# Redshift-weighted constraints on primordial non-Gaussianity from the clustering of the eBOSS DR14 quasars in Fourier space

## TL;DR

This paper constrains primordial non-Gaussianity using quasar clustering data from SDSS IV eBOSS DR14, employing optimal Fourier space analysis to achieve some of the tightest large-scale structure limits to date.

## Contribution

It introduces an optimal power spectrum estimator with redshift weighting to improve constraints on local primordial non-Gaussianity from quasar clustering data.

## Key findings

- Constraints of -51<f_NL<21 at 95% CL from eBOSS DR14 quasars.
- Redshift weighting improves error bars by 15%.
- Forecasts suggest future data could reach σ_f_NL≈5-8.

## Abstract

We present constraints on local primordial non-Gaussianity (PNG), parametrized through $f^{\rm loc}_{\rm NL}$, using the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 14 quasar sample. We measure and analyze the anisotropic clustering of the quasars in Fourier space, testing for the scale-dependent bias introduced by primordial non-Gaussianity on large scales. We derive and employ a power spectrum estimator using optimal weights that account for the redshift evolution of the PNG signal. We find constraints of $-51<f^{\rm loc}_{\rm NL}<21$ at 95% confidence level. These are amont the tightest constraints from Large Scale Structure (LSS) data. Our redshift weighting improves the error bar by 15% in comparison to the unweighted case. If quasars have lower response to PNG, the constraint degrades to $-81<f^{\rm loc}_{\rm NL}<26$, with a 40% improvement over the standard approach. We forecast that the full eBOSS dataset could reach $\sigma_{f^{\rm loc}_{\rm NL}}\simeq 5\text{-}8$ using optimal methods and full range of scales.