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The paper claims that the largest cosmic shear dataset yet assembled—270 million galaxies across 13,000 square degrees—constrains the structure-growth parameter S8 to 0.805 ± 0.019, in agreement with the Planck CMB measurement at 1.9σ.

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The largest cosmic shear dataset to date yields S8 = 0.805 ± 0.019 and shows baryon modeling, not extra small-scale data, is the current bottleneck.

T0 review reviewed 2026-08-05 challenge →

load-bearing objection Largest cosmic shear dataset to date with a credible S8, but the combined 13k contour's precision rests on an untested independence assumption; worth serious refereeing. the 3 major comments →

arxiv 2509.03582 v3 pith:OR5T7VU3 submitted 2025-09-03 astro-ph.CO astro-ph.GA

The Dark Energy Camera All Data Everywhere cosmic shear project V: Constraints on cosmology and astrophysics from 270 million galaxies across 13,000 deg² of the sky

D. Anbajagane , C. Chang , A. Drlica-Wagner , C. Y. Tan , M. Adamow , R. A. Gruendl , L. F. Secco , Z. Zhang
show 73 more authors
M. R. Becker P. S. Ferguson N. Chicoine K. Herron A. Alarcon R. Teixeira D. Suson A. J. Shajib J. A. Frieman A. N. Alsina A. Amon F. Andrade-Oliveira J. Blazek C. R. Bom H. Camacho J. A. Carballo-Bello A. Carnero Rosell R. Cawthon W. Cerny A. Choi Y. Choi S. Dodelson C. Doux K. Eckert J. Elvin-Poole J. Esteves M. Gatti G. Giannini D. Gruen W. G. Hartley K. Herner E. M. Huff B. Jain D. J. James M. Jarvis E. Krause N. Kuropatkin C. E. Mart\'inez-V\'azquez P. Massana S. Mau J. McCullough G. E. Medina B. Mutlu-Pakdil J. Myles M. Navabi N. E. D. No\"el A. B. Pace S. Pandey A. Porredon J. Prat M. Raveri A. H. Riley E. S. Rykoff J. D. Sakowska S. Samuroff D. Sanchez-Cid D. J. Sand L. Santana-Silva I. Sevilla-Noarbe T. Shin M. Soares-Santos G. S. Stringfellow C. To E. J. Tollerud A. Tong M. A. Troxel A. K. Vivas M. Yamamoto B. Yanny B. Yin A. Zenteno Y. Zhang J. Zuntz
This is my paper
classification astro-ph.CO astro-ph.GA
keywords cosmic shearweak lensingS8matter clusteringbaryon feedbackdark energy equation of stateDECADEDES Y3
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper argues that a new combination of three weak-lensing datasets—the northern and southern Galactic caps of the DECADE survey plus the Dark Energy Survey Year 3—creates the largest cosmic shear sample to date, 270 million galaxies over 13,000 square degrees. From it, the authors extract ΛCDM constraints of S8 = 0.805 ± 0.019 and Ωm = 0.262(+0.023/−0.036), consistent with Planck 2018 within 1.9σ. The paper's more surprising claim is about information rather than cosmology: current scale cuts already limit baryon-induced bias to about 0.3σ, and switching to all scales with explicit baryon modeling improves the S8–Ωm figure of merit by only about 7%, because the extra small-scale information is consumed by self-calibrating the baryon suppression model. The practical upshot is that fully exploiting small-scale lensing in future surveys will require external handles on baryonic physics, such as Sunyaev-Zeldovich measurements.

Core claim

Combining the DECADE northern cap, a newly processed southern cap, and DES Y3 at the likelihood level, with independent intrinsic-alignment parameters per survey, the study measures shear two-point correlation functions and obtains S8 = 0.805 ± 0.019 and Ωm = 0.262(+0.023/−0.036). The three datasets are mutually consistent, and the combined contour matches Planck 2018 within 1.9σ. A second, arguably more consequential discovery is the saturation of lensing-only constraining power: scale cuts reduce baryon contamination to roughly 0.3σ residual bias in the S8–Ωm plane, and modeling baryons explicitly while using all scales adds only about 7% to the figure of merit, since the additional small-

