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arxiv: 2606.23781 · v1 · pith:BGIO434Qnew · submitted 2026-06-22 · 🌌 astro-ph.CO

Accurate modeling for 3times2pt analyses in Roman and Rubin: a study of model approximations

Junzhou Zhang , Chihway Chang , Jiachuan Xu , Vivian Miranda , Chun-Hao To , Haley Bowden , Kaili Cao , Tim Eifler
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Roman HLIS Cosmology PIT
This is my paper

Pith reviewed 2026-06-26 07:11 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords 3x2pt analysisLimber approximationredshift-space distortionsnonlinear power spectrumRoman Space TelescopeRubin Observatorycosmological constraintsmodeling biases
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The pith

Neglecting Limber approximation, redshift-space distortions or nonlinear power spectrum models biases Roman and Rubin 3x2pt constraints by 1-2 sigma.

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

The paper investigates the impact of three common modeling approximations on 3x2pt analyses for the Roman and Rubin surveys. Using simulated likelihood analyses, it shows that each approximation can lead to significant biases in cosmological parameters. The study validates the modeling pipeline and examines how survey configurations influence the results.

Core claim

Neglecting any of the three approximations—Limber, redshift-space distortions, or less accurate nonlinear power spectrum—can induce biases in cosmological constraints approaching or exceeding 1σ, and exceeding 2σ for Rubin in several cases.

What carries the argument

Simulated likelihood analysis comparing full modeling to cases where one approximation is applied at a time, for 3x2pt correlations in Roman and Rubin surveys.

If this is right

  • Biases from these approximations must be accounted for to achieve unbiased cosmology from Stage-IV surveys.
  • Redshift-space distortions are particularly important to include for lens galaxy samples.
  • Different scale cuts and lens sample choices can change the magnitude of the biases.
  • The choice of nonlinear matter power spectrum model affects the accuracy of constraints.

Where Pith is reading between the lines

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

  • If the biases are as large as simulated, survey teams will need to adopt full modeling without these approximations for final analyses.
  • This may require more computational resources but could prevent misinterpretation of dark energy or other parameters.
  • Similar effects might appear in other large-scale structure probes beyond 3x2pt.

Load-bearing premise

The simulated likelihood analysis and the specific lens-galaxy sample configurations accurately capture the biases that would appear in real data analyses for Roman and Rubin.

What would settle it

Comparing cosmological constraints from real Roman or Rubin data using both the approximated models and the full model without approximations to see if parameter shifts match the simulated ones.

Figures

Figures reproduced from arXiv: 2606.23781 by Chihway Chang, Chun-Hao To, Haley Bowden, Jiachuan Xu, Junzhou Zhang, Kaili Cao, Roman HLIS Cosmology PIT, Tim Eifler, Vivian Miranda.

