Milkyway@home is a research project that uses Internet-connected computers to do research in modeling and determining the evolution of the Milkyway galaxy. You can participate by downloading the BOINC software and attaching your computer to the project.
MilkyWay@home project URL; http://milkyway.cs.rpi.edu/milkyway/
MilkyWay@home is based at the Rensselaer Computer Science Department in New York. This particular project is being developed to better understand the power of volunteer computing resources.
The astronomy application attempts to discover various structures existing in the Milky Way galaxy and their spatial distribution. This requires a probabilistic algorithm for locating geometric objects in spatial databases. The data being analyzed is from the Sloan Digital Sky Survay, which has recently released 10 terabytes of images and spectra in online catalogs.
The observed density of stars is drawn from a mixture distribution parameterized by the fraction of local sub-structure stars in the data compared to a smooth global background population, the parameters that specify the position and distribution of the sub structure, and the parameters of the smooth background. Specifically this is a probability density function that calculates the chance of obtaining the observed star distribution after repeated independent sampling from the total set of stars.
Such probabilistic framework gives a natural sampling algorithm for separating sub-structure from background.By identifying and quantifying the stellar substructure and the smooth portion of the Milky Way’s spheroid, it will be possible to test models for the formation of our galaxy, and by example the process of galaxy formation in general. In particular, we would like to know how many merger events contributed to the build up of the spheroid, what the sizes of the merged galaxies were, and at what time in the history of the Milky Way the merger events occurred. Models for tidal disruption of merger events that build up the spheroid of the Milky Way can be matched with individual, quantified spatial substructures to constrain the Galaxy’s gravitational potential. Since the gravitational potential is dominated by dark matter, this technique will also teach us about the spatial distribution of dark matter in the Milky Way.
Video about the evolution of the Milky Way Galaxy
Carl Sagan video about Galaxys and the Milky Way
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