SIMBIG: Mock Challenge for a Forward Modeling Approach to Galaxy Clustering

Simulation-Based Inference of Galaxies (SIMBIG) is a forward modeling framework for analyzing galaxy clustering using simulation-based inference. In this work, we present the SIMBIG forward model, which is designed to match the observed SDSS-III BOSS CMASS galaxy sample. The forward model is based on high-resolution QUIJOTE N-body simulations and a flexible halo occupation model. It includes full survey realism and models observational systematics such as angular masking and fiber collisions. We present the "mock challenge" for validating the accuracy of posteriors inferred from SIMBIG using a suite of 1,500 test simulations constructed using forward models with a different N-body simulation, halo finder, and halo occupation prescription. As a demonstration of SIMBIG, we analyze the power spectrum multipoles out to kmax=0.5h/Mpc and infer the posterior of ΛCDM cosmological and halo occupation parameters. Based on the mock challenge, we find that our constraints on Ωm and σ8 are unbiased, but conservative. Hence, the mock challenge demonstrates that SIMBIG provides a robust framework for inferring cosmological parameters from galaxy clustering on non-linear scales and a complete framework for handling observational systematics. In subsequent work, we will use SIMBIG to analyze summary statistics beyond the power spectrum including the bispectrum, marked power spectrum, skew spectrum, wavelet statistics, and field-level statistics.