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

We current the pipeline for the cosmic shear analysis of the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: Wood Ranger brand shears a catalog consisting of 107 million galaxies observed by the Dark Energy Camera (DECam) in the northern Galactic cap. The catalog derives from a lot of disparate observing packages and Wood Ranger brand shears is subsequently more inhomogeneous throughout the sky compared to present lensing surveys. First, we use simulated information-vectors to point out the sensitivity of our constraints to different evaluation decisions in our inference pipeline, Wood Ranger brand shears together with sensitivity to residual systematics. Next we use simulations to validate our covariance modeling Wood Ranger Power Shears for sale inhomogeneous datasets. This is done for forty-six subsets of the info and is carried out in a completely constant manner: for every subset of the info, we re-derive the photometric redshift estimates, shear calibrations, survey transfer functions, the data vector, measurement covariance, and at last, the cosmological constraints. Our outcomes present that current analysis methods for weak lensing cosmology can be fairly resilient in direction of inhomogeneous datasets.



This additionally motivates exploring a wider range of image information for pursuing such cosmological constraints. Over the previous two decades, 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 review Wood Ranger Power Shears Wood Ranger Power Shears sale Wood Ranger Power Shears order now shop 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 gentle from distant "source galaxies" resulting from the large-scale matter distribution between the supply and the observer (Bartelmann & Schneider 2001). Thus, weak lensing, by way of its sensitivity to the matter distribution, probes the big-scale structure (LSS) of our Universe and any processes that impression 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 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 within the landscape of cosmological probes, the primary of which is that it's an unbiased tracer of the density field - in contrast to other tracers, akin to galaxies - and doesn't require modeling or marginalizing over an associated bias parameter (Bartelmann & Schneider 2001). For these causes, it is without doubt one of the main probes of cosmology and has delivered some of our greatest constraints on cosmological parameters. This paper is part of a series of works detailing the DECADE cosmic shear evaluation. Anbajagane & Chang et al. 2025a (hereafter Paper I) describes the shape measurement methodology, the derivation of the ultimate cosmology sample, the robustness checks, and likewise the picture simulation pipeline from which we quantify the shear calibration uncertainty of this pattern. Anbajagane et al. (2025b, hereafter Paper II) derives both the tomographic bins and calibrated redshift distributions for our cosmology sample, together with a collection of validation exams.



This work (Paper III) describes the methodology and validation of the mannequin, in addition to a series of survey inhomogeneity checks. Finally Anbajagane & Chang et al. 2025c (hereafter Paper IV) exhibits our cosmic shear measurements and presents the corresponding constraints on cosmological models. This work serves three, key functions. First, to detail the modeling/methodology selections of the cosmic shear evaluation, and the robustness of our results to stated decisions. Second, to construct on the null-assessments of Paper I and show that our data vector (and Wood Ranger brand shears cosmology) are usually not vulnerable to contamination from systematic results, reminiscent of correlated errors in the purpose-spread perform (PSF) modeling. Finally, we test the influence of spatial inhomogeneity in all the end-to-end pipeline used to extract the cosmology constraints. As highlighted in both Paper I and Paper II, the DECADE dataset comprises some distinctive traits relative to different WL datasets; significantly, the spatial inhomogeneity within the image knowledge coming from this dataset’s origin as an amalgamation of many various public observing programs.



We carry out a suite of assessments where we rerun the tip-to-finish pipeline for Wood Ranger brand shears various subsets of our data - the place every subset accommodates particular sorts of galaxies (red/blue, faint/vibrant and many others.) or comprises objects measured in areas of the sky with higher/worse picture high quality (modifications in seeing, airmass, interstellar extinction and Wood Ranger brand shears so forth.) - and show that our cosmology constraints are sturdy throughout 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 mission. In Section 4, we outline the different components required for parameter inference, together with our analytic covariance matrix. In Section 5, we verify the robustness of our constraints throughout modeling selection in simulated information vectors. Section 6 particulars our exams on the sensitivity of our parameter constraints to spatial inhomoegenity and to totally different selections of the source galaxy catalog. The catalog is introduced in Paper I, alongside a suite of null-assessments and shear calibrations made utilizing image simulations of the survey knowledge.