What carries the argument

The analysis is carried by the angular cosmic shear two-point correlation functions ξ±, computed in four tomographic redshift bins per survey. The model chain uses a nonlinear matter power spectrum with a five-parameter intrinsic-alignment model per dataset, and the three surveys are combined by summing log-likelihoods under the assumption of independent sky patches. For the baryon study, the central object is the suppression ratio S(k) = P_bary(k)/P_dmo(k), generated through a halo-model calculation using the profile prescriptions of the BCEmu, Bacco, and HMx models and then emulated for fast sampling. This ratio is what determines both the inferred astrophysical feedback strength and the s

Load-bearing premise

The three sky patches are treated as statistically independent at the likelihood level even though they share the same camera, the same image-processing pipeline, and partly the same redshift-calibration deep fields; if correlated systematics survive, the combined posterior is overconfident and S8 could be biased.

What would settle it

Recompute the DECam 13k posterior using a covariance that includes cross-survey correlations between the three patches—constructed, for instance, by jackknifing the shared redshift-calibration deep fields—and check whether the S8–Ωm contour widens by more than the quoted S8 uncertainty. A second test: if a future spectroscopic redshift calibration that does not rely on those shared fields shifts S8 by more than about 0.02, the independence assumption fails.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • If S8 = 0.805 ± 0.019 holds, a lensing-only survey of 13,000 square degrees can match Planck-level precision on the growth parameter, providing a strong low-redshift check on the CMB.
  • The inferred ~25% baryon suppression becomes a concrete target for hydrodynamical simulations and for thermal/kinetic Sunyaev-Zeldovich observations.
  • For upcoming Stage IV surveys, blind scale cuts may be nearly as informative as explicit baryon marginalization unless external baryon priors are added.
  • Adding BAO and supernova data pulls Ωm upward toward the Planck value while leaving S8 essentially unchanged, breaking the geometry-growth degeneracy that plagues lensing-only contours.
  • The low goodness-of-fit of the combined ΛCDM fit originates in a few tomographic bin combinations in one survey region and does not shift the cosmology, marking those bins as a useful systematic diagnostic.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • A direct test of the 7% saturation claim would be to run the same all-scales pipeline on mock catalogs built from two very different baryon-feedback simulations; if the recovered S8 shifts between mocks by more than the statistical error, the lensing data are not fully self-calibrating even at 13,000 square degrees.
  • The difference in intrinsic-alignment behavior between the northern cap (a non-zero tidal-torquing amplitude) and the southern cap (consistent with no alignment) suggests alignment properties may vary with environment or survey depth, which could be tested by cross-correlating both shear catalogs with spectroscopic galaxy samples.
  • If future surveys adopt external baryon priors from tSZ/kSZ measurements, re-analyzing this same 13k dataset would quantify how much of the missing small-scale information can be recovered; a gain well above 7% would indicate that the reported saturation is specific to lensing-only data rather than fundamental.
  • The direction of the lensing-versus-Planck shift—low Ωm, slightly high S8—could indicate a distance-calibration effect rather than a growth effect; the fact that BAO/SNe data remove the Ωm discrepancy supports testing this with deeper photometric redshift calibration in the same footprint.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. This paper presents cosmic shear constraints from the combination of three data vectors: DECADE NGC, DECADE SGC, and DES Y3, totaling 270 million galaxies over 13,000 deg^2. Using a DES Y3-style pipeline with TATT intrinsic alignments, HMCode nonlinear power spectrum, and CosmoCov covariance, the authors report a fiducial ΛCDM result S8 = 0.805 ± 0.019, Ωm = 0.262^{+0.023}_{-0.036} (Eq. 7), consistent with Planck 2018 at 1.9σ. They extend the analysis to dynamical dark energy (w0wa and wφ models), finding that lensing adds only modest information beyond BAO+SNe. They then study six baryon suppression models, concluding that scale cuts leave a residual bias of ≈0.3σ in the S8–Ωm plane and that using all scales with explicit baryon modeling improves the figure of merit by only 7%, because the extra small-scale information mostly self-calibrates the baryon model. The data products and likelihoods are publicly released.

