Cosmological constraints using Minkowski functionals from the first year data of the Hyper Suprime-Cam

TL;DR

This paper demonstrates that Minkowski functionals applied to weak lensing maps from the Hyper Suprime-Cam survey provide improved cosmological constraints, especially on the matter density and clustering amplitude, surpassing power spectrum results.

Contribution

The study introduces the use of Minkowski functionals on real survey data to enhance cosmological parameter constraints and mitigate systematic effects.

Findings

Achieved a 40% improvement in S8 constraints over power spectrum only analyses.

Results are consistent with Planck CMB measurements.

Minkowski functionals effectively break degeneracies between Omega_m and sigma_8.

Abstract

We use Minkowski functionals to analyse weak lensing convergence maps from the first-year data release of the Subaru Hyper Suprime-Cam (HSC-Y1) survey. Minkowski functionals provide a description of the morphological properties of a field, capturing the non-Gaussian features of the Universe matter-density distribution. Using simulated catalogs that reproduce survey conditions and encode cosmological information, we emulate Minkowski functionals predictions across a range of cosmological parameters to derive the best-fit from the data. By applying multiple scales cuts, we rigorously mitigate systematic effects, including baryonic feedback and intrinsic alignments. From the analysis, combining constraints of the angular power spectrum and Minkowski functionals, we obtain $S_8 \equiv \sigma_8\sqrt{\Omega_{{\rm m}}/0.3} = {0.808}_{-0.046}^{+0.033}$ and $\Omega_{\rm m} = {0.293}_{-0.043}^{+0.157}$. These results represent a $40\%$ improvement on the $S_8$ constraints compared to using power spectrum only. \newtext{Minkowski functionals results are consistent with other two-point, and higher order statistics constraints using the same data, being in agreement with CMB results from the Planck $S_8$ measurements. Our study demonstrates the power of Minkowski functionals beyond two-point statistics to constrain and break the degeneracy between $\Omega_{\rm m}$ and $\sigma_8$.