MilkyWay@home

MilkyWay@home is a volunteer computing project dedicated to building high-precision three-dimensional models of the Milky Way galaxy. By analyzing the positions, velocities, and chemical compositions of stars across the sky, the project aims to reconstruct the gravitational potential of our galaxy — and by extension, map the distribution of dark matter, the mysterious invisible substance that makes up roughly 85% of all matter in the universe.

Run by the Department of Computer Science at Rensselaer Polytechnic Institute (RPI), the project focuses on tidal stellar streams — elongated structures formed when smaller satellite galaxies or star clusters are gravitationally disrupted and stretched out by the Milky Way's tidal forces. These streams act as sensitive tracers of the galaxy's gravitational field: their shapes, lengths, and density profiles encode information about the total mass distribution, including the dark matter halo that envelops the visible galaxy.

The project uses data from the Sloan Digital Sky Survey (SDSS) and applies optimization algorithms (including genetic algorithms and GPU-accelerated N-body simulations) to fit models of stellar stream formation against observed data. Each volunteer's computer tests different parameter combinations for the galactic potential, the orbit of the disrupted satellite, and the properties of the dark matter halo.

MilkyWay@home is one of the earliest volunteer computing projects to make extensive use of GPU acceleration, leveraging the massively parallel architecture of graphics cards to run N-body gravitational simulations orders of magnitude faster than CPUs alone. Results from the project have been published in The Astrophysical Journal and have contributed to our understanding of galactic structure and the nature of dark matter.