Kavli Affiliate: Jia Liu
| First 5 Authors: Joaquin Armijo, Gabriela A. Marques, Camila P. Novaes, Leander Thiele, Jessica A. Cowell
| Summary:
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 $S_8 equiv sigma_8sqrt{Omega_{{rm m}}/0.3} =
{0.808}_{-0.046}^{+0.033}$ 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, and are consistent with previous non-Gaussian
statistics analyses of the same dataset. Our study demonstrates the power of
Minkowski functionals beyond two-point statistics for constraining and breaking
the degeneracy between $Omega_{rm m}$ and $sigma_8$.
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