The Coyote Universe II [electronic resource] : Cosmological Models and Precision Emulation of the Nonlinear Matter Power Spectrum
- Washington, D.C. : United States. Dept. of Energy, 2008.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Additional Creators:
- Los Alamos National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- The power spectrum of density fluctuations is a foundational source of cosmological information. Precision cosmological probes targeted primarily at investigations of dark energy require accurate theoretical determinations of the power spectrum in the nonlinear regime. To exploit the observational power of future cosmological surveys, accuracy demands on the theory are at the one percent level or better. Numerical simulations are currently the only way to produce sufficiently error-controlled predictions for the power spectrum. The very high computational cost of (precision) N-body simulations is a major obstacle to obtaining predictions in the nonlinear regime, while scanning over cosmological parameters. Near-future observations, however, are likely to provide a meaningful constraint only on constant dark energy equation of state 'wCDM' cosmologies. In this paper we demonstrate that a limited set of only 37 cosmological models -- the 'Coyote Universe' suite -- can be used to predict the nonlinear matter power spectrum at the required accuracy over a prior parameter range set by cosmic microwave background observations. This paper is the second in a series of three, with the final aim to provide a high-accuracy prediction scheme for the nonlinear matter power spectrum for wCDM cosmologies.
- Report Numbers:
- E 1.99:la-ur-08-07921
E 1.99: la-ur-08-7921
- Other Subject(s):
- Published through SciTech Connect.
Astrophysical Journal ISSN 0004-637X; ASJOAB FT
Heitmann, Katrin; Habib, Salman; Higdon, David; Williams, Brian J; White, Martin; Wagner, Christian.
- Funding Information:
View MARC record | catkey: 13804488