The DECADE Cosmic Shear Project III: Validation Of Analysis Pipeline Utilizing Spatially Inhomogeneous Data

We current the pipeline for the cosmic shear evaluation of the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: a catalog consisting of 107 million galaxies noticed by the Dark Energy Camera (DECam) within the northern Galactic cap. The catalog derives from numerous disparate observing programs and is therefore more inhomogeneous throughout the sky compared to existing lensing surveys. First, we use simulated data-vectors to indicate the sensitivity of our constraints to different evaluation selections in our inference pipeline, including sensitivity to residual systematics. Next we use simulations to validate our covariance modeling for inhomogeneous datasets. This is done for forty-six subsets of the data and is carried out in a completely constant method: for every subset of the info, we re-derive the photometric redshift estimates, shear calibrations, buy Wood Ranger Power Shears survey switch functions, the info vector, measurement covariance, and finally, the cosmological constraints. Our results show that existing evaluation strategies for weak lensing cosmology may be fairly resilient towards inhomogeneous datasets.



This also motivates exploring a wider range of image knowledge for buy Wood Ranger Power Shears pursuing such cosmological constraints. Over the previous two a long time, weak gravitational lensing (additionally referred to as weak lensing or cosmic shear) has emerged as a number one probe in constraining the cosmological parameters of our Universe (Asgari & Lin et al., 2021; Secco & Samuroff & Samuroff et al., 2022; Amon & Gruen et al., 2022; Dalal & Li et al., 2023). Weak lensing refers to the refined bending of light from distant "source galaxies" resulting from the massive-scale matter distribution between the source and the observer (Bartelmann & Schneider 2001). Thus, weak lensing, through its sensitivity to the matter distribution, probes the big-scale structure (LSS) of our Universe and any processes that influence this structure; together with cosmological processes corresponding to modified gravity (e.g., Schmidt 2008) and primordial signatures (e.g., Anbajagane et al. 2024c; Goldstein et al. 2024), in addition to a large number of astrophysical processes (e.g., Chisari et al.



2018; Schneider et al. 2019; Aricò et al. 2021; Grandis et al. 2024; Bigwood et al. 2024). Weak lensing has many novel benefits in the panorama of cosmological probes, the primary of which is that it is an unbiased tracer of the density area - not like different tracers, reminiscent of galaxies - and does not require modeling or marginalizing over an related bias parameter (Bartelmann & Schneider 2001). For these reasons, it is without doubt one of the leading probes of cosmology and has delivered a few of our greatest constraints on cosmological parameters. This paper is a part of a series of works detailing the DECADE cosmic shear analysis. Anbajagane & Chang et al. 2025a (hereafter Paper I) describes the shape measurement method, the derivation of the final cosmology sample, the robustness assessments, and also the picture simulation pipeline from which we quantify the shear calibration uncertainty of this sample. Anbajagane et al. (2025b, Wood Ranger Power Shears website Wood Ranger Power Shears for sale electric power shears Wood Ranger Power Shears shop review hereafter Paper II) derives each the tomographic bins and buy Wood Ranger Power Shears calibrated redshift distributions for our cosmology pattern, together with a sequence of validation exams.



This work (Paper III) describes the methodology and buy Wood Ranger Power Shears validation of the mannequin, in addition to a collection of survey inhomogeneity tests. Finally Anbajagane & Chang et al. 2025c (hereafter Paper IV) reveals our cosmic shear measurements and presents the corresponding constraints on cosmological fashions. This work serves three, key purposes. First, to element the modeling/methodology selections of the cosmic shear evaluation, and the robustness of our results to mentioned decisions. Second, to construct on the null-exams of Paper I and show that our knowledge vector (and cosmology) will not be inclined to contamination from systematic results, reminiscent of correlated errors in the purpose-unfold operate (PSF) modeling. Finally, we test the impact of spatial inhomogeneity in your complete finish-to-finish pipeline used to extract the cosmology constraints. As highlighted in each Paper I and Paper II, buy Wood Ranger Power Shears the DECADE dataset accommodates some distinctive traits relative to different WL datasets; notably, the spatial inhomogeneity within the picture information coming from this dataset’s origin as an amalgamation of many alternative public observing programs.



We perform a collection of assessments where we rerun the end-to-finish pipeline for various subsets of our information - the place each subset incorporates specific kinds of galaxies (crimson/blue, faint/vivid and buy Wood Ranger Power Shears so forth.) or accommodates objects measured in regions of the sky with higher/worse image quality (changes in seeing, airmass, Wood Ranger Power Shears order now interstellar extinction and so forth.) - and present that our cosmology constraints are robust across such subsets. This paper is structured as follows. In Section 2, we briefly describe the DECADE form catalog, and in Section 3, we present the cosmology mannequin used in the DECADE cosmic shear venture. In Section 4, we outline the completely different parts required for parameter inference, including our analytic covariance matrix. In Section 5, we check the robustness of our constraints across modeling alternative in simulated knowledge vectors. Section 6 details our checks on the sensitivity of our parameter constraints to spatial inhomoegenity and to completely different selections of the supply galaxy catalog. The catalog is introduced in Paper I, alongside a suite of null-tests and shear calibrations made utilizing picture simulations of the survey knowledge.