Cosmic Emulation: Fast Predictions for the Galaxy Power Spectrum

The halo occupation distribution (HOD) approach has proven to be an effective method for modeling galaxy clustering and bias. In this approach, galaxies of a given type are probabilistically assigned to individual halos in N-body simulations. In this paper, we present a fast emulator for predicting the fully nonlinear galaxy power spectrum over a range of freely specifiable HOD modeling parameters. The emulator is constructed using results from 100 HOD models run on a large LCDM N-body simulation, with Gaussian Process interpolation applied to a PCA-based representation of the galaxy power spectrum. The total error is currently ~3% (~2% in the simulation and ~1% in the emulation process) from z=1 to z=0, over the considered parameter range. We use the emulator to investigate parametric dependencies in the HOD model, as well as the behavior of galaxy bias as a function of HOD parameters. The emulator is publicly available at http://www.hep.anl.gov/cosmology/CosmicEmu/emu.html.Comment: Replaced to match published version. The emulator can be downloaded at http://www.hep.anl.gov/cosmology/CosmicEmu/emu.htm

Shrinkage Estimation of the Power Spectrum Covariance Matrix

We seek to improve estimates of the power spectrum covariance matrix from a limited number of simulations by employing a novel statistical technique known as shrinkage estimation. The shrinkage technique optimally combines an empirical estimate of the covariance with a model (the target) to minimize the total mean squared error compared to the true underlying covariance. We test this technique on N-body simulations and evaluate its performance by estimating cosmological parameters. Using a simple diagonal target, we show that the shrinkage estimator significantly outperforms both the empirical covariance and the target individually when using a small number of simulations. We find that reducing noise in the covariance estimate is essential for properly estimating the values of cosmological parameters as well as their confidence intervals. We extend our method to the jackknife covariance estimator and again find significant improvement, though simulations give better results. Even for thousands of simulations we still find evidence that our method improves estimation of the covariance matrix. Because our method is simple, requires negligible additional numerical effort, and produces superior results, we always advocate shrinkage estimation for the covariance of the power spectrum and other large-scale structure measurements when purely theoretical modeling of the covariance is insufficient.Comment: 9 pages, 7 figures (1 new), MNRAS, accepted. Changes to match accepted version, including an additional explanatory section with 1 figur

The introduction of new interventional procedures in the British National Health Service : A qualitative study

Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.Peer reviewedPostprin

The Universe at Extreme Scale: Multi-Petaflop Sky Simulation on the BG/Q

Remarkable observational advances have established a compelling cross-validated model of the Universe. Yet, two key pillars of this model -- dark matter and dark energy -- remain mysterious. Sky surveys that map billions of galaxies to explore the `Dark Universe', demand a corresponding extreme-scale simulation capability; the HACC (Hybrid/Hardware Accelerated Cosmology Code) framework has been designed to deliver this level of performance now, and into the future. With its novel algorithmic structure, HACC allows flexible tuning across diverse architectures, including accelerated and multi-core systems. On the IBM BG/Q, HACC attains unprecedented scalable performance -- currently 13.94 PFlops at 69.2% of peak and 90% parallel efficiency on 1,572,864 cores with an equal number of MPI ranks, and a concurrency of 6.3 million. This level of performance was achieved at extreme problem sizes, including a benchmark run with more than 3.6 trillion particles, significantly larger than any cosmological simulation yet performed.Comment: 11 pages, 11 figures, final version of paper for talk presented at SC1

The Clustering of AGN in the Sloan Digital Sky Survey

We present the two--point correlation function (2PCF) of narrow-line active galactic nuclei (AGN) selected within the First Data Release of the Sloan Digital Sky Survey. Using a sample of 13605 AGN in the redshift range 0.055 < z < 0.2, we find that the AGN auto--correlation function is consistent with the observed galaxy auto--correlation function on scales 0.2h^{-1}Mpc to >100h^{-1}Mpc. The AGN hosts trace an intermediate population of galaxies and are not detected in either the bluest (youngest) disk--dominated galaxies or many of the reddest (oldest) galaxies. We show that the AGN 2PCF is dependent on the luminosity of the narrow [OIII] emission line (L_{[OIII]}), with low L_{[OIII]} AGN having a higher clustering amplitude than high L_{[OIII]} AGN. This is consistent with lower activity AGN residing in more massive galaxies than higher activity AGN, and L_{[OIII]} providing a good indicator of the fueling rate. Using a model relating halo mass to black hole mass in cosmological simulations, we show that AGN hosted by ~ 10^{12} M_{odot} dark matter halos have a 2PCF that matches that of the observed sample. This mass scale implies a mean black hole mass for the sample of M_{BH} ~ 10^8 M_{odot}.Comment: 5 pages, 4 figures. Accepted for publication in ApJ