Figure 1
Figure 1. Figure 1: — These plots show the redshift distributions of galaxy samples for Roman (left) and Rubin (right) used in this work, as defined in Section 3.1 and 3.2. TABLE 1 The survey settings for Roman HLIS-Y5 and Rubin LSST-Y10. For Roman HLIS-Y5, its survey area corresponds to the medium tier. We assume both surveys use the Rubin LSST-Y10 lens sample, the number density of which decreases from 48 to 30 arcmin−2 aft… view at source ↗
Figure 2
Figure 2. Figure 2: — This figure shows the bias significance of data vector between two pipelines over the angular scale: CCL and CoCoA. The data vector difference is first computed and then divided by the square root of diagonal term of data vector covariance matrix to get the significance of bias. Each of the four subplots represents a probe, including (ξ +, ξ−, γt, w). Only part of the correlations are shown in the figure… view at source ↗
Figure 3
Figure 3. Figure 3: — ∆χ 2 of 3×2pt simulated by CosmoLike and CCL with varying cosmologies over Ωm − σ8. The red lines with numbers are ∆χ 2 contours over cosmologies. The red cross represents our fiducial cosmology. model) and approximations (RSD and non-Limber) that are used in this analysis. For the real-space data vectors with and without fidu￾cial scale cuts, we find, ∆χ 2 fid−cut(ξ ±, γt,w, 3 × 2pt)Roman = (0.004, 0.00… view at source ↗
Figure 4
Figure 4. Figure 4: — This plot compares data vectors of four scenarios with our Baseline, including Limber, noRSD, HMCode, and Limber-noRSD-HMCode. The difference of data vectors is measured by the diagonal components of the data vector covariance matrix as (Scenario − Baseline)/ p Diag(Cov), illustrating the significance of bias. The upper figure is for Roman HLIS-Y5 in real space while the lower is for that in harmonic spa… view at source ↗
Figure 5
Figure 5. Figure 5: — This plot compares data vectors of four scenarios, as described in [PITH_FULL_IMAGE:figures/full_fig_p012_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: — This plot shows S8 − Ωm constraints of five scenarios, including Baseline, Limber, noRSD, HMCode, and Limber-noRSD-HMCode, for survey Roman HLIS-Y5. The contours enclose a 68% credible region. The colored crosses represent the posterior means of scenarios, while the gray cross-hair represents the parameter value of the fiducial cosmology. 0.30 0.33 0.83 0.84 S8 Real Rubin LSST-Y10 0.30 0.33 Harmonic m Ba… view at source ↗
Figure 7
Figure 7. Figure 7: — This plot shows S8 −Ωm constraints of five scenarios as described in [PITH_FULL_IMAGE:figures/full_fig_p013_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: — Lens and source redshift distributions of scenarios discussed in Appendix B. TABLE 5 This table shows FoMs of probes (columns 2-4) and the number densities of lens and source samples (columns 5-6) for scenarios discussed in Appendix B. FoMs are calculated based on the area of Ωm − σ8 plane with 68% credible region. The number density is in units of arcmin−2 . FoMs | neff 3 × 2pt cosmic shear 2 × 2pt lens… view at source ↗
Figure 9
Figure 9. Figure 9: — The left three panels compare the posterior mean of parameters σ8, Ωm, and S8, under different scenarios which are explained in Appendix C. The vertical black solid line represents the input fiducial, while the blue horizontal line is the posterior mean of our baseline, the difference between the two shows the level of projection effect. The rightmost plot shows the FoM defined in the plane of parameter … view at source ↗
read the original abstract

One of the pillars of modern cosmology is the use of galaxy imaging surveys to extract information from the large-scale structure. In recent surveys, this measurement is typically performed through a 3$\times$2pt analysis, which combines auto- and cross-correlations between galaxy density and galaxy weak lensing. In this paper, we carry out a systematic study of three modeling approximations commonly used in such analyses: 1) applying the Limber approximation, 2) neglecting redshift-space distortions, and 3) using less accurate models for the nonlinear matter power spectrum. We carry out the study in the context of the final data from two major Stage-IV galaxy imaging surveys: the Nancy Grace Roman Space Telescope's High Latitude Imaging Survey and the Vera C. Rubin Observatory's Legacy Survey of Space and Time. To do this, we first validate our modeling pipeline, implemented in the software package CoCoA, against an established code base, CCL. Next, we perform a simulated likelihood analysis to assess the impact of these approximations on the cosmological constraints. We find all three effects to be important; neglecting any of them can induce biases in cosmological constraints approaching or exceeding $1\sigma$, and exceeding $2\sigma$ for Rubin in several cases. Moreover, we explore how the lens-galaxy sample configuration and scale-cut choice can influence the constraints.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper validates a 3×2pt modeling pipeline (CoCoA) against CCL and performs simulated likelihood analyses for Roman and Rubin surveys. It concludes that neglecting the Limber approximation, redshift-space distortions, or accurate nonlinear matter power spectrum modeling can induce biases in cosmological constraints of order 1σ or larger (exceeding 2σ for Rubin in several cases), with additional exploration of how lens-galaxy sample configuration and scale cuts affect the results.

