Constraining primordial non-Gaussianity from DESI quasar targets and Planck CMB lensing

Abstract

We detect the cross-correlation between 2.7 million DESI quasar targets across 14,700 deg${}^2$ (180 quasars deg${}^{-2}$) and Planck 2018 CMB lensing at $\sim$30$\sigma$. We use the cross-correlation on very large scales to constrain local primordial non-Gaussianity via the scale dependence of quasar bias. The DESI quasar targets lie at an effective redshift of 1.51 and are separated into four imaging regions of varying depth and image quality. We select quasar targets from Legacy Survey DR9 imaging, apply additional flux and photometric redshift cuts to improve the purity and reduce the fraction of unclassified redshifts, and use early DESI spectroscopy of 194,000 quasar targets to determine their redshift distribution and stellar contamination fraction (2.6%). Due to significant excess large-scale power in the quasar autocorrelation, we apply weights to mitigate contamination from imaging systematics such as depth, extinction, and stellar density. We use realistic contaminated mocks to determine the greatest number of systematic modes that we can fit, before we are biased by overfitting and spuriously remove real power. We find that linear regression with one to seven imaging templates removed per region accurately recovers the input cross-power, $f_{\text{NL}}$ and linear bias. As in previous analyses, our $f_{\text{NL}}$ constraint depends on the linear primordial non-Gaussianity bias parameter, $b_{\varphi }=2(b-p){\delta }_c$ assuming universality of the halo mass function. We measure $f_{\text{NL}}=-26_{-40}^{+45}$ with $p=1.6$ $(f_{\text{NL}}=-18_{-27}^{+29}$ with $p=1.0$), and find that this result is robust under several systematics tests. Future spectroscopic quasar cross-correlations with Planck lensing lensing can tighten the $f_{\text{NL}}$ constraints by a factor of 2 if they can remove the excess power on large scales in the quasar auto power spectrum.

57 pages, 25 figures, updated to match accepted version

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