Confidence in the models of stellar structure and evolution of massive stars depends on the accuracy with which their basic parameters can be measured. The key step consists in determining accurate distances. This parameter is also fundamental for the census of stellar populations in clusters and galaxies. In this context, massive stars are relevant, given their high luminosities. Several new open clusters, some with large mass, have been discovered in the Milky Way, most of them so far and so affected by reddening that traditional methods of measurement of distances can not be applied. For these cases, the most direct and most accurate way of determining distances is based on the study of eclipsing binary systems (Torres et al. 1991, Vaz et al. 1997 e Torres et al. 2010). Besides the distances, it is possible to determine all the system parameters (Massey et al. 2012). The study of OB type stars has allowed the direct measurement of distances to galaxies like Andromeda (Bonanos 2010). Nearby galaxies have been mapped in order to determine the spatial distribution of their stellar populations. In particular, it is possible to evaluate the thickness of the Large Magellanic Cloud. New deep surveys, such as the one being done with the VISTA telescope in the infrared (http://www.vista.ac.uk/index.html), covering the galactic plane, and the LSST telescope (http://www.lsst.org/lsst) in the optical (from 2016), which will cover the whole sky of the Southern Hemisphere, will open wide horizons in this field, through the discovery of hundreds of massive eclipsing binaries.This project was designed to study a particular eclipsing binary in Westerlund 1 (Wdeb) as an example, in order to test our procedures. This is driven by the fact that we have already more than 70 nights of photometry for Westerlund 1 in the OPD Observatory, 4 epochs of spectroscopy in Gemini telescope and 5 nights in Soar. The procedures tested in this case will be used to the similar objects expected to be discovered in the near future in other stellar clusters.
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