Significance. If the central results hold, the work supplies concrete, survey-specific guidance on the modeling accuracy required for Stage-IV 3×2pt analyses, helping to avoid parameter biases in Roman and Rubin data. The explicit validation against CCL and the systematic variation of lens-sample and scale-cut choices are strengths that make the findings actionable for the community.

major comments (2)
  1. [Simulated likelihood analysis] Simulated likelihood section: the headline bias amplitudes (approaching or exceeding 1–2σ) are obtained from a specific choice of lens-galaxy redshift distributions, number densities, and scale cuts. Because the abstract itself states that these choices influence the constraints, the manuscript must show that the reported bias levels remain at the quoted magnitude for at least one additional set of configurations that bracket the expected final Roman and Rubin analysis choices; otherwise the quantitative claim is configuration-dependent rather than general.
  2. [Validation section] Validation against CCL: the text states that the pipeline was validated, but does not report quantitative agreement metrics (e.g., fractional differences in C_ℓ or parameter shifts) for the exact modeling choices used in the bias study. This information is needed to confirm that the reported biases are not partly artifacts of residual discrepancies between CoCoA and CCL.
minor comments (2)
  1. [Tables] Table captions should explicitly state the cosmological parameters varied and the priors used in the simulated likelihood runs.
  2. [Introduction] The notation for the three approximations (Limber, RSD, nonlinear P(k)) should be introduced once with a consistent abbreviation list.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments on our manuscript. We address each major comment point by point below and outline the revisions we will make.

read point-by-point responses

  1. Referee: [Simulated likelihood analysis] Simulated likelihood section: the headline bias amplitudes (approaching or exceeding 1–2σ) are obtained from a specific choice of lens-galaxy redshift distributions, number densities, and scale cuts. Because the abstract itself states that these choices influence the constraints, the manuscript must show that the reported bias levels remain at the quoted magnitude for at least one additional set of configurations that bracket the expected final Roman and Rubin analysis choices; otherwise the quantitative claim is configuration-dependent rather than general.

    Authors: We agree that the quantitative bias levels are configuration-dependent and that the abstract highlights the influence of these choices. The manuscript already varies lens-galaxy sample configurations and scale cuts to demonstrate their effects. However, to strengthen the generality of the headline claims, we will add results for at least one additional set of configurations that bracket the expected final Roman and Rubin analysis choices. These will be presented in a revised version of the simulated likelihood section. revision: yes

  2. Referee: [Validation section] Validation against CCL: the text states that the pipeline was validated, but does not report quantitative agreement metrics (e.g., fractional differences in C_ℓ or parameter shifts) for the exact modeling choices used in the bias study. This information is needed to confirm that the reported biases are not partly artifacts of residual discrepancies between CoCoA and CCL.

    Authors: We agree that quantitative agreement metrics are necessary to substantiate the validation. While the manuscript states that CoCoA was validated against CCL, specific numerical metrics (such as fractional differences in C_ℓ or parameter shifts) for the exact modeling choices in the bias study were not reported. We will add these quantitative metrics to the validation section in the revised manuscript to confirm that residual discrepancies do not affect the reported biases. revision: yes

Circularity Check

0 steps flagged

No significant circularity; results from external validation and simulated likelihoods

full rationale

The paper validates its CoCoA pipeline against the independent external code CCL, then computes biases via simulated likelihoods on explicitly chosen lens samples and scale cuts. No equations reduce reported biases to parameters defined inside the paper, no predictions are statistically forced by fits, and no load-bearing self-citations or uniqueness theorems are invoked. The quantitative 1-2σ claims are direct outputs of the simulation pipeline rather than self-referential constructions, satisfying the criteria for a self-contained analysis against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

No free parameters, axioms, or invented entities are described in the abstract; the work is an empirical comparison of existing modeling choices.

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discussion (0)

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Reference graph

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