The Aemulus Project III: Emulation of the Galaxy Correlation Function

Using the N-body simulations of the AEMULUS Project, we construct an emulator for the non-linear clustering of galaxies in real and redshift space. We construct our model of galaxy bias using the halo occupation framework, accounting for possible velocity bias. The model includes 15 parameters, including both cosmological and galaxy bias parameters. We demonstrate that our emulator achieves ~ 1% precision at the scales of interest, 0.1<r<10 h^{-1} Mpc, and recovers the true cosmology when tested against independent simulations. Our primary parameters of interest are related to the growth rate of structure, f, and its degenerate combination fsigma_8. Using this emulator, we show that the constraining power on these parameters monotonically increases as smaller scales are included in the analysis, all the way down to 0.1 h^{-1} Mpc. For a BOSS-like survey, the constraints on fsigma_8 from r<30 h^{-1} Mpc scales alone are more than a factor of two tighter than those from the fiducial BOSS analysis of redshift-space clustering using perturbation theory at larger scales. The combination of real- and redshift-space clustering allows us to break the degeneracy between f and sigma_8, yielding a 9% constraint on f alone for a BOSS-like analysis. The current AEMULUS simulations limit this model to surveys of massive galaxies. Future simulations will allow this framework to be extended to all galaxy target types, including emission-line galaxies.Comment: 14 pages, 8 figures, 1 table; submitted to ApJ; the project webpage is available at https://aemulusproject.github.io ; typo in Figure 7 and caption updated, results unchange

Simulating the Universe with MICE: The abundance of massive clusters

We introduce a new set of large N-body runs, the MICE simulations, that provide a unique combination of very large cosmological volumes with good mass resolution. They follow the gravitational evolution of ~ 8.5 billion particles (2048^3) in volumes covering up to 450 (Gpc/h)^3. Our main goal is to accurately model and calibrate basic cosmological probes that will be used by upcoming astronomical surveys. Here we take advantage of the very large volumes of MICE to make a robust sampling of the high-mass tail of the halo mass function (MF). We discuss and avoid possible systematic effects in our study, and do a detailed analysis of different error estimators. We find that available fits to the local abundance of halos (Warren et al. (2006)) match well the abundance in MICE up to M ~ 10^{14}\Msun, but significantly deviate for larger masses, underestimating the mass function by 10% (30%) at M = 3.16 x 10^{14}\Msun (10^{15}\Msun). Similarly, the widely used Sheth & Tormen (1999) fit, if extrapolated to high redshift assuming universality, leads to an underestimation of the cluster abundance by 30%, 20% and 15% at z=0, 0.5, 1 for M ~ [7 - 2.5 - 0.8] x 10^{14}\Msun respectively ($\nu = \delta_c/\sigma ~ 3$). We provide a re-calibration of the halo MF valid over 5 orders of magnitude in mass, 10^{10} < M/(\Msun) < 10^{15}, that accurately describes its redshift evolution up to z=1. We explore the impact of this re-calibration on the determination of dark-energy, and conclude that using available fits may systematically bias the estimate of w by as much as 50% for medium-depth (z <= 1) surveys. MICE halo catalogues are publicly available at http://www.ice.cat/miceComment: 16 pages, 11 figures. Data publicly available at http://www.ice.cat/mice. New version adds discussion on halo definition (SO vs FoF) and minor modifications. Accepted for publication in MNRA

The persistent cosmic web and its filamentary structure II: Illustrations

The recently introduced discrete persistent structure extractor (DisPerSE, Soubie 2010, paper I) is implemented on realistic 3D cosmological simulations and observed redshift catalogues (SDSS); it is found that DisPerSE traces equally well the observed filaments, walls, and voids in both cases. In either setting, filaments are shown to connect onto halos, outskirt walls, which circumvent voids. Indeed this algorithm operates directly on the particles without assuming anything about the distribution, and yields a natural (topologically motivated) self-consistent criterion for selecting the significance level of the identified structures. It is shown that this extraction is possible even for very sparsely sampled point processes, as a function of the persistence ratio. Hence astrophysicists should be in a position to trace and measure precisely the filaments, walls and voids from such samples and assess the confidence of the post-processed sets as a function of this threshold, which can be expressed relative to the expected amplitude of shot noise. In a cosmic framework, this criterion is comparable to friend of friend for the identifications of peaks, while it also identifies the connected filaments and walls, and quantitatively recovers the full set of topological invariants (Betti numbers) {\sl directly from the particles} as a function of the persistence threshold. This criterion is found to be sufficient even if one particle out of two is noise, when the persistence ratio is set to 3-sigma or more. The algorithm is also implemented on the SDSS catalogue and used to locat interesting configurations of the filamentary structure. In this context we carried the identification of an ``optically faint'' cluster at the intersection of filaments through the recent observation of its X-ray counterpart by SUZAKU. The corresponding filament catalogue will be made available online.Comment: A higher resolution version is available at http://www.iap.fr/users/sousbie together with complementary material (movie and data). Submitted to MNRA