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

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We present the pipeline for the cosmic shear analysis 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 a large number of disparate observing packages and Wood Ranger Power Shears reviews is therefore extra inhomogeneous throughout the sky compared to current lensing surveys. First, we use simulated knowledge-vectors to point out the sensitivity of our constraints to completely different analysis choices 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 Wood Ranger Power Shears reviews is carried out in a completely consistent method: for every subset of the information, we re-derive the photometric redshift estimates, shear calibrations, survey transfer functions, the information vector, measurement covariance, and at last, the cosmological constraints. Our results show that current analysis strategies for weak lensing cosmology can be pretty resilient in the direction of inhomogeneous datasets.



This additionally motivates exploring a wider range of image knowledge for pursuing such cosmological constraints. Over the previous two a long time, weak gravitational lensing (also known 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., Wood Ranger Power Shears reviews 2021; Secco & Samuroff & Samuroff et al., 2022; Amon & Gruen et al., 2022; Dalal & Li et al., 2023). Weak lensing refers to the subtle bending of mild from distant "source galaxies" attributable to the large-scale matter distribution between the source and the observer (Bartelmann & Schneider 2001). Thus, weak lensing, by means of its sensitivity to the matter distribution, probes the large-scale construction (LSS) of our Universe and any processes that impact this construction; including cosmological processes reminiscent of modified gravity (e.g., Schmidt 2008) and primordial signatures (e.g., Anbajagane et al. 2024c; Goldstein et al. 2024), in addition to a large variety 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 advantages in the panorama of cosmological probes, the first of which is that it is an unbiased tracer of the density subject - not like other tracers, equivalent to galaxies - and does not require modeling or marginalizing over an related bias parameter (Bartelmann & Schneider 2001). For these causes, it is likely one of the main probes of cosmology and has delivered some of our greatest constraints on cosmological parameters. This paper is a part of a sequence of works detailing the DECADE cosmic shear analysis. Anbajagane & Chang et al. 2025a (hereafter Paper I) describes the shape measurement methodology, the derivation of the ultimate cosmology sample, the robustness assessments, Wood Ranger Power Shears reviews and likewise the image simulation pipeline from which we quantify the shear calibration uncertainty of this sample. Anbajagane et al. (2025b, hereafter Paper II) derives both the tomographic bins and calibrated redshift distributions for Wood Ranger Power Shears reviews our cosmology sample, together with a sequence of validation assessments.



This work (Paper III) describes the methodology and Wood Ranger Power Shears review Ranger Power Shears sale validation of the mannequin, along with a sequence of survey inhomogeneity tests. Finally Anbajagane & Chang et al. 2025c (hereafter Paper IV) shows our cosmic shear measurements and presents the corresponding constraints on cosmological models. This work serves three, key functions. First, to detail the modeling/methodology decisions of the cosmic shear evaluation, and Wood Ranger Power Shears features Ranger Power Shears shop the robustness of our results to stated choices. Second, to construct on the null-checks of Paper I and show that our knowledge vector (and cosmology) are usually not prone to contamination from systematic effects, akin to correlated errors in the purpose-spread operate (PSF) modeling. Finally, we take a look at the impact of spatial inhomogeneity in your complete end-to-finish pipeline used to extract the cosmology constraints. As highlighted in each Paper I and Paper II, the DECADE dataset incorporates some unique traits relative to different WL datasets; particularly, the spatial inhomogeneity within the image data coming from this dataset’s origin as an amalgamation of many different public observing applications.



We carry out a set of checks the place we rerun the end-to-end pipeline for different subsets of our knowledge - where each subset comprises particular sorts of galaxies (pink/blue, faint/brilliant and so forth.) or incorporates objects measured in regions of the sky with higher/worse picture quality (modifications in seeing, airmass, interstellar extinction and so on.) - and show that our cosmology constraints are strong 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 within the DECADE cosmic shear venture. In Section 4, we outline the totally different elements required for parameter inference, including our analytic covariance matrix. In Section 5, we check the robustness of our constraints throughout modeling alternative in simulated information vectors. Section 6 details our tests on the sensitivity of our parameter constraints to spatial inhomoegenity and Wood Ranger Power Shears reviews to completely different selections of the supply galaxy catalog. The catalog is launched in Paper I, alongside a collection of null-tests and shear calibrations made utilizing picture simulations of the survey information.

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