Tomographic galaxy clustering with the Subaru Hyper Suprime-Cam first year public data release

Abstract

We analyze the clustering of galaxies in the first public data release of the Hyper Suprime-Cam Subaru Strategic Program. Despite the relatively small footprints of the ob- served fields, the data are an excellent proxy for the very deep photometric datasets that will be acquired by the Large Synoptic Survey Telescope, and are therefore an ideal test bed for the analysis methods being implemented by the LSST Dark Energy Science Collaboration. We select a magnitude limited sample with i < 24.5 and analyze it in four tomographic redshift bins covering the range 0.15 . z . 1.5. We carry out a Fourier-space analysis of the two-point clustering of this sample, including all auto- and cross-correlations between bins. We demonstrate the use of map-level deprojection methods to account for non-physical fluctuations in the galaxy number density caused by observational systematics. Through a halo occupation distribution analysis, we place constraints on the characteristic halo masses of this sample as a function of redshift, finding a good fit up to scales kmax = 1 Mpc−1, including both auto- and cross-correlations. Our results show monotonically decreasing av- erage halo masses with increasing redshift, which can be interpreted in terms of the drop-out of red galaxies at high redshifts for a flux-limited sample, consistent with previous analyses. In terms of photometric redshift systematics, we show that additional care is needed in or- der to marginalize over uncertainties in the redshift distribution in galaxy clustering, even for samples of this small size, and that these uncertainties can be significantly constrained by including cross-bin correlations. We are able to make a ∼ 3σ detection of the effects of lensing magnification in the HSC data. Our results are stable to variations in the amplitude of density fluctuations σ8 and the cold dark matter abundance Ωc and we find constraints that agree well with measurements from Planck and low-redshift probes. Finally, we use our analysis pipeline to study the clustering of galaxies as a function of limiting flux, and provide a simple fitting function for the linear galaxy bias for magnitude limited samples as a function of limiting magnitude and redshift.