Local primordial non-Gaussianity (PNG) is a promising observable of the
underlying physics of inflation, characterised by fNLloc​. We
present the methodology to measure fNLloc​ 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 fNLloc​
constraints. The methods are analysed for two types of simulations: ∼246
GOLIAT-PNG N-body small area simulations with fNL​ equal to -100 and
100, and 1952 Gaussian ICE-COLA mocks with fNL​=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 fNL​ within the 1σ when including
the integral constraint. In contrast, we found a bias of ΔfNL​∼100 when not including it. For a DES-like scenario, we forecast a bias of
ΔfNL​∼23, equivalent to 1.8σ, when not using the IC
for a fiducial value of fNL​=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 fNL​ within
σ(fNL​)=31 when using the DES-Y3 BAO sample, with the ACF in the
1 deg<θ<20 deg range.Comment: Version after MNRAS reviewer comments. Improved discussion in Section
7. 16 pages, 11 figure