A new model to predict weak-lensing peak counts

Abstract

Context. Weak-lensing peak counts have been shown to be a powerful tool for cosmology. They provide non-Gaussian information of large scale structures and are complementary to second-order statistics. Aims. We propose a new flexible method for predicting weak-lensing peak counts, which can be adapted to realistic scenarios, such as a real source distribution, intrinsic galaxy alignment, mask effects, and photo-z errors from surveys. The new model is also suitable for applying the tomography technique and nonlinear filters. Methods. A probabilistic approach to modeling peak counts is presented. First, we sample halos from a mass function. Second, we assign them density profiles. Third, we place those halos randomly on the field of view. The creation of these "fast simulations" requires much less computing time than do N-body runs. Then, we perform ray-tracing through these fast simulation boxes and select peaks from weak-lensing maps to predict peak number counts. The computation is achieved by our C algorithm. Results. We compare our results to N-body simulations to validate our model. We find that our approach is in good agreement with full N-body runs. We show that the lensing signal dominates shape noise and Poisson noise for peaks with S/N between 4 and 6. Also, counts from the same S/N range are sensitive to Ω m and σ 8 . We show how our model can distinguish between various combinations of those two parameters. Conclusions. In this paper, we offer a powerful tool for studying weak-lensing peaks. The potential of our forward model is its high flexibility, which makes the using peak counts under realistic survey conditions feasible.

Origin of weak lensing convergence peaks

“…Semi-analytical studies of peaks by various groups [13][14][15][16] all rely heavily on the assumption that peaks are projections of foreground dark matter halos. Motivated by these theoretical works, we here search for the peak-halo connection in observations.…”

“…Therefore, it is important to understand the origin of these low peaks, and eventually include them in peak count models. So far, only theoretical work using N-body simulations can incorporate low peaks, while simpler models [13][14][15][16] only focus on high peaks.…”

Do dark matter halos explain lensing peaks?

“…In particular, we compare results from full N-body simulations with those of a recent publicly available algo- rithm, Camelus [31]. In previous work [31], this model was found to predict accurately peak counts from N-body simulations for a specific cosmology. Here, we expand the comparison of peak counts to a wide range of different cosmologies, and also examine their predicted covariance matrices, showing how differences affect the resulting parameter credibility regions.…”

Cosmological constraints from weak lensing peak statistics with Canada-France-Hawaii Telescope Stripe 82 Survey

“…To overcome this limitation, higher order cosmic shear correlation analyses are a natural extension (e.g., Semboloni et al 2011;van Waerbeke et al 2013;Fu et al 2014). Weak lensing peak statistics, i.e., concentrating on high signal regions, is another way to probe efficiently the nonlinear regime of the structure formation, and thus can provide important complements to the cosmic shear 2-pt correlation analysis (e.g., White et al 2002;Hamana et al 2004;Tang & Fan 2005;Hennawi & Spergel 2005;Dietrich & Hartlap 2010;Kratochvil et al 2010;Yang et al 2011;Marian et al 2012;Hilbert et al 2012;Bard et al 2013;Lin & Kilbinger 2015) Observationally, different analyses have proved the feasibility of performing weak lensing peak searches from data (e.g., Wittman et al 2006;Gavazzi & Soucail 2007;Miyazaki et al 2007;Geller et al 2010). However, up to now, few cosmological constraints are derived from weak lensing peak statistics in real observations.…”