Details

Autor(en) / Beteiligte

• Mead, A. J
• Heymans, C
• Lombriser, L
• Peacock, J. A
• Steele, O. I
• Winther, H. A

Titel

Accurate halo-model matter power spectra with dark energy, massive neutrinos and modified gravitational forces

Ist Teil von

• Monthly notices of the Royal Astronomical Society, 2016-06, Vol.459 (2), p.1468-1488

Ort / Verlag

London: Oxford University Press

Erscheinungsjahr

2016

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• We present an accurate non-linear matter power spectrum prediction scheme for a variety of extensions to the standard cosmological paradigm, which uses the tuned halo model previously developed in Mead et al. We consider dark energy models that are both minimally and non-minimally coupled, massive neutrinos and modified gravitational forces with chameleon and Vainshtein screening mechanisms. In all cases, we compare halo-model power spectra to measurements from high-resolution simulations. We show that the tuned halo-model method can predict the non-linear matter power spectrum measured from simulations of parametrized w(a) dark energy models at the few per cent level for k < 10 h Mpc−1, and we present theoretically motivated extensions to cover non-minimally coupled scalar fields, massive neutrinos and Vainshtein screened modified gravity models that result in few per cent accurate power spectra for k < 10 h Mpc−1. For chameleon screened models, we achieve only 10 per cent accuracy for the same range of scales. Finally, we use our halo model to investigate degeneracies between different extensions to the standard cosmological model, finding that the impact of baryonic feedback on the non-linear matter power spectrum can be considered independently of modified gravity or massive neutrino extensions. In contrast, considering the impact of modified gravity and massive neutrinos independently results in biased estimates of power at the level of 5 per cent at scales k > 0.5 h Mpc−1. An updated version of our publicly available hmcode can be found at https://github.com/alexander-mead/hmcode.