Cold Gas Subgrid Model (CGSM): A two-fluid framework for modeling unresolved cold gas in galaxy simulations

Creators: Butsky, Iryna S.^{1, 2, 3}; Hummels, Cameron B.²; Hopkins, Philip F.²; Quinn, Thomas R.³; Werk, Jessica K.³

1. Kavli Institute for Particle Astrophysics and Cosmology
2. California Institute of Technology
3. University of Washington

Abstract

The cold (∼10⁴ K) component of the circumgalactic medium (CGM) accounts for a significant fraction of all galactic baryons. However, using current galaxy-scale simulations to determine the origin and evolution of cold CGM gas poses a significant challenge, since it is computationally infeasible to directly simulate a galactic halo alongside the sub-pc scales that are crucial for understanding the interactions between cold CGM gas and the surrounding 'hot' medium. In this work, we introduce a new approach: the Cold Gas Subgrid Model (CGSM), which models unresolved cold gas as a second fluid in addition to the standard 'normal' gas fluid. The CGSM tracks the total mass density and bulk momentum of unresolved cold gas, deriving the properties of its unresolved cloudlets from the resolved gas phase. The interactions between the subgrid cold fluid and the resolved fluid are modeled by prescriptions from high-resolution simulations of 'cloud crushing' and thermal instability. Through a series of idealized tests, we demonstrate the CGSM's ability to overcome the resolution limitations of traditional hydrodynamics simulations, successfully capturing the correct cold gas mass, its spatial distribution, and the timescales for cloud destruction and growth. We discuss the implications of using this model in cosmological simulations to more accurately represent the microphysics that govern the galactic baryon cycle.

Copyright and License

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Acknowledgement

We thank the referee, Rainer Weinberger, for constructive comments and suggestions that improved this manuscript. The authors would also like to thank Greg Bryan, Drummond Fielding, Matthew Smith, and Peng Oh for insightful conversations that contributed to the development of ideas presented in this paper. ISB was supported by HST Legacy grant AR-15800, the DuBridge Postdoctoral Fellowship at Caltech, and by NASA through the Hubble Fellowship, grant HST-HF2-51525.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS 5–26555. CBH is supported by NSF grant AAG-1911233, and NASA grants 80NSSC23K1515, HST-AR-15800, HSTAR-16633, and HST-GO-16703. Support for PFH was provided by NSF Research grants 1911233 and 20009234, NSF CAREER grant 1455342, and NASA grants 80NSSC18K0562 and HST-AR-15800.001-A.

Data Availability

The data supporting this article and CGSM source code are available on reasonable request to the corresponding author.

Software References

The CGSM was implemented in the enzo astrophysical simulation code (Bryan et al. 2014; Brummel-Smith et al. 2019). The analysis of the simulations relied heavily on the yt (Turk et al. 2011), matplotlib (Hunter 2007), and numpy (Harris et al. 2020) packages for the python (Perez & Granger 2007) programming language.

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