Accurate modeling for 3 times 2pt 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, Roman HLIS Cosmology PIT
astro-ph.CO
Submitted: 2026-06-22
Comments: 18 pages, 9 figures, 5 tables
Code: https://github.com/CosmoLike/cocoa
License: http://creativecommons.org/licenses/by/4.0/
The gist: One of the pillars of modern cosmology is the use of galaxy imaging surveys to extract information from the large-scale structure.
Terminology
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.
Sources
- Machine Learning LSST 3x2pt analyses -- forecasting the impact of systematics on cosmological constraints using neural networks
- Fisher Forecasts for Cosmological Yields from 3! times!2 pt Analysis of the Roman Space Telescope High Latitude Imaging Survey
- The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document
- Dark Energy Survey Year 6 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing
- Dark Energy Survey Year 1 Results: Multi-Probe Methodology and Simulated Likelihood Analyses
- Dark Energy Survey Year 6 Results: Weak Lensing and Galaxy Clustering Cosmological Analysis Framework
- Constraining baryonic feedback and cosmology from DES Y3 and Planck PR4 6$\times$2pt data. I. $\Lambda$CDM models
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