A modern halo streaming model for redshift space distortions

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ID: 330059
2026
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Abstract
Abstract Accurate modelling of redshift-space distortions (RSD) in galaxy clustering is essential for extracting cosmological information from current and forthcoming large-scale structure surveys. While perturbation theory is reliable on large scales, much of the constraining power lies at intermediate and small separations, where nonlinear dynamics within and between dark matter haloes dominate. We present a halo streaming model for nonlinear galaxy clustering in redshift space that is accurate and physically interpretable. Our framework combines the streaming model for RSD with a halo-model decomposition of the galaxy clustering into central/satellite and one-/two-halo contributions. We build dedicated emulators for the key physical ingredients, trained on a suite of N-body simulations: halo mass functions, real-space halo two-point correlation functions, and pairwise velocity moments. By emulating these modular building blocks rather than the final redshift-space observable, this approach preserves physical transparency, enables targeted optimisation for each ingredient, and remains flexible to changes in tracer populations and galaxy-halo connection models. The resulting halo streaming model reproduces the simulated nonlinear anisotropic clustering signal down to highly nonlinear scales, while achieving the computational efficiency required for cosmological parameter inference. This framework is designed to support full-shape RSD analyses for surveys such as DESI and Euclid, facilitating precision measurements of structure growth and tests of gravity. All codes and trained emulators are publicly available in the freyja repository.
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openalex_W7135048489 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Cheng-Zong Ruan, Baojiu Li, C. M. Baugh, Sownak Bose, Alexander Eggemeier, David F. Mota
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Journal monthly notices of the royal astronomical society
Year 2026
DOI
10.1093/mnras/stag1842
URL
https://doi.org/10.1093/mnras/stag1842
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