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Fnord666 writes:

Researchers from the University of Zurich have simulated the formation of our entire Universe with a large supercomputer. A gigantic catalogue of about 25 billion virtual galaxies has been generated from 2 trillion digital particles. This catalogue is being used to calibrate the experiments on board the Euclid satellite, that will be launched in 2020 with the objective of investigating the nature of dark matter and dark energy.

Over a period of three years, a group of astrophysicists from the University of Zurich has developed and optimised a revolutionary code to describe with unprecedented accuracy the dynamics of dark matter and the formation of large-scale structures in the Universe. As Joachim Stadel, Douglas Potter and Romain Teyssier report in their recently published paper, the code (called PKDGRAV3) has been designed to use optimally the available memory and processing power of modern supercomputing architectures, such as the "Piz Daint" supercomputer of the Swiss National Computing Center (CSCS). The code was executed on this world-leading machine for only 80 hours, and generated a virtual universe of two trillion (i.e., two thousand billion or 2 x 10¹²) macro-particles representing the dark matter fluid, from which a catalogue of 25 billion virtual galaxies was extracted

Thanks to the high precision of their calculation, featuring a dark matter fluid evolving under its own gravity, the researchers have simulated the formation of small concentration of matter, called dark matter halos, in which we believe galaxies like the Milky Way form. The challenge of this simulation was to model galaxies as small as one tenth of the Milky Way, in a volume as large as our entire observable Universe. This was the requirement set by the European Euclid mission, whose main objective is to explore the dark side of the Universe.

Source: University of Zurich

Journal Reference:
Douglas Potter, Joachim Stadel, Romain Teyssier. PKDGRAV3: beyond trillion particle cosmological simulations for the next era of galaxy surveys. Computational Astrophysics and Cosmology, 2017; 4 (1) DOI: 10.1186/s40668-017-0021-1

Original Submission