Stable clustering, the halo model and non-linear cosmological power spectra

By Rowan J. Smith, J. Peacock, Adrian Jenkins, Simon D. M. White, Carlos S. Frenk, Frazer R. Pearce, P. Thomas, G. Efstathiou, Hugh M. P. Couchman. 2002

1,693 citations recorded by the source corpus.

We present the results of a large library of cosmological N-body simulations, using power-law initial spectra.

Subfields: Astronomy and Astrophysics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/7b9dfc2efcb0ade3084757322a2bd9e99a30f912

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Astronomy and Astrophysics

In Instrumentation

Citations in the corpus

COLOSSUS: A Python Toolkit for Cosmology, Large-scale Structure, and Dark Matter Halos (2017, background): “Physically, the excess density at large radii is due to a combination of the non-linear infall of matter into the halo and the statistical contribution from neighboring halos (the 2-halo term, e.g. Smith et al. 2003; Hayashi & White 2008).”
The 2dF Galaxy Redshift Survey: power-spectrum analysis of the final data set and cosmological implications (2005, methodology): “The halo model is thus only required to give the real-space ratio between galaxy and nonlinear mass power spectra. c© 0000 RAS, MNRAS 000, 000–000 The ratio between non-linear and linear mass power is given by the HALOFIT fitting formula from Smith et al. (2003).”
The WiggleZ Dark Energy Survey: measuring the cosmic expansion history using the Alcock-Paczynski test and distant supernovae (2011, methodology): “Indeed, using the simplication of Equation 5, where Pδδ(k) is the non-linear power spectrum obtained from CAMB, produced an unchanged result for F (within the statistical errors), as illustrated in Figure 3 (the cyan data points).”
The WiggleZ Dark Energy Survey: mapping the distance-redshift relation with baryon acoustic oscillations (2011, methodology): “We included the boost in small-scale clustering power due to the non-linear scale-dependent growth of structure using the “halofit” prescription of Smith et al. (2003), as applied to the no-wiggles reference spectrum: PNL(k) = [ Pref,halofit(k) Pref(k) ] × Pdamped(k).”
Estimating Cosmological Parameters from the Dark Matter Distribution (2016, methodology): “, 2000), supplemented with the empirically calibrated non-linear corrections obtained from HALOFIT (Smith et al., 2003).”
The Dark Side of the Halo Occupation Distribution (2003, methodology): “We also checked this by comparing matter correlation functions in the simulation with the model of Smith et al. (2003).”
Galaxy clustering and galaxy-galaxy lensing: a promising union to constrain cosmological parameters (2008, methodology): “The linear power spectrum of density perturbations is computed using the transfer function of Eisenstein & Hu (1998), which properly accounts for the baryons, while the evolved, non-linear power spectrum of the dark matter, PNLdm (k), is computed using the fitting formula of Smith et al. (2003).”
A Closure Theory for Nonlinear Evolution of Cosmological Power Spectra (2007, methodology): “…theoretical tools dealing with the non-linear gravitational clustering are the N -body simulation and the fitting formula for matter power spectrum (e.g., Peacock & Dodds 1996; Smith et al. 2003), as well as the phenomenological approach based on the halo model (Cooray & Sheth 2002, for a review).”
Multipoint propagators in cosmological gravitational instability (2008, background): “[16, 23], originate either from the near universal transform advocated in [8] or are based on an even more empirical construction, the halo model [2].”
Galaxy formation theory (2010, background): “They are therefore not as “clean” as CMB and large scale structure constraints. determine the statistical distribution of matter in the nonlinear regime exist (Hamilton et al. 1991; Peacock and Dodds 1996; Smith et al. 2003; Heitmann et al. 2009).”
Cosmological baryonic and matter densities from 600 000 SDSS luminous red galaxies with photometric redshifts (2006, methodology): “We derived model spatial power spectra using the ‘CAMB’ software package (Lewis, Challinor & Lasenby 2000) which is based on CMBFAST (Seljak & Zaldarriaga 1996), including corrections for non-linear growth of structure using the fitting formulae of Smith et al. (2003) (‘halofit = 1’ in CAMB).”
Measurements of H(z) and DA(z) from the two-dimensional two-point correlation function of Sloan Digital Sky Survey luminous red galaxies (2011, methodology): “We then use the software packagehalofit (Smith et al. 2003) to compute the non-linear matter power spectrum: rhalofit(k) ≡ Phalofit,nw(k) Pnw(k) (3) Pnl(k) = Pdw(k)rhalofit(k), (4) wherePhalofit,nw(k) is the power spectrum obtained by applying halofit to the no-wiggle power spectrum, andPnl(k) is…”