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O'Connell, Ross

Publications and source records attributed to O'Connell, Ross.

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: theoretical systematics and Baryon Acoustic Oscillations in the galaxy correlation function

We investigate the potential sources of theoretical systematics in the anisotropic Baryon Acoustic Oscillation (BAO) distance scale measurements from the clustering of galaxies in configuration space using the final Data Release (DR12) of the Baryon Oscillation Spectroscopic Survey (BOSS). We perform a detailed study of the impact on BAO measurements from choices in the methodology such as fiducial cosmology, clustering estimators, random catalogues, fitting templates, and covariance matrices. The theoretical systematic uncertainties in BAO parameters are found to be 0.002 in the isotropic dilation α and 0.003 in the quadrupolar dilation ε. The leading source of systematic uncertainty is related to the reconstruction techniques. Theoretical uncertainties are sub-dominant compared with the statistical uncertainties for BOSS survey, accounting 0.2σ stat for α and 0.25σ stat for ε (σ α , stat ~ 0.010 and σ ε , stat ~ 0.012, respectively). We also present BAO-only distance scale constraints from the anisotropic analysis of the correlation function. Our constraints on the angular diameter distance D A (z) and the Hubble parameter H(z), including both statistical and theoretical systematic uncertainties, are 1.5 percent and 2.8 percent at z eff = 0.38, 1.4 percent and 2.4 percent at z eff = 0.51, and 1.7 percent and 2.6 percent at z eff = 0.61. This paper is part of a set that analyses the final galaxy clustering data set from BOSS. The measurements and likelihoods presented here are cross-checked with other BAO analysis in Alam et al. The systematic error budget concerning the methodology on post-reconstruction BAO analysis presented here is used in Alam et al. to produce the final cosmological constraints from BOSS.

79 ASTRONOMY AND ASTROPHYSICS↗

Large covariance matrices: smooth models from the two-point correlation function

We introduce a new method for estimating the covariance matrix for the galaxy correlation function in surveys of large-scale structure. Our method combines simple theoretical results with a realistic characterization of the survey to dramatically reduce noise in the covariance matrix. For example, with an investment of only ≈1000 CPU hours we can produce a model covariance matrix with noise levels that would otherwise require ~35 000 mocks. Non-Gaussian contributions to the model are calibrated against mock catalogues, after which the model covariance is found to be in impressive agreement with the mock covariance matrix. Since calibration of this method requires fewer mocks than brute force approaches, we believe that it could dramatically reduce the number of mocks required to analyse future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