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Title: Primordial non-Gaussianity with angular correlation function: integral constraint and validation for DES

Journal Article · · Monthly Notices of the Royal Astronomical Society
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [2]; ORCiD logo [3]; ORCiD logo [4];  [5];  [6];  [1]; ORCiD logo [7]; ORCiD logo [8]; ORCiD logo [9]; ORCiD logo [10];  [11]; ORCiD logo [12];  [13];  [9]; ORCiD logo [11];  [9];  [9]
  1. Instituto de Física Teorica UAM-CSIC, Madrid (Spain); Universidad Autónoma de Madrid (Spain)
  2. The Ohio State University, Columbus, OH (United States); University of Edinburgh, Scotland (United Kingdom)
  3. University of Oslo (Norway)
  4. Sun Yat-Sen Univ., Zhuhai (China)
  5. Universidade Estadual Paulista, São Paulo (Brazil)
  6. Universidade Estadual Paulista, São Paulo (Brazil); Laboratório Interinstitucional de e-Astronomia, Rio de Janeiro (Brazil)
  7. Laboratório Interinstitucional de e-Astronomia, Rio de Janeiro (Brazil); Instituto de Astrofisica de Canarias, Tenerife (Spain)
  8. Institut d’Estudis Espacials de Catalunya (IEEC), Barcelona (Spain); Institute of Space Sciences (ICE, CSIC), Campus UAB, Barcelona (Spain)
  9. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) , Madrid (Spain)
  10. University of Arizona, Tucson, AZ (United States); California Institute of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Laboratory (JPL)
  11. The Ohio State University, Columbus, OH (United States)
  12. University of California, Berkeley, CA (United States); University of Arizona, Tucson, AZ (United States)
  13. University of Arizona, Tucson, AZ (United States)

Local primordial non-Gaussianity (PNG) is a promising observable of the underlying physics of inflation, characterized by $$f_{NL}^{loc}$$. Here we present the methodology to measure $$f_{NL}^{loc}$$ from the Dark Energy Survey (DES) data using the two-point angular correlation function (ACF) with scale-dependent bias. One of the focuses of the work is the integral constraint (IC). This condition appears when estimating the mean number density of galaxies from the data and is key in obtaining unbiased $$f_{NL}^{loc}$$ 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 IC when measuring PNG, where we recover the fiducial values of fNL within the 1σ when including the IC. 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 set-up finding it robust to different analysis choices: best-fitting 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.>

Research Organization:
Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Argonne National Laboratory (ANL), Argonne, IL (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP); USDOE
Grant/Contract Number:
AC02-07CH11359
OSTI ID:
1975324
Alternate ID(s):
OSTI ID: 1898856
Report Number(s):
FERMILAB-PUB-22-655-V; DES-2021-0676; IFT-UAM/CSIC-22-107; arXiv:2209.07187; oai:inspirehep.net:2152441
Journal Information:
Monthly Notices of the Royal Astronomical Society, Vol. 523, Issue 1; ISSN 0035-8711
Publisher:
Oxford University PressCopyright Statement
Country of Publication:
United States
Language:
English

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