Significance. If the central result holds, this is the largest-area, largest-source-count weak lensing analysis to date and one of the most precise S8 constraints from cosmic shear alone. The paper is unusually transparent about goodness of fit, model variations, and the baryon-model dependence of small-scale information. Strengths include the public release of catalogs and likelihoods, the use of a well-tested covariance pipeline, multiple baryon models under a common BaryonForge framework, and explicit checks that posterior shifts from redshift-calibration uncertainties are small. The main scientific value is as a demonstration of what can be extracted from a 13,000 deg^2 lensing dataset before Stage IV surveys, and as a testing ground for the treatment of baryons and intrinsic alignments.

major comments (3)
  1. [§II.A and Appendix A] The combined 13k constraint is built by multiplying three likelihood blocks with zero cross-covariance, justified by independent sky patches, but the calibration systematics are not independent. Appendix A explicitly states that the NGC and SGC redshift calibration fields are shared, that the pipeline is unable to produce correlated calibration priors, and that the same data products are lacking for DES Y3. The independent Gaussian priors on Δz_i and m_i in Table I therefore do not capture common-mode calibration errors. The Δz_i = 0 test in Appendix A marginalizes over the total per-survey calibration uncertainty but leaves a coherent shift of all three data vectors untested. A shared calibration offset would bias S8/Ωm without changing this diagnostic. This is load-bearing for the 3× FoM gain and the quoted ±0.019 precision. Please quantify the impact of correlated calibration errors,
  2. [§III.A, Table III] The fiducial DECam 13k ΛCDM fit has p = 0.007, and the p-value only rises to 0.14 after dropping three DECADE NGC bin combinations that were identified in Paper IV and then excluded post hoc from the combined analysis. The authors correctly note that the cosmology posterior is unchanged, but a p-value this low indicates that the model or covariance is not fully capturing the data. Since this same dataset drives the central S8 constraint, the manuscript should provide a more detailed diagnosis: which angular scales/tomographic bin combinations contribute to the low p-value, whether the SGC or DES Y3 blocks show similar residuals, and whether the combined covariance is validated against the residuals. At minimum, the fiducial result should be reported side-by-side with the post-drop result more prominently, and the possibility of an underestimated covariance should be addressed explicitly.
  3. [§III.C, Figure 5 and Table III] The statement that current scale cuts leave a residual baryon bias of ≈0.3σ is an internal model comparison: 'No baryons, w/ cuts' is compared to 'BCEmu, w/ cuts' on the same lensing data, and the OWLS-AGN-based scale cuts are themselves derived from a simulation model. This is not an external calibration of the baryon suppression. If the true baryon feedback is outside the BCEmu prior or differs in shape from the OWLS-AGN template, the 0.3σ estimate could be larger. The agreement among BCEmu, Bacco, and HMx after widening their astrophysical priors is also agreement of models fitted to the same data, not independent validation. The paper does compare to simulations and tSZ/kSZ results in Figures 13–14, which helps, but the abstract's 'residual bias ≈0.3σ' phrasing should be caveated more explicitly as conditional on the baryon model family and the assumed scale-cut prescription.
minor comments (5)
  1. [§IV, first bullet] The summary quotes Ωm = 0.268^{+0.023}_{-0.036}, while Eq. (7) and Table III give Ωm = 0.262^{+0.023}_{-0.036}. Please correct this inconsistency.
  2. [§III.C, Figure 5 caption / text] The text says the FoM improves from 1872 to 1993, a '7%' improvement, but Table III also lists a '13k, no baryons' row with FoM = 2641 for the all-scales analysis. The comparison is clear in context, but the repeated use of 'no baryons' for two different scale-cut choices is confusing; consider relabeling the fiducial scale-cut model as 'No baryons, w/ cuts' throughout.
  3. [Figure 4 caption] Minor grammar: 'The BFG-BCEmu results matches the BCEmu result' should be 'matches'; also consider clarifying that the comparison is for the suppression ratio S(k), not the cosmology posterior, in the caption.
  4. [§II.A] The sentence 'The redshift distributions are listed in Figure 8 of Appendix A' is slightly awkward; consider referring to it as 'Figure 8' directly without the appendix cross-reference, or rephrase.
  5. [Table II] The WL+BAO rows have p-values of 0.013 and 0.010, which are close to the fiducial 13k p-value of 0.007. It would be helpful to state explicitly in the table caption or text whether these low p-values share the same origin as the fiducial ΛCDM low p-value.

