CMB lensing and primordial non-Gaussianity
Duncan Hanson, Kendrick M. Smith, Anthony Challinor, Michele Liguori
TL;DR
This study assesses how gravitational lensing affects the estimation of primordial non-Gaussianity from the CMB bispectrum, focusing on ISW-lensing bias and lensing-induced shape changes. Using analytic low-order results and extensive non-Gaussian simulations with Planck-like $\ell_{max}$, the authors show that the ISW-lensing bias is a significant contaminant for the local shape but is manageable with subtraction, while lensing-induced modifications to the bispectrum shape have only small impact on $f_{NL}$ normalization. They demonstrate that the lensed bispectrum smears acoustic features by about 10% and that the resulting increase in estimator variance is negligible for Planck, implying robust constraints on $f_{NL}^{\rm loc}$ and $f_{NL}^{\rm eq}$ in this regime. Overall, lensing does not substantially degrade Planck-like measurements of primordial non-Gaussianity when biases are properly accounted, and the results support continued use of standard Fisher-forecast techniques with lensed simulations for future analyses.
Abstract
We study the effects of gravitational lensing on the estimation of non-Gaussianity from the bispectrum of the cosmic microwave background (CMB) temperature anisotropies. We find that the effect of lensing on the bispectrum may qualitatively be described as a smoothing of the acoustic features analogous to the temperature power spectrum. In contrast to previous results, for a Planck-like experiment which is cosmic-variance limited to L=2000, we find that lensing causes no significant degradation of our ability to constrain the non-Gaussianity amplitude fNL for both local and equilateral configurations, provided that the biases due to the cross correlation between the lensing potential and the integrated-Sachs-Wolfe (ISW) contribution to the CMB temperature are adequately understood. With numerical simulations, we also verify that low-order Taylor approximations to the lensed bispectrum and ISW-lensing biases are accurate.
