRS PhD thesis Oscar A. Gonzalez used the VVV data to produce the highest resolution extinction map and a first global photometric metallicity map of the Milky Way bulge. The principal aim of the VVV project, finding variable stars (in particular RR Lyrae) and using their properties to derive the 3D structure of inner Galaxy and better understand its formation and evolution are the next challenges that will be addressed through this PhD project.

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