Circularity Check

0 steps flagged

No load-bearing circularity: the central S8/Omega_m constraints are fit to new lensing data, and the baryon-model results are explicitly internal self-calibration rather than predictions forced by the inputs.

full rationale

The paper's central claim, S8 = 0.805 +/- 0.019 and Omega_m = 0.262^{+0.023}_{-0.036} (Eq. 7), is obtained by fitting a standard lensing model to three measured shear correlation-function data vectors. Nothing in the model is defined in terms of the final S8 or Omega_m, and the result is an externally falsifiable measurement compared against Planck, DES Y3, KiDS, and HSC. The combination of NGC, SGC, and DES Y3 is done at the likelihood level with zero cross-covariance (Section II.A). That is an independence assumption that could be wrong -- Appendix A explicitly states that the deep-field redshift-calibration samples are shared across NGC and SGC and that the pipeline 'is unable to produce correlated calibration priors.' But shared calibration fields are a systematic-error/correctness concern, not circularity: the three data vectors are still independent measurements, and the combined posterior is not constructed to equal any calibration input. The baryon-model section is best described as honest self-calibration. The paper fits baryon-suppression parameters on the same small-scale lensing data and then shows that different models agree once priors are widened (Figures 4-6). This is an internal consistency check, and the paper explicitly states that the new small-scale information is used 'solely to self-calibrate the baryon model' and that external probes are needed to access the full statistical power. Comparing two models on the same data is not a prediction from an external benchmark, but it is also not a fit renamed as a prediction. The residual scale-cut bias of ~0.3 sigma is likewise a relative comparison between analysis choices, not a claimed external prediction. The self-citations to Papers I-IV carry the shear catalogue, redshift calibration, and pipeline from the same collaboration. These are load-bearing in the sense that the analysis reuses previously developed tools, but they are not circular: they describe publicly released data products and validated pipelines, and the new SGC data vector is a genuinely new input. The w_phi model and the 1.35 < alpha < 1.45 prior come from Shajib & Frieman (2025), which has overlapping authors. This is a modeling choice with a stated prior, not a result that reduces to its own input; the dynamical-dark-energy conclusions are driven mainly by the external DESI BAO and DES SNe, with lensing providing minor orthogonal improvement. Overall, the central derivation is not equivalent to its inputs by constructio

Axiom & Free-Parameter Ledger

5 free parameters · 8 axioms · 0 invented entities

The paper fits a standard cosmological model with many nuisance parameters (IA, redshift and shear calibrations) and, for the baryon analyses, dozens of astrophysical parameters. No new entities are postulated. The key assumptions are the validity of the lensing kernel, the HMCode nonlinear prescription, the TATT IA model, the independence of the three data vectors, and the halo-model mapping used by the BaryonForge emulators.

free parameters (5)
  • Cosmological parameters Ωm, As, ns, h, Ωb, Ωνh^2 = Ωm posterior 0.262; others not quoted
    Target parameters of the fit with uniform priors (Table I); they are fitted to the lensing data and drive the quoted S8.
  • TATT IA amplitudes a1, a2, η1, η2, bTA per data vector = a2(NGC) > 0 at ~2σ; others unquoted
    15 free parameters (5 per dataset) modeling intrinsic alignments; the NGC a2 preference is unexplained and could trade off with cosmology.
  • Redshift calibration shifts Δz_i (NGC and SGC) = Gaussian priors, means 0, σ 1.0-1.6×10^-2
    8 parameters for the two DECADE regions, fitted with Gaussian priors; correlated across surveys because they share deep-field calibration samples.
  • Shear calibration m_i (NGC and SGC) = Gaussian priors, means -0.9% to -5.7%, σ 0.3-0.8%
    8 parameters from the shear calibration; priors in Table I.
  • Baryon model parameters (BCEmu: 8; Bacco: up to ~14; HMx: 10) = not quoted; posteriors shown in Figure 4
    The baryon suppression models have multiple free parameters with priors in Table V; these are fit to the lensing data and their priors are widened ('Wide' variants) to achieve cross-model concordance.
axioms (8)
  • domain assumption Shear two-point correlations are related to the matter power spectrum through standard weak lensing theory (Eq. 1).
    Foundational relation of cosmic shear, assumed throughout, Section II.B.
  • domain assumption HMCode (Mead et al. 2020) accurately predicts the nonlinear matter power spectrum.
    Adopted for the fiducial analysis following DES+KiDS; systematic errors from this choice are not fully quantified, Section II.B.
  • domain assumption TATT model (Blazek et al. 2019) describes intrinsic alignments in all three datasets.
    Used as the IA model, Eqs (2)-(4); DECADE NGC shows an unexplained preference for a2>0, Appendix C.
  • domain assumption The three data vectors are statistically independent and can be combined by multiplying their Gaussian likelihoods.
    Stated in Section II.A as due to independent sky patches; shared instrument and calibration fields may introduce correlations.
  • domain assumption The covariance matrix is fixed and known, computed with CosmoCov.
    Gaussian, connected non-Gaussian, super-sample, and mask terms included; no baryon effects because shape noise dominates on small scales, Section II.B and footnote 2.
  • domain assumption Baryons are the only statistically significant unmodeled small-scale systematic besides IA.
    Explicitly stated in a Summary bullet: 'This statement assumes baryons are the only statistically significant systematic on small scales.'
  • domain assumption The halo model with NFW profiles, Tinker mass function and the baryon density profiles of BCEmu/Bacco/HMx maps astrophysical parameters to the suppression S(k).
    Used to build the BaryonForge emulators, Appendix B.
  • domain assumption The theory-informed prior on α in the wφ model is correct.
    α ∈ [1.35,1.45] (or 1.55 per Table II) from Shajib & Frieman (2025), Section III.B.

