Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations

The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations

Thumbnail Image
Download
Name

2001.07214.pdf

Description
Accepted version
Size

2.36 MB

Format

Adobe PDF

Checksum (MD5)

98b17dc0567161452012cf32105cdd64

sword-2022-05-06T16:57:54.original.xml (130 B)
Original SWORD entry document
Author(s)
Li, Hui
•
Vogelsberger, Mark
•
Marinacci, Federico
•
Sales, Laura V
•
Torrey, Paul
Date Issued
2020
Journal
Monthly Notices of the Royal Astronomical Society
Publisher
Oxford University Press (OUP)
Citation
Li, Hui, Vogelsberger, Mark, Marinacci, Federico, Sales, Laura V and Torrey, Paul. 2020. "The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations." Monthly Notices of the Royal Astronomical Society, 499 (4).
Version
Author's final manuscript
Abstract
Recent cosmological hydrodynamical simulations are able to reproduce numerous statistical properties of galaxies that are consistent with observational data. Yet, the adopted subgrid models strongly affect the simulation outcomes, limiting the predictive power of these simulations. In this work, we perform a suite of isolated galactic disc simulations under the SMUGGLE framework and investigate how different subgrid models affect the properties of giant molecular clouds (GMCs). We employ ASTRODENDRO, a hierarchical clump-finding algorithm, to identify GMCs in the simulations. We find that different choices of subgrid star formation efficiency, ϵff, and stellar feedback channels, yield dramatically different mass and spatial distributions for the GMC populations. Without feedback, the mass function of GMCs has a shallower power-law slope and extends to higher mass ranges compared to runs with feedback. Moreover, higher ϵff results in faster molecular gas consumption and steeper mass function slopes. Feedback also suppresses power in the two-point correlation function (TPCF) of the spatial distribution ofGMCs. Specifically, radiative feedback strongly reduces the TPCF on scales below 0.2 kpc, while supernova feedback reduces power on scales above 0.2 kpc. Finally, runs with higher ϵff exhibit a higher TPCF than runs with lower ϵff, because the dense gas is depleted more efficiently, thereby facilitating the formation of well-structured supernova bubbles. We argue that comparing simulated and observed GMC populations can help better constrain subgrid models in the next generation of galaxy formation simulations.
MIT Department
Massachusetts Institute of Technology. Department of Physics
MIT Kavli Institute for Astrophysics and Space Research
Terms of Use
Attribution-NonCommercial-ShareAlike 4.0 International
https://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/142402
DOI of Published Version
https://doi.org/10.1093/MNRAS/STAA3122
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.