Clustering of Sloan Digital Sky Survey III Photometric Luminous Galaxies: The Measurement, Systematics and Cosmological Implications

TL;DR

The paper presents the measurement of the angular clustering of photometric CMASS Luminous Red Galaxies from SDSS-III DR8 over z ≈ 0.45–0.65, using an optimal quadratic estimator across four redshift slices and a novel approach to correcting large-scale systematics. By modeling non-linearities with a simple bias-plus-noise framework and incorporating redshift-space distortions, the authors extract the full shape of the angular power spectrum and detect BAO features, achieving cosmological constraints competitive with spectroscopic surveys when combined with WMAP7, HST, and SN data. The results yield a concordance-like cosmology with Ω_Λ ≈ 0.73, H_0 ≈ 70–71, and w ≈ -1, while tightening constraints on curvature and providing a robust framework for handling systematics in large photometric surveys. The work demonstrates the potential of imaging surveys for precision cosmology and sets the stage for next-generation surveys like DES and LSST to exploit large-scale structure through angular clustering.

Abstract

The Sloan Digital Sky Survey (SDSS) surveyed 14,555 square degrees, and delivered over a trillion pixels of imaging data. We present a study of galaxy clustering using 900,000 luminous galaxies with photometric redshifts, spanning between $z=0.45$ and $z=0.65$, constructed from the SDSS using methods described in Ross et al. (2011). This data-set spans 11,000 square degrees and probes a volume of $3h^{-3} \rm{Gpc}^3$, making it the largest volume ever used for galaxy clustering measurements. We present a novel treatment of the observational systematics and its applications to the clustering signals from the data set. In this paper, we measure the angular clustering using an optimal quadratic estimator at 4 redshift slices with an accuracy of ~15% with bin size of delta_l = 10 on scales of the Baryon Acoustic Oscillations (BAO) (at l~40-400). We derive cosmological constraints using the full-shape of the power-spectra. For a flat Lambda CDM model, when combined with Cosmic Microwave Background Wilkinson Microwave Anisotropy Probe 7 (WMAP7) and H_0 constraints from 600 Cepheids observed by HST, we find Ω_Λ= 0.73 +/- 0.019 and H_0 to be 70.5 +/- 1.6 km/s/Mpc. For an open Lambda CDM model, when combined with WMAP7 + HST, we find $Ω_K = 0.0035 +/- 0.0054, improved over WMAP7+HST alone by 40%. For a wCDM model, when combined with WMAP7+HST+SN, we find w = -1.071 +/- 0.078, and H_0 to be 71.3 +/- 1.7 km/s/Mpc, which is competitive with the latest large scale structure constraints from large spectroscopic surveys such as SDSS Data Release 7 (DR7) (Reid et al. 2010, Percival et al. 2010, Montesano et al. 2011) and WiggleZ (Blake et al. 2011). The SDSS-III Data Release 8 (SDSS-III DR8) Angular Clustering Data allows a wide range of investigations into the cosmological model, cosmic expansion (via BAO), Gaussianity of initial conditions and neutrino masses. (abridged)

Figures (31)

• Figure 1: The full imaging angular mask in equatorial coordinate system after generating a unique set of all polygons that contains primary fields with good observing conditions. The colors represents the Modified Julian Date of observation of each field.
• Figure 2: The preliminary imaging mask after applying primary selection cuts such as cuts on seeing and the bright star mask on the full imaging angular mask.
• Figure 3: The redshift distribution of the photometric CMASS sample when we match the objects with an unbiased sub sample from SDSS-III BOSS.
• Figure 4: The photometric vs spectroscopic redshift distribution of 112,778 of SDSS-III BOSS CMASS galaxies.
• Figure 5: To justify our choice of scale for fitting our cosmological parameters, and the model we adopted, we show how well simple model such as $b^2 P_{\rm halofit}(k) +1/n + a$ can fit fairly well up to $k=0.2 h/Mpc$. Top panel shows the non-linear power-spectrum of halos in a cosmological simulations (dots with error bars), the model being considered here $b^2 P_{\rm halofit}(k) +1/n$ (solid line) and the dashed line shows what happens if we only use $b^2(k) P_{\rm NL}(k)$ instead. Bottom panel shows $a/P_{\rm hh}(k)$ where $a= P_{\rm halofit}(k) +1/n$, we can see that the ratio is fairly consistent with 0.0 for a large range of mass, and it starts to deviate from 0.0 starting at $k=0.1$Mpc/h. Therefore, we find it prudent to include an extra parameter a in our formalism, as we do include some modes at k larger than $k=0.1$ Mpc/h. The different color lines correspond to different halo mass ranges. The largest halos are those with highest bias, which also gives the largest deviations from the model.