reviewed 2026-08-05 · how reviews work

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Cite this review

Pith. "Pith review of The Dark Energy Camera All Data Everywhere cosmic shear project V: Constraints on cosmology and astrophysics from 270 million galaxies across 13,000 deg$^2$ of the sky." pith.science (2026). https://pith.science/paper/OR5T7VU3

@misc{pith2026250903582,
  author       = {Pith},
  title        = {Pith review of: The Dark Energy Camera All Data Everywhere cosmic shear project V: Constraints on cosmology and astrophysics from 270 million galaxies across 13,000 deg$^2$ of the sky},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/OR5T7VU3}},
  note         = {Machine review of arXiv:2509.03582}
}
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read the original abstract

We present constraints on models of cosmology and astrophysics using cosmic shear data vectors from three datasets: the northern and southern Galactic cap of the Dark Energy Camera All Data Everywhere (DECADE) project, and the Dark Energy Survey (DES) Year 3. These data vectors combined consist of 270 million galaxies spread across 13,000 ${\rm deg}^2$ of the sky. We first extract constraints for $\Lambda$CDM cosmology and find $S_8= 0.805^{+0.019}_{-0.019}$ and $\Omega_{\rm m} = 0.262^{+0.023}_{-0.036}$, which is consistent within $1.9 \sigma$ of constraints from the Planck satellite. Extending our analysis to dynamical dark energy models shows that lensing provides some (but still minor) improvements to existing constraints from supernovae and baryon acoustic oscillations. Finally, we study six different models for the impact of baryons on the matter power spectrum. We show the different models provide consistent constraints on baryon suppression, and associated cosmology, once the astrophysical priors are sufficiently wide. Current scale-cut approaches for mitigating baryon contamination result in a residual bias of $\approx 0.3\sigma$ in the $S_8, \Omega_{\rm m}$ posterior. Using all scales with dedicated baryon modeling leads to negligible improvement as the new information is used solely to self-calibrate the baryon model on small scales. Additional non-lensing datasets, and/or calibrations of the baryon model, will be required to access the full statistical power of the lensing measurements. The combined dataset in this work represents the largest lensing dataset to date (most galaxies, largest area) and provides an apt testing ground for analyses of upcoming datasets from Stage IV surveys. The DECADE shear catalogs, data vectors, and likelihoods are made publicly available.

Figures

Figures reproduced from arXiv: 2509.03582 by A. Alarcon, A. Amon, A. B. Pace, A. Carnero Rosell, A. Choi, A. Drlica-Wagner, A. H. Riley, A. J. Shajib, A. K. Vivas, A. N. Alsina, A. Porredon, A. Tong, A. Zenteno, B. Jain, B. Mutlu-Pakdil, B. Yanny, B. Yin, C. Chang, C. Doux, C. E. Mart\'inez-V\'azquez, C. R. Bom, C. To, C. Y. Tan, D. Anbajagane, D. Gruen, D. J. James, D. J. Sand, D. Sanchez-Cid, D. Suson, E. J. Tollerud, E. Krause, E. M. Huff, E. S. Rykoff, F. Andrade-Oliveira, G. E. Medina, G. Giannini, G. S. Stringfellow, H. Camacho, I. Sevilla-Noarbe, J. A. Carballo-Bello, J. A. Frieman, J. Blazek, J. D. Sakowska, J. Elvin-Poole, J. Esteves, J. McCullough, J. Myles, J. Prat, J. Zuntz, K. Eckert, K. Herner, K. Herron, L. F. Secco, L. Santana-Silva, M. Adamow, M. A. Troxel, M. Gatti, M. Jarvis, M. Navabi, M. Raveri, M. R. Becker, M. Soares-Santos, M. Yamamoto, N. Chicoine, N. E. D. No\"el, N. Kuropatkin, P. Massana, P. S. Ferguson, R. A. Gruendl, R. Cawthon, R. Teixeira, S. Dodelson, S. Mau, S. Pandey, S. Samuroff, T. Shin, W. Cerny, W. G. Hartley, Y. Choi, Y. Zhang, Z. Zhang.

