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Can Halo Models Accurately Predict Weak Lensing Peaks?

Presentation #214.01 in the session Strong and Weak Gravitational Lensing.

Published onJun 29, 2022
Can Halo Models Accurately Predict Weak Lensing Peaks?

Weak gravitational lensing (WL), which traces all of the mass distribution in the universe, is one of the most promising cosmological probes of both dark matter and dark energy. In order to extract maximum cosmological information from next-generation WL surveys (e.g. Euclid, Roman, LSST), we need to make use of higher-order statistics that probe the information on small-scales where mass fluctuations are non-linear due to gravitational collapse. WL peak counts are one such advantageous and simple statistic. Their physical origin has previously been linked to dark matter halos along the line of sight and this relation has been used to develop various semi-analytic halo-based models for predicting peak counts. Using a suite of ray-tracing N-body simulations, we further study the origin of WL peaks and the effectiveness of halo-based models for WL peak counts by comparing WL peaks from the full simulations to those in WL maps created from only particles associated with halos — the latter playing the role of a “perfect” halo model. We find that while halos are able to predict positive peak counts well qualitatively, using WL maps generated from halo particles alone leads to a significant bias on the parameters (Ωm, σ8) for surveys larger than ≥ 100 deg2. We conclude that other elements of the cosmic web, outside and far away from dark matter halos, need to be incorporated into models of WL peaks in order to infer unbiased cosmological constraints and to take full advantage of this non-Gaussian statistic.

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