摘要: We introduce the cosmological HYPER code based on an innovative
hydro-particle-mesh (HPM) algorithm for efficient and rapid simulations of gas
and dark matter. For the HPM algorithm, we update the approach of Gnedin & Hui
(1998) to expand the scope of its application from the lower-density
intergalactic medium (IGM) to the higher-density intracluster medium (ICM).
While the original algorithm tracks only one effective particle species, the
updated version separately tracks the gas and dark matter particles as they do
not exactly trace each other on small scales. For the approximate hydrodynamics
solver, the pressure term in the gas equations of motion is calculated using
robust physical models. In particular, we use a dark matter halo model, ICM
pressure profile, and IGM temperature-density relation, all of which can be
systematically varied for parameter-space studies. We show that the HYPER
simulation results are in good agreement with the halo model expectations for
the density, temperature, and pressure radial profiles. Simulated galaxy
cluster scaling relations for Sunyaev-Zel'dovich (SZ) and X-ray observables are
also in good agreement with mean predictions, with scatter comparable to that
found in hydrodynamic simulations. HYPER also produces lightcone catalogs of
dark matter halos and full-sky tomographic maps of the lensing convergence, SZ
effect, and X-ray emission. These simulation products are useful for testing
data analysis pipelines, generating training data for machine learning,
understanding selection and systematic effects, and for interpreting
astrophysical and cosmological constraints.