Constraining neutrino mass with tomographic weak lensing peak counts

Abstract

Massive cosmic neutrinos change the structure formation history by suppressing perturbations on small scales. Weak lensing data from galaxy surveys probe the structure evolution and thereby can be used to constrain the total mass of the three active neutrinos. However, much of the information is at small scales where the dynamics are nonlinear. Traditional approaches with second order statistics thus fail to fully extract the information in the lensing field. In this paper, we study constraints on the neutrino mass sum using lensing peak counts, a statistic which captures non-Gaussian information beyond the second order. We use the ray-traced weak lensing mocks from the Cosmological Massive Neutrino Simulations (MassiveNuS), and apply LSST-like noise. We discuss the effects of redshift tomography, multipole cutoff max for the power spectrum, smoothing scale for the peak counts, and constraints from peaks of different heights. We find that combining peak counts with the traditional lensing power spectrum can improve the constraint on neutrino mass sum, Ωm, and As by 39%, 32%, and 60%, respectively, over that from the power spectrum alone.

Weak lensing minima and peaks: Cosmological constraints and the impact of baryons

“…For peak counts, we find more peaks at the high κ tails in the simulations than in the GRFs, as the non-linear growth in the simulations leads to non-Gaussianity. This is consistent with previous works on peak counts (Yang et al 2011;Li et al 2019). For minimum counts, the non-Gaussian signatures are more prominent in the negative κ tails, with less minima in the simulations than in the GRFs.…”

“…3. Previously, Li et al (2019) studied the impact of massive neutrinos on lensing peaks and found a reduction in high lensing peaks, consistent with the expectation that massive neutrinos suppress the formation of massive haloes.…”

“…We verify that the interpolation errors are significantly smaller than the measurement errors. Further details of our emulator are described in detail in Li et al (2019), Coulton et al (2019). The simulation sample parameter ranges are used as the limits of our flat priors,…”

“…Further, by definition it only accesses third-order information and is therefore insensitive to information in fourth-and higher-order moments. Therefore, weak lensing summary statistics, which can be easier to measure and also contain information of all orders, have been proposed as simpler alternatives, such as the peak counts (Jain & Van Waerbeke 2000;Marian, Smith & Bernstein 2009;Maturi et al 2010;Yang et al 2011;Marian et al 2013;Liu et al 2015Liu et al , 2014Lin & Kilbinger 2015a, b;Kacprzak et al 2016;Martinet et al 2018;Peel et al 2018;Shan et al 2018;Li et al 2019), Minkowski functionals (Kratochvil et al 2012;Petri et al 2013Petri et al , 2015Shirasaki & Yoshida 2014;Marques et al 2019), clipped field statistics (Giblin et al 2018), and higher-order moments (Bernardeau, van Waerbeke & Mellier 1997;Hui 1999;Van Waerbeke et al 2001;Takada & Jain 2002;Zaldarriaga & Scoccimarro 2003;Kilbinger & Schneider 2005;Petri et al 2015;Peel et al 2018).…”

The impact of baryonic physics and massive neutrinos on weak lensing peak statistics

“…, using the present day number density of neutrinos given by Lesgourgues & Pastor (2012), where ρ ν and ρ 0 c are the neutrino and critical densities today. When massive neutrinos were added in the WMAP 9-based cosmology, the cold dark matter density was reduced in order to keep a flat geometry, or Ω b + Ω cdm + Ω ν + Ω Λ = 1.…”