Sensitivity Analysis of the SimBIG-II Forward Model

Abstract

Simulation-based inference (SBI) has recently emerged as a promising avenue for inferring cosmological parameters from the 3D distribution of galaxies from large spectroscopic surveys (DESI, PFS, DESI-II). The first iteration of the SimBIG project demonstrated a proof-of-concept for this approach, using a forward-modeling pipeline built from high-fidelity QUIJOTE N-body simulations applied to a subset of the BOSS survey. The initial SimBIG results were promising, producing $H_0$ and $S_8$ constraints up to 1.5 and 1.9x tighter than traditional power spectra analyses. However, scaling this approach to larger survey volumes presents a major challenge, as the computational costs of high-resolution N-body simulations quickly becomes prohibitive. In this work, we present a scalable SimBIG-II approach. We leverage relatively inexpensive simulations from augmented Lagrangian perturbation theory (ALPT) with a highly flexible local and non-local bias prescription. We combine these simulations with a probabilistic emulator so that they retain the predictive power of N-body + HOD simulations. I will present the preliminary results of our sensitivity analysis of the SimBIG-II pipeline. Then, I will discuss the implications for our initial application to the full BOSS survey volume, as well as the subsequent SimBIG-II analyses of DESI galaxy samples.