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Bibliographic Details
Main Authors: Gatti, M., Campailla, G., Jeffrey, N., Whiteway, L., Porredon, A., Prat, J., Williamson, J., Raveri, M., Jain, B., Ajani, V., Giannini, G., Yamamoto, M., Zhou, C., Blazek, J., Anbajagane, D., Samuroff, S., Kacprzak, T., Alarcon, A., Amon, A., Bechtol, K., Becker, M., Bernstein, G., Campos, A., Chang, C., Chen, R., Choi, A., Davis, C., Derose, J., Diehl, H. T., Dodelson, S., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferte, A., Gruen, D., Gruendl, R., Harrison, I., Hartley, W. G., Herner, K., Huff, E. M., Jarvis, M., Kuropatkin, N., Leget, P. F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Rollins, R. P., Roodman, A., Sanchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Abbott, T. M. C., Aguena, M., Allam, S. S., Alves, O., Andrade-Oliveira, F., Bacon, D., Bocquet, S., Brooks, D., Rosell, A. Carnero, Carretero, J., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Ferrero, I., Frieman, J., García-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Lee, S., Marshall, J. L., Mena-Fernández, J., Miquel, R., Pieres, A., Malagón, A. A. Plazas, Sanchez, E., Cid, D. Sanchez, Schubnell, M., Smith, M., Suchyta, E., Tarle, G., Weaverdyck, N., Weller, J., Wiseman, P.
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2405.10881
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Table of Contents:
  • We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years (Y3) of the Dark Energy Survey (DES). We implement: 1) second and third moments; 2) wavelet phase harmonics; 3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven $νw$CDM cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the Figure of Merit $\textrm{FoM}(S_8, Ω_{\textrm{m}})$ is improved by 70 percent ($Λ$CDM) and 90 percent ($w$CDM). When all the summary statistics are combined, we achieve a 2 percent constraint on the amplitude of fluctuations parameter $S_8 \equiv σ_8 (Ω_{\textrm{m}}/0.3)^{0.5}$, obtaining $S_8 = 0.794 \pm 0.017$ ($Λ$CDM) and $S_8 = 0.817 \pm 0.021$ ($w$CDM). The constraints from different statistics are shown to be internally consistent (with a $p$-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the DES Y3 data, finding good consistency; we also compare with results from external datasets, such as \planck{} constraints from the Cosmic Microwave Background, finding statistical agreement, with discrepancies no greater than $<2.2σ$.