A new model to predict weak-lensing peak counts III. Filtering technique comparisons

Understand

This is the third in a series of papers that develop a new and flexible model to predict weak-lensing (WL) peak counts, which have been shown to be a very valuable non-Gaussian probe of cosmology.

• In this paper, we compare the cosmological information extracted from WL peak counts using different filtering techniques of the galaxy shear data, including linear filtering with a Gaussian and two compensated filters (the starlet wavelet and the aperture mass), and the nonlinear filtering method MRLens.
• We present improvements to our model that account for realistic survey conditions, which are masks, shear-to-convergence transformations, and non-constant noise.
• We create simulated peak counts from our stochastic model, from which we obtain constraints on the matter density $\Omega_\mathrm{m}$, the power spectrum normalisation $\sigma_8$, and the dark-energy parameter $w_0$.