Abstract

Local primordial non-Gaussianity (PNG) is a promising observable of the underlying physics of inflation, characterised by fNLlocf_{\rm NL}^{\rm loc}. We present the methodology to measure fNLlocf_{\rm NL}^{\rm loc} from the Dark Energy Survey (DES) data using the 2-point angular correlation function (ACF) with scale-dependent bias. One of the focuses of the work is the integral constraint. This condition appears when estimating the mean number density of galaxies from the data and is key in obtaining unbiased fNLlocf_{\rm NL}^{\rm loc} constraints. The methods are analysed for two types of simulations: ∼246\sim 246 GOLIAT-PNG N-body small area simulations with fNLf_{\rm NL} equal to -100 and 100, and 1952 Gaussian ICE-COLA mocks with fNL=0f_{\rm NL}=0 that follow the DES angular and redshift distribution. We use the ensemble of GOLIAT-PNG mocks to show the importance of the integral constraint when measuring PNG, where we recover the fiducial values of fNLf_{\rm NL} within the 1σ1\sigma when including the integral constraint. In contrast, we found a bias of ΔfNL∼100\Delta f_{\rm NL}\sim 100 when not including it. For a DES-like scenario, we forecast a bias of ΔfNL∼23\Delta f_{\rm NL} \sim 23, equivalent to 1.8σ1.8\sigma, when not using the IC for a fiducial value of fNL=100f_{\rm NL}=100. We use the ICE-COLA mocks to validate our analysis in a realistic DES-like setup finding it robust to different analysis choices: best-fit estimator, the effect of IC, BAO damping, covariance, and scale choices. We forecast a measurement of fNLf_{\rm NL} within σ(fNL)=31\sigma(f_{\rm NL})=31 when using the DES-Y3 BAO sample, with the ACF in the 1 deg<θ<20 deg1\ {\rm deg}<\theta<20\ {\rm deg} range.Comment: Version after MNRAS reviewer comments. Improved discussion in Section 7. 16 pages, 11 figure

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