Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey – I: Catalogue preparation and systematic mitigation

Abstract

We investigate the large-scale clustering of the final spectroscopic sample of quasars from the recently completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). The sample contains 343708 objects in the redshift range 0.8 < z < 2.2 and 72667 objects with redshifts 2.2 < z < 3.5, covering an effective area of 4699 deg2. We develop a neural network-based approach to mitigate spurious fluctuations in the density field caused by spatial variations in the quality of the imaging data used to select targets for follow-up spectroscopy. Simulations are used with the same angular and radial distributions as the real data to estimate covariance matrices, perform error analyses, and assess residual systematic uncertainties. We measure the mean density contrast and cross-correlations of the eBOSS quasars against maps of potential sources of imaging systematics to address algorithm effectiveness, finding that the neural network-based approach outperforms standard linear regression. Stellar density is one of the most important sources of spurious fluctuations, and a new template constructed using data from the Gaia spacecraft provides the best match to the observed quasar clustering. The end-product from this work is a new value-added quasar catalogue with the improved weights to correct for nonlinear imaging systematic effects, which will be made public. Our quasar catalogue is used to measure the local-type primordial non-Gaussianity in our companion paper, Mueller et al. in preparation.

Angular clustering properties of the DESI QSO target selection using DR9 Legacy Imaging Surveys

“…Dawson et al 2016 ). For SDSS DR16 quasars, we use the systematic weights provided in Rezaie et al ( 2021 ) based on an NN treatment (see Ross et al 2020 , for the standard treatment). The results are shown in Fig.…”

Multi-wavelength spectroscopic probes: biases from neglecting light-cone effects

“…However, the degree of bias depends on the survey specifications. One should note that f NL is also sensitive to bias from observational systematics such as stellar contamination [19] and foreground contamination of 21cm intensity maps [20,21]. The analysis in our companion paper [1] takes into account these systematics, and shows that their effect on σ(f NL ) is considerably reduced in multi-tracer constraints.…”

Detecting the power spectrum turnover with HI intensity mapping

“…Current galaxy analyses probing primordial non-Gaussianity on ultra-large scales adopt similar approaches of very deep redshift bins (e.g. Castorina et al 2019;Rezaie et al 2021). Redshift weighting schemes can be constructed for specific probes (e.g.…”