SimBIG: mock challenge for a forward modeling approach to galaxy clustering

Abstract

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 k max = 0.5 h/Mpc and infer the posterior of ΛCDM cosmological and halo occupation parameters. Based on the mock challenge, we find that our constraints on Ω m and σ 8 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.

Analysis of BOSS galaxy data with weighted skew-spectra

“…Secondly, we perform a high-dimensional numerical integral in order to obtain our theory skew-spectra, which is a time-consuming task and therefore prevents us from varying the full νΛCDM parameters simultaneously in the likelihood analysis. This could be potentially accomplished with help of simulation-based inference methods [82][83][84][85][86]. For example, a related recent work [56] uses the SIMBIG forward modelling framework to perform simulation-based inference with skew-spectra through normalizing flows.…”

EFTofLSS meets simulation-based inference: σ 8 from biased tracers

“…Although not particular to SBI, forward modeling presents several advantages over other methods, such as the straightforward inclusion of observational effects, including window functions, redshift-space distortions and systematic effects [46,57,[65][66][67][68]. In the context of the EFT forward model employed here, forward modeling at the field-level allows us to reach essentially arbitrary perturbative (loop) order [69].…”

“…In the context of galaxy clustering, recent progress has been made by using graphs networks to capture the map information from the galaxy distribution [22,23]. SBI has been widely used in the cosmological inference context, including weak-lensing [24][25][26][27], type IA supernovae [24,25,[28][29][30][31][32], standard sirens [33,34], CMB [35,36], galaxy cluster abundance [37], Gaussian and lognormal fields [38][39][40][41], dark-matter overdensity fields [40,42], voids [43], dark-matter halos [23,44] and galaxies [45][46][47][48].…”

Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite

“…Therefore, expanding this project to observed galaxy clustering requires first robustly generating realistic galaxies from the properties the SC-SAM produces. This would entail selecting a galaxy sample that CAMELS-SAM is large and resolved enough to simulate (e.g., perhaps the 2D clustering of emission line galaxies in a small but well-studied field like COSMOS; Khostovan et al 2018), as well as a detailed understanding of the selection function and observational systematics for the sample (such as, e.g., Hahn et al 2022Hahn et al , 2023 include in their forward model for BOSS CMASS galaxies). Additionally, expanding to other SAMs (and their unique parameterization of galaxy physics) could improve the neural networks' ability to marginalize over many forms of astrophysical prescriptions and better constrain Ω M and σ 8 for similar galaxy selections.…”