Figure 1
Figure 1. Figure 1: FIG. 1. The footprint of the [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. The [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. The constraints on two dynamical dark energy models — the phenomological [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. The baryonic suppression at [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. The [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6. The [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: FIG. 7. All [PITH_FULL_IMAGE:figures/full_fig_p012_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8. The redshift distribution for each of the four tomographic bins for galaxies in the [PITH_FULL_IMAGE:figures/full_fig_p018_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: FIG. 9. The constraints from the [PITH_FULL_IMAGE:figures/full_fig_p019_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: FIG. 10. The impact of fixing cosmology priors in the baryon model. [PITH_FULL_IMAGE:figures/full_fig_p020_10.png] view at source ↗
Figure 12
Figure 12. Figure 12: FIG. 12. The [PITH_FULL_IMAGE:figures/full_fig_p021_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: FIG. 13. The suppression from the [PITH_FULL_IMAGE:figures/full_fig_p021_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: FIG. 14. Comparison of our inferred suppression (Figure [PITH_FULL_IMAGE:figures/full_fig_p022_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: FIG. 15. The intrinsic alignment (IA) constraints of different datasets, for the fiducial DECam 13k analysis (blue), using all scales (red), and [PITH_FULL_IMAGE:figures/full_fig_p023_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: FIG. 16. The measured [PITH_FULL_IMAGE:figures/full_fig_p024_16.png] view at source ↗

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Reference graph

Works this paper leans on

18 extracted references · 17 canonical work pages · cited by 4 Pith papers

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    Baryon suppression of the matter power spectrum Figure 4 presents the baryon suppression of the matter power spectrum predicted by each model. This is shown for our fiducial analysis using the DECam 13k data, and for the extendedanalysiswhichaddsBAOandSNeinformationtothe WLdata. Constraintsfromthetwodifferentdatacombinations are consistent with each other...

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    Cosmology with scale cuts and with all scales Havingestablishedconcordanceinthebaryonsuppres- sion constraints from different models, we now turn to the effectiveness of scale cuts in mitigating baryon-driven biases in the inferred cosmology. For simplicity, we only consider the BCEmu model for this analysis. We quantify the baryon- drivenbiasbyanalyzingt...

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    DECam 13k + Ext, BFG-HMx 0.25 0.50 Ω m 0.5 1.0 σ8 FIG. 7. AllΛCDM constraints from this work, in comparison to external constraints (lines 8-15) and to variations of different baryon models. The gray bands show the1𝜎 and 2𝜎 regions of the fiducial results (line 5, DECam 13k). The numerical constraints are listed in Table III. KiDS-Legacy only quotes const...

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  17. [2023]

    No baryons

    with the halo density profiles assumed by each of these models (HMx, BCEmu, and Bacco). These predictions are derivedusingthe BaryonForge3 codebase(Anbajaganeetal. 2024a), where we have implemented all profiles from these models. Wethenbuildanemulatorforthebaryonsuppression thatspansbothastrophysicalnuisanceparametersandcosmol- ogyparameters. Allhalo-mode...

    work page 2019

  18. [2025]

    la Caixa

    or by utilizing more stringent selections on the source galaxy sample (McCullough et al. 2024). The uncertainties from redshift calibration are negligible relative to the other two; though, we note this is also becauseDECADEand DES Y3dataareshallowerthanthedatafromDESY6(Yamamoto &Beckeretal.2025)andtheupcomingLSSTY1release. The calibration uncertainties w...

    arXiv 2024

This paper was first reviewed by deepseek-v4-flash on August 5, 2026.