The impact of signaltonoise, redshift, and angular range on the bias of weak lensing 2point functions
Abstract
Weak lensing data follow a naturally skewed distribution, implying the data vector most likely yielded from a survey will systematically fall below its mean. Although this effect is qualitatively known from CMBanalyses, correctly accounting for it in weak lensing is challenging, as a direct transfer of the CMB results is quantitatively incorrect. While a previous study (Sellentin et al. 2018) focused on the magnitude of this bias, we here focus on the frequency of this bias, its scaling with redshift, and its impact on the signaltonoise of a survey. Filtering weak lensing data with COSEBIs, we show that weak lensing likelihoods are skewed up until $\ell \approx 100$, whereas CMBlikelihoods Gaussianize already at $\ell \approx 20$. While COSEBIcompressed data on KiDS and DESlike redshift and angular ranges follow Gaussian distributions, we detect skewness at 6$\sigma$ significance for half of a Euclid or LSSTlike data set, caused by the wider coverage and deeper reach of these surveys. Computing the signaltonoise ratio per data point, we show that precisely the data points of highest signaltonoise are the most biased. Over all redshifts, this bias affects at least 10% of a survey's total signaltonoise, at high redshifts up to 25%. The bias is accordingly expected to impact parameter inference. The bias can be handled by developing nonGaussian likelihoods. Otherwise, it could be reduced by removing the data points of highest signaltonoise.
 Publication:

The Open Journal of Astrophysics
 Pub Date:
 September 2020
 DOI:
 10.21105/astro.2007.07253
 arXiv:
 arXiv:2007.07253
 Bibcode:
 2020OJAp....3E..11L
 Keywords:

 Astrophysics  Cosmology and Nongalactic Astrophysics;
 Statistics  Methodology
 EPrint:
 Accepted by the Open Journal of Astrophysics