Euclid preparation-XXVIII. Forecasts for ten different higher-order weak lensing statistics
V Ajani, M Baldi, A Barthelemy, A Boyle… - Astronomy & …, 2023 - aanda.org
Astronomy & Astrophysics, 2023•aanda.org
Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by
independent teams now outperform standard two-point estimators in terms of statistical
precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The
aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare,
and combine the constraining power of ten different HOS on a common set of Euclid-like
mocks, derived from N-body simulations. In this first paper of the HOWLS series, we …
independent teams now outperform standard two-point estimators in terms of statistical
precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The
aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare,
and combine the constraining power of ten different HOS on a common set of Euclid-like
mocks, derived from N-body simulations. In this first paper of the HOWLS series, we …
Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of Euclid-like mocks, derived from N-body simulations. In this first paper of the HOWLS series, we computed the nontomographic (Ωm, σ8) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a 4.5 times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with Euclid. The data used in this analysis are publicly released with the paper.
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