UNIONS: The impact of systematic errors on weak-lensing peak counts

Abstract

Context. The Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) is an ongoing deep photometric multiband survey of the northern sky. As part of UNIONS, the Canada-France Imaging Survey (CFIS) provides r-band data, which we use to study weak-lensing peak counts for cosmological inference. Aims. We assess systematic effects for weak-lensing peak counts and their impact on cosmological parameters for the UNIONS survey. In particular, we present results on local calibration, metacalibration shear bias, baryonic feedback, the source galaxy redshift estimate, intrinsic alignment, and cluster member dilution. Methods. For each uncertainty and systematic effect, we describe our mitigation scheme and the impact on cosmological parameter constraints. We obtain constraints on cosmological parameters from Monte Carlo Markov chains using CFIS data and MassiveNuS N-body simulations as a model for peak counts statistics. Results. Depending on the calibration (local versus global, and the inclusion or not of the residual multiplicative shear bias), the mean matter density parameter, Ωm, can shift by up to −0.024 (−0.5σ). We also see that including baryonic corrections can shift Ωm by +0.027 (+0.5σ) with respect to the dark-matter-only simulations. Reducing the impact of the intrinsic alignment and cluster member dilution through signal-to-noise cuts leads to larger constraints. Finally, with a mean redshift uncertainty of Δz̄ = 0.03, we see that the shift in Ωm (+0.001, which corresponds to +0.02σ) is not significant. Conclusions. This paper investigates, for the first time with UNIONS weak-lensing data and peak counts, the impact of systematic effects. The value of Ωm is the most impacted and can shift by up to ∼0.03, which corresponds to 0.5σ depending on the choices for each systematics. We expect constraints to become more reliable with future (larger) data catalogs, for which the current pipeline will provide a starting point. The code used to obtain the results is available on GitHub.

Starlet higher order statistics for galaxy clustering and weak lensing

“…Furthermore, the increasing precision reached with next-generation surveys will enable us to access the non-Gaussian part of cosmological signals, induced by the nonlinear evolution of structure on small scales and low redshifts, which is not captured with second-order summary statistics alone. Specifically for weak lensing, a rich literature proposing several non-Gaussian statistics (Euclid Collaboration 2023), such as Minkowski functionals (e.g., Kratochvil et al 2012 andParroni et al 2020), higher order moments (e.g., Petri et al 2016 andGatti et al 2020), bispectrum (Takada & Jain 2004;Coulton et al 2019), peak counts (Kruse & Schneider 1999;Dietrich & Hartlap 2010;Liu et al 2015;Lin & Kilbinger 2015;Peel et al 2017;Martinet et al 2017;Li et al 2019;Ajani et al 2020;Zücher et al 2022b;Ayçoberry et al 2023), Betti numbers (Parroni et al 2021), the scattering transform (Cheng et al 2020), wavelet phase harmonic statistics (Allys et al 2020), and machine learning-based methods (e.g., Fluri et al 2018 andShirasaki et al 2021), is catching the attention of the community. The 1 -norm of wavelet coefficients of weak-lensing convergence maps has been proposed (Ajani et al 2021) as a new summary statistics for weak lensing as it provides a unified framework to perform a multi-scale analysis that takes into account the information encoded in all pixels of the map.…”