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Fast, Accurate and Perturbative Forward Modeling of Galaxy Clustering Part I: Galaxies in the Restframe

2024/09/17 by J. Stadler, Stadler, Julia, Fabian Schmidt +3 · 4 citations
Economics, Econometrics and Finance · Physics and Astronomy · #Astronomy and Astrophysical Research #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Regional Economic and Spatial Analysis #Scientific Research and Discoveries

paper · pdf · doi:10.48550/arxiv.2409.10937

openalex publication_date 2024/09/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Forward models of the galaxy density field enable simulation based inference as well as field level inference of galaxy clustering. However, these analysis techniques require forward models that are both computationally fast and robust to modeling uncertainties in the relation between galaxies and matter. Both requirements can be addressed with the Effective Field Theory of Large Scale Structure. Here, we focus on the physical and numerical convergence of the LEFTfield model. Based on the perturbative nature of the forward model, we derive an analytic understanding of the leading numerical errors, and we compare our estimates to high-resolution and N-body references. This allows us to derive a set of best-practice recommendations for the numerical accuracy parameters, which are completely specified by the desired order of the perturbative solution and the cut-off scale. We verify these recommendations by an extended set of parameter recovery tests from fully nonlinear mock data and find very consistent results. A single evaluation of the forward model takes seconds, making cosmological analyses of galaxy clustering data based on forward models computationally feasible.

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