A Hydro-particle-mesh Code for Efficient and Rapid Simulations of the Intracluster Medium

He, Yizhou; Trac, Hy; Gnedin, Nickolay Y.

doi:10.3847/1538-4357/ac3bcb

Title: A Hydro-particle-mesh Code for Efficient and Rapid Simulations of the Intracluster Medium

Journal Article · 31 January 2022 · The Astrophysical Journal

DOI: https://doi.org/10.3847/1538-4357/ac3bcb · OSTI ID:1834795

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Carnegie Mellon Univ., Pittsburgh, PA (United States). McWilliams Center for Cosmology
Carnegie Mellon Univ., Pittsburgh, PA (United States). McWilliams Center for Cosmology; Carnegie Mellon Univ., Pittsburgh, PA (United States). NSF AI Planning Institute for Physics of the Future
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Univ. of Chicago, IL (United States). Kavli Inst. for Cosmological Physics (KICP); Univ. of Chicago, IL (United States)

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 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.

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Research Organization:: Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)

Sponsoring Organization:: National Science Foundation (NSF); Pittsburgh Supercomputing Center; USDOE Office of Science (SC), High Energy Physics (HEP)

Grant/Contract Number:: AC02-07CH11359

OSTI ID:: 1834795

Report Number(s):: FERMILAB-PUB--21-662-T; arXiv:2107.04606; oai:inspirehep.net:1881786

Journal Information:: The Astrophysical Journal, Journal Name: The Astrophysical Journal Journal Issue: 2 Vol. 925; ISSN 0004-637X

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United States

Language:: English

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Title: A Hydro-particle-mesh Code for Efficient and Rapid Simulations of the Intracluster Medium

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