English

Post-Born corrections to the one-point statistics of (CMB) lensing convergence obtained via large deviation theory

Cosmology and Nongalactic Astrophysics 2020-04-15 v2

Abstract

Weak lensing of galaxies and CMB photons through the large-scale structure of the Universe is one of the most promising cosmological probes with upcoming experiments dedicated to its measurements such as Euclid/LSST and CMB Stage 4 experiments. With increasingly precise measurements, there is a dire need for accurate theoretical predictions. In this work, we focus on higher order statistics of the weak lensing convergence field, namely its cumulants such as skewness and kurtosis and its one-point probability distribution (PDF), and we quantify using perturbation theory the corrections coming from post-Born effects, meaning beyond the straight-line and independent lenses approximations. At first order, two such corrections arise: lens-lens couplings and geodesic deviation. Though the corrections are small for low source redshifts (below a few percents) and therefore for galaxy lensing, they become important at higher redshifts, notably in the context of CMB lensing, where the non-gaussianities computed from tree-order perturbation theory are found to be of the same order as the signal itself. We include these post-Born corrections on the skewness into a prediction for the one-point convergence PDF obtained with large deviation theory and successfully test these results against numerical simulations. The modelled PDF is indeed shown to perform better than the percent for apertures above ~ 10 arcminutes and typically in the three sigmas region around the mean.

Keywords

Cite

@article{arxiv.2002.03625,
  title  = {Post-Born corrections to the one-point statistics of (CMB) lensing convergence obtained via large deviation theory},
  author = {Alexandre Barthelemy and Sandrine Codis and Francis Bernardeau},
  journal= {arXiv preprint arXiv:2002.03625},
  year   = {2020}
}

Comments

Accepted for publication in MNRAS, 17 pages, comments welcome