Speaker
Description
As part of the Learning the Universe collaboration, we have pushed the CAMELS-SAM simulation suite into observational photometric space, and present initial results for constraints on cosmological and astrophysical parameters for galaxy population statistics for the SDSS Main Galaxy Sample. CAMELS-SAM already included more than 1000 N-body simulations of (100 cMpc)$^3$, covering a vast cosmological parameter space in $\Omega_M$ and $\sigma_8$. Our new and unique forward-model combines: the CAMELS-SAM simulations and framework with the Santa Cruz semi-analytic model for galaxy formation (varying several new parameters for galaxy formation processes); the powerful and flexible Synthesizer software to model synthetic astrophysical observables for simulated galaxies; and physically-motivated analyses for galaxy dust attenuation. With these components, we test how clustering statistics and other galaxy population statistics perform in a simulation-based inference pipeline directly in the observed lightcone. We present initial results and lessons learned in this ambitious application of SBI and galaxy forward modeling, and discuss how it can be scaled up for the next generation of galaxy surveys. Finally, we detail the value of the expanded CAMELS-SAM simulation suite for the testing and development of new field-level methods for galaxy surveys.