Systematic effects in large-scale angular power spectra of photometric quasars and implications for constraining primordial nongaussianity

TL;DR

This study investigates large-scale systematic errors in SDSS photometric quasar data that hinder accurate constraints on primordial non-Gaussianity, highlighting the importance of controlling systematics for future cosmological surveys.

Contribution

It demonstrates the significant impact of systematic contaminants on quasar clustering measurements and evaluates template-based methods to mitigate these effects.

Findings

Systematic errors cause significant large-scale correlations in quasar maps.

Template projection reduces contamination but does not eliminate it.

Current data quality limits constraints on primordial non-Gaussianity.

Abstract

Primordial non-Gaussianity of local type is predicted to lead to enhanced halo clustering on very large scales. Photometric quasars, which can be seen from cosmological redshifts z>2 even in wide-shallow optical surveys, are promising tracers for constraining non-Gaussianity using this effect. However, large-scale systematics can also mimic this signature of non-Gaussianity. In order to assess the contribution of systematic effects, we cross-correlate overdensity maps of photometric quasars from the Sloan Digital Sky Survey (SDSS) Data Release 6 (DR6) in different redshift ranges. We find that the maps are significantly correlated on large scales, even though we expect the angular distributions of quasars at different redshifts to be uncorrelated. This implies that the quasar maps are contaminated with systematic errors. We investigate the use of external templates that provide information on the spatial dependence of potential systematic errors to reduce the level of spurious clustering in the quasar data. We find that templates associated with stellar density, the stellar color locus, airmass, and seeing are major contaminants of the quasar maps, with seeing having the largest effect. Using template projection, we are able to decrease the significance of the cross-correlation measurement on the largest scales from 9.2-sigma to 5.4-sigma. Although this is an improvement, the remaining cross-correlation suggests the contamination in this quasar sample is too great to allow a competitive constraint on fNL by correlations internal to this sample. The SDSS quasar catalog exhibits spurious number density fluctuations of ~2% rms, and we need a contamination level less than 1% (0.6%) in order to measure values of fNL less than 100 (10). Properly dealing with these systematics will be paramount for future large scale structure surveys that seek to constrain non-Gaussianity.