The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations
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...
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Oxford University Press (OUP)
2022
|
| Online Access: | https://hdl.handle.net/1721.1/142402 |
| _version_ | 1811074990884257792 |
|---|---|
| author | Li, Hui Vogelsberger, Mark Marinacci, Federico Sales, Laura V Torrey, Paul |
| author2 | Massachusetts Institute of Technology. Department of Physics |
| author_facet | Massachusetts Institute of Technology. Department of Physics Li, Hui Vogelsberger, Mark Marinacci, Federico Sales, Laura V Torrey, Paul |
| author_sort | Li, Hui |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T09:58:38Z |
| format | Article |
| id | mit-1721.1/142402 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:58:38Z |
| publishDate | 2022 |
| publisher | Oxford University Press (OUP) |
| record_format | dspace |
| spelling | mit-1721.1/1424022023-04-14T18:35:30Z The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations Li, Hui Vogelsberger, Mark Marinacci, Federico Sales, Laura V Torrey, Paul Massachusetts Institute of Technology. Department of Physics MIT Kavli Institute for Astrophysics and Space Research 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. 2022-05-06T17:01:56Z 2022-05-06T17:01:56Z 2020 2022-05-06T16:57:54Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/142402 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). en 10.1093/MNRAS/STAA3122 Monthly Notices of the Royal Astronomical Society Attribution-NonCommercial-ShareAlike 4.0 International https://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Oxford University Press (OUP) arXiv |
| spellingShingle | Li, Hui Vogelsberger, Mark Marinacci, Federico Sales, Laura V Torrey, Paul The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations |
| title | The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations |
| title_full | The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations |
| title_fullStr | The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations |
| title_full_unstemmed | The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations |
| title_short | The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations |
| title_sort | effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations |
| url | https://hdl.handle.net/1721.1/142402 |
| work_keys_str_mv | AT lihui theeffectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations AT vogelsbergermark theeffectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations AT marinaccifederico theeffectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations AT saleslaurav theeffectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations AT torreypaul theeffectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations AT lihui effectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations AT vogelsbergermark effectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations AT marinaccifederico effectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations AT saleslaurav effectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations AT torreypaul effectsofsubgridmodelsonthepropertiesofgiantmolecularcloudsingalaxyformationsimulations |