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Magnification effect on the detection of primordial non-Gaussianity from photometric surveys

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arxiv 1103.1118 v1 pith:LV6Z5KKY submitted 2011-03-06 astro-ph.CO

classification astro-ph.CO
keywords surveysbiasmagnificationphotometricsystematiceffectgalaxynon-gaussianity
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We present forecast results for constraining the primordial non-Gaussianity from photometric surveys through a large-scale enhancement of the galaxy clustering amplitude. In photometric surveys, the distribution of observed galaxies at high redshifts suffers from the gravitational-lensing magnification, which systematically alters the number density for magnitude-limited galaxy samples. We estimate size of the systematic bias in the best-fit cosmological parameters caused by the magnification effect, particularly focusing on the primordial non-Gaussianity. For upcoming deep and/or wide photometric surveys like HSC, DES and LSST, the best-fit value of the non-Gaussian parameter, fNL, obtained from the galaxy count data is highly biased, and the true values of fNL would typically go outside the 3-sigma error of the biased confidence region, if we ignore the magnification effect in the theoretical template of angular power spectrum. The additional information from cosmic shear data helps not only to improve the constraint, but also to reduce the systematic bias. As a result, the size of systematic bias on fNL would become small enough compared to the expected 1-sigma error for HSC and DES, but it would be still serious for deep surveys with z_m > 1.5, like LSST. Tomographic technique improves the constraint on fNL by a factor of 2-3 compared to the one without tomography, but the systematic bias would increase.

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  1. Primordial non-Gaussianity -- the effects of relativistic and wide-angle corrections to the power spectrum

    astro-ph.CO 2024-12 conditional novelty 5.0 of 10

    Including the quadrupole in power-spectrum forecasts improves f_NL precision by 45% to 63%, while neglected relativistic and wide-angle corrections shift f_NL by up to 0.6 sigma for MegaMapper.

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