Statistics – Computation
Scientific paper
Jan 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aas...21523104h&link_type=abstract
American Astronomical Society, AAS Meeting #215, #231.04; Bulletin of the American Astronomical Society, Vol. 42, p.595
Statistics
Computation
Scientific paper
Ongoing and future large scale structure surveys targeted at the investigation of dark energy will exploit the nonlinear regime of structure formation. In order to take full advantage of the newly available information from this regime and to extract cosmological constraints, very accurate theoretical predictions are needed. Such predictions can currently only be obtained from precision high-performance simulations. The very high computational cost of these simulations is a major obstacle to obtaining predictions in the nonlinear regime, while scanning over cosmological parameters. In this talk I will discuss the "Cosmic Calibration Framework", a statistical framework developed by us recently to extract cosmological information from a restricted set of high-precision simulations and observations. The framework combines sophisticated simulation design methods with Gaussian Process models to create precision emulators. These emulators can then be used to replace expensive simulators and to accurately determine cosmological parameters from observations.
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