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

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<br>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 observed by the Dark Energy Camera (DECam) in the northern Galactic cap. The catalog derives from a large number of disparate observing applications and  [https://wiki.fuzokudb.com/fdb/Bandage_Scissors_Are_Similar_In_Design pruning shears] is subsequently extra inhomogeneous throughout the sky compared to existing lensing surveys. First, we use simulated data-vectors to indicate the sensitivity of our constraints to completely different evaluation choices in our inference pipeline, including sensitivity to residual systematics. Next we use simulations to validate our covariance modeling [https://systemcheck-wiki.de/index.php?title=Benutzer:BetseyW56727616 Wood Ranger Power Shears for sale] inhomogeneous datasets. This is finished for forty-six subsets of the info and is carried out in a fully consistent manner: for each subset of the info, we re-derive the photometric redshift estimates, [https://omnideck.org/index.php/User:AishaShanahan1 pruning shears] shear calibrations, survey switch capabilities, [https://pipewiki.org/wiki/index.php/Tools_For_Installing_Fiber-Cement_Siding pruning shears] the info vector, [http://83.151.205.89:3000/marshageoghega/wood-ranger-official2002/wiki/Lawn+%2526+Hedge+Shears Wood Ranger Tools] measurement covariance, and at last, [https://coastalexpedition.com/ArchaixChronicon/index.php/Mythos_Offset_5.5_LEFT_Conblade Wood Ranger Power Shears reviews] the cosmological constraints. Our results present that existing evaluation methods for [https://andyfreund.de/wiki/index.php?title=Shears_Family_Home_Page pruning shears] weak lensing cosmology might be fairly resilient towards inhomogeneous datasets.<br><br><br><br>This also motivates exploring a wider vary of image knowledge for pursuing such cosmological constraints. Over the previous two decades, [https://koreanaggies.net/board_Lmao72/1992412 pruning shears] weak gravitational lensing (additionally referred to as weak lensing or cosmic shear) has emerged as a leading 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" as a consequence of the large-scale matter distribution between the supply and the observer (Bartelmann & Schneider 2001). Thus, weak lensing, through its sensitivity to the matter distribution, probes the big-scale construction (LSS) of our Universe and any processes that impression this structure; including cosmological processes akin to modified gravity (e.g., Schmidt 2008) and primordial signatures (e.g., Anbajagane et al. 2024c; Goldstein et al. 2024), as well as a large variety of astrophysical processes (e.g., Chisari et al.<br><br><br><br>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 landscape of cosmological probes, the primary of which is that it's an unbiased tracer of the density subject - in contrast to different tracers, similar to galaxies - and does not require modeling or marginalizing over an associated bias parameter (Bartelmann & Schneider 2001). For these causes, it is without doubt one of the leading probes of cosmology and has delivered a few of our best constraints on cosmological parameters. This paper is part of a sequence of works detailing the DECADE cosmic shear analysis. Anbajagane & Chang et al. 2025a (hereafter Paper I) describes the shape measurement method, [http://stephankrieger.net/index.php?title=If_They_Are_Used_In_Battle pruning shears] the derivation of the final cosmology pattern, the robustness checks, and also the picture simulation pipeline from which we quantify the shear calibration uncertainty of this sample. Anbajagane et al. (2025b, hereafter Paper II) derives each the tomographic bins and calibrated redshift distributions for our cosmology pattern, together with a series of validation exams.<br><br><br><br>This work (Paper III) describes the methodology and validation of the model, along with a collection 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 fashions. This work serves three, key functions. First, [https://wiki.insidertoday.org/index.php/The_Fifth_Book_Chapter_IX rechargeable garden shears] to element the modeling/methodology selections of the cosmic shear evaluation, and the robustness of our results to mentioned choices. Second, to build on the null-assessments of Paper I and present that our information vector (and [https://bbarlock.com/index.php/What_Happens_To_Weapons_Confiscated_At_The_Airport Wood Ranger Power Shears manual] cosmology) should not vulnerable to contamination from systematic results, similar to correlated errors in the purpose-unfold function (PSF) modeling. Finally, we take a look at the impact of spatial inhomogeneity in all the finish-to-end pipeline used to extract the cosmology constraints. As highlighted in both Paper I and Paper II, the DECADE dataset contains some distinctive characteristics relative to other WL datasets; significantly, the spatial inhomogeneity in the picture data coming from this dataset’s origin as an amalgamation of many alternative public observing applications.<br><br><br><br>We carry out a set of assessments where we rerun the tip-to-end pipeline for different subsets of our knowledge - where every subset incorporates particular kinds of galaxies (red/blue, faint/vivid and many others.) or contains objects measured in areas of the sky with higher/worse picture high quality (adjustments in seeing, airmass, interstellar extinction and so forth.) - and show that our cosmology constraints are sturdy across such subsets. This paper is structured as follows. In Section 2, we briefly describe the DECADE form catalog, and in Section 3, we current the cosmology model used within the DECADE cosmic shear venture. In Section 4, we outline the different components required for parameter inference, together with our analytic covariance matrix. In Section 5, we examine the robustness of our constraints across modeling selection in simulated knowledge vectors. Section 6 details our tests on the sensitivity of our parameter constraints to spatial inhomoegenity and to different selections of the source galaxy catalog. The catalog is launched in Paper I, alongside a set of null-checks and shear calibrations made using picture simulations of the survey data.<br>
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<br>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  [http://wiki.rumpold.li/index.php?title=Benutzer:AthenaQuezada 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 [https://wapure.best/edmundosaldiva 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.<br><br><br><br>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., [https://shaderwiki.studiojaw.com/index.php?title=Pinking_Shears_-_Scallop 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.<br><br><br><br>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, [http://bluecell.synology.me:3000/conradkiefer8/conrad1990/wiki/Scrap+Metal+Processing+Equipment 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 [https://wiki.heycolleagues.com/index.php/Top_Kitchen_Shears_On_Amazon:_Your_Guide Wood Ranger Power Shears reviews] our cosmology sample, together with a sequence of validation assessments.<br><br><br><br>This work (Paper III) describes the methodology and [https://hongkong.a2bookmarks.com/2025/09/16/revolutionizing-garden-care-with-wood-ranger-power-shears-3/ 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 [http://giteaiposeek.cn/iafvince362588 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.<br><br><br><br>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 [https://www.ebersbach.org/index.php?title=User:RefugiaNolan8 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.<br>

Aktuelle Version vom 17. September 2025, 02:00 Uhr


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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