Cosmological information in weak lensing peaks

Abstract

Recent studies have shown that the number counts of convergence peaks N (κ) in weak lensing (WL) maps, expected from large forthcoming surveys, can be a useful probe of cosmology. We follow up on this finding, and use a suite of WL convergence maps, obtained from ray-tracing N-body simulations, to study (i) the physical origin of WL peaks with different heights, and (ii) whether the peaks contain information beyond the convergence power spectrum P . In agreement with earlier work, we find that high peaks (with amplitudes > ∼ 3.5σ, where σ is the r.m.s. of the convergence κ) are typically dominated by a single massive halo. In contrast, medium-height peaks (≈ 0.5 − 1.5σ) cannot be attributed to a single collapsed dark matter halo, and are instead created by the projection of multiple (typically, 4-8) halos along the line of sight, and by random galaxy shape noise. Nevertheless, these peaks dominate the sensitivity to the cosmological parameters w, σ8, and Ωm. We find that the peak height distribution and its dependence on cosmology differ significantly from predictions in a Gaussian random field. We directly compute the marginalized errors on w, σ8, and Ωm from the N (κ) + P combination, including redshift tomography with source galaxies at zs = 1 and zs = 2. We find that the N (κ) + P combination has approximately twice the cosmological sensitivity compared to P alone. These results demonstrate that N (κ) contains non-Gaussian information complementary to the power spectrum.PACS numbers: PACS codes: 95.36.+x, 98.65.Cw, 95.80.+p

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

“…Concentrating on high peaks, it is expected that signals of true peaks mainly come from individual massive halos (e.g., Hamana et al 2004;Tang & Fan 2005;Yang et al 2011). We therefore divide a given area into halo regions and field regions.…”

“…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.…”

Probing cosmology with weak lensing Minkowski functionals

“…fluctuations in κ caused by large-scale structures at z s = 2 are σ κ = 0.022, very close to the r.m.s. noise σ noise = 0.023 added to the maps [54]. We thus expect noise to degrade the constraints by of order a factor of ∼two.…”

“…(17) from the simulated WL maps -one can use the Fisher matrix formalism ( [67], and see [68] and [69] for comprehensive reviews of this application) to compute parameter constraints. In fact, at least four groups have followed this approach recently for weak lensing simulations, some with redshift tomography [53][54][55]70]. In practice, however, the Fisher matrix is a forecasting tool and misestimation of the covariance from the (simulated) data makes this procedure unstable as we combine smoothing scales and redshifts.…”

“…The early works [47] and [48] considered the Ω m -dependence of the one-point function and peak statistics, using ray-tracing simulations, while [26] and [27] used MFs to discern between SCDM, OCDM and ΛCDM models. More recently, [28] used the fractional area of "hot spots" of a thresholded map as a statistic, [49,50] explored the extent to which 2D projections of the 3D mass field trace cosmology, while [34,51] and later [52][53][54][55] used counts of peaks (defined as local maxima) in convergence and shear maps. 4 Finally, [56] constructed an analytical approximation to the peak number counts-their approximate statistic turns out to be the genus, which, as we will see below, is identical to one of the three MFs.…”