We developed a method to perform Wiener Filtering of Gaussian fields with an innovative neural network approach. Wiener filtering (or inverse covariance filtering) is the computational bottleneck of optimal analyses of near-Gaussian random fields, which are ubiquitous in cosmology. Our neural network, after training, is able to Wiener filter CMB maps a thousand times faster than the standard conjugate gradient …

In this paper we developed a new technique, called kSZ velocity reconstruction (sometimes also kSZ tomography), that uses the non-linear secondary anisotropies of the CMB, in combination with a galaxy survey, to get tighter constraints on cosmological parameters. The kSZ effect, the scattering of CMB photons on moving electrons, is the leading contribution to the CMB at small scales and …