The Impacts of Modeling Choices on the Inference of the Circumgalactic
  Medium Properties from Sunyaev-Zeldovich Observations
  As the signal-to-noise of Sunyaev-Zeldovich (SZ) cross-correlation
measurements of galaxies improves our ability to infer properties about the
circumgalactic medium (CGM), we will transition from being limited by
statistical uncertainties to systematic uncertainties. Using thermodynamic
profiles of the CGM created from the IllustrisTNG (The Next Generation)
simulations we investigate the importance of specific choices in modeling the
galaxy sample. These choices include different sample selections in the
simulation (stellar versus halo mass, color selections) and different fitting
models (matching by the shape of the mass distribution, inclusion of a two-halo
term). We forward model a mock galaxy sample into projected SZ observable
profiles and fit these profiles to a generalized Navarro-Frenk-White profile
using forecasted errors of the upcoming Simons Observatory experiment. We test
the number of free parameters in the fits and show that this is another
modeling choice that yields different results. Finally, we show how different
fitting models can reproduce parameters of a fiducial profile, and show that
the addition of a two-halo term and matching by the mass distribution of the
sample are extremely important modeling choices to consider.
