The DECADE Cosmic Shear Project III: Validation of Analysis Pipeline using Spatially Inhomogeneous Data > 자유게시판

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We current the pipeline for Wood Ranger Power Shears website the cosmic shear evaluation of the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: a catalog consisting of 107 million galaxies observed by the Dark Energy Camera (DECam) within the northern Galactic cap. The catalog derives from a lot of disparate observing programs and is due to this fact more inhomogeneous throughout the sky compared to present lensing surveys. First, we use simulated data-vectors to point out the sensitivity of our constraints to totally different evaluation decisions 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 totally consistent method: for each subset of the info, we re-derive the photometric redshift estimates, Wood Ranger Tools shear calibrations, survey switch capabilities, the info vector, measurement covariance, and Wood Ranger Power Shears reviews finally, buy Wood Ranger Power Shears the cosmological constraints. Our outcomes show that current evaluation methods for weak lensing cosmology can be pretty resilient towards inhomogeneous datasets.

This also motivates exploring a wider vary of image data for 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 back to the refined bending of light from distant "source galaxies" as a consequence of the massive-scale matter distribution between the supply and the observer (Bartelmann & Schneider 2001). Thus, weak lensing, through its sensitivity to the matter distribution, probes the large-scale construction (LSS) of our Universe and any processes that impression this construction; including cosmological processes such as modified gravity (e.g., Schmidt 2008) and primordial signatures (e.g., Anbajagane et al. 2024c; Goldstein et al. 2024), as well as 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 advantages within the landscape of cosmological probes, the primary of which is that it is an unbiased tracer of the density field - unlike different tracers, comparable to galaxies - and doesn't require modeling or marginalizing over an associated bias parameter (Bartelmann & Schneider 2001). For these reasons, it is among the leading probes of cosmology and has delivered a few of our greatest constraints on cosmological parameters. This paper is a part of a sequence of works detailing the DECADE cosmic shear evaluation. Anbajagane & Chang et al. 2025a (hereafter Paper I) describes the shape measurement technique, the derivation of the ultimate cosmology sample, the robustness tests, and also the picture simulation pipeline from which we quantify the shear calibration uncertainty of this pattern. Anbajagane et al. (2025b, hereafter Paper II) derives each the tomographic bins and calibrated redshift distributions for our cosmology sample, together with a series of validation tests.

This work (Paper III) describes the methodology and validation of the mannequin, along with a sequence of survey inhomogeneity tests. 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 element the modeling/methodology selections of the cosmic shear analysis, and Wood Ranger Power Shears reviews the robustness of our outcomes to stated selections. Second, to build on the null-exams of Paper I and show that our data vector (and Wood Ranger Power Shears cosmology) will not be inclined to contamination from systematic results, akin to correlated errors in the purpose-spread function (PSF) modeling. Finally, we take a look at the impact of spatial inhomogeneity in the entire finish-to-end pipeline used to extract the cosmology constraints. As highlighted in both Paper I and Paper II, Wood Ranger Power Shears reviews the DECADE dataset comprises some unique traits relative to different WL datasets; particularly, the spatial inhomogeneity within the picture information coming from this dataset’s origin as an amalgamation of many various public observing applications.

We carry out a collection of checks where we rerun the top-to-finish pipeline for Wood Ranger Power Shears reviews various subsets of our knowledge - where every subset comprises specific sorts of galaxies (purple/blue, faint/brilliant and buy Wood Ranger Power Shears so on.) or contains objects measured in regions of the sky with better/worse picture high quality (adjustments in seeing, airmass, Wood Ranger Power Shears reviews interstellar extinction etc.) - and show that our cosmology constraints are strong throughout such subsets. This paper is structured as follows. In Section 2, we briefly describe the DECADE shape catalog, and in Section 3, we current the cosmology model used within the DECADE cosmic shear project. In Section 4, we define the completely different elements required for parameter inference, together with our analytic covariance matrix. In Section 5, we examine the robustness of our constraints across modeling choice in simulated information vectors. Section 6 particulars our checks on the sensitivity of our parameter constraints to spatial inhomoegenity and to totally different selections of the supply galaxy catalog. The catalog is launched in Paper I, Wood Ranger Power Shears reviews alongside a collection of null-checks and shear calibrations made using picture simulations of the survey knowledge.