__smbhome.uscs.susx.ac.uk_bw233_Desktop_SRO_SRO - Jon Loveday_10.1093-mnras-stx2131.pdf (1.41 MB)
Towards a consistent model for both the Hi and stellar mass functions of galaxies
journal contribution
posted on 2023-06-09, 08:43 authored by Hazel Martindale, Peter ThomasPeter Thomas, Bruno M Henriques, Jonathan LovedayJonathan LovedayUsing the L-Galaxies semi-analytic model we simultaneously fit the H?I mass function, stellar mass function and the fraction of red galaxies. We find good fits to all three observations at z = 0 and to the stellar mass function and red fraction at z = 2. Using Markov Chain Monte Carlo (MCMC) techniques we adjust the L-Galaxies parameters to best fit the constraining data. In order to fit the H?I mass function we must greatly reduce the gas surface density threshold for star formation, thus lowering the number of low H?I mass galaxies. A simultaneous reduction in the star formation efficiency prevents the overproduction of stellar content. A simplified model in which the surface density threshold is eliminated altogether also provides a good fit to the data. Unfortunately, these changes weaken the fit to the Kennicutt–Schmidt relation and raise the star formation rate density at recent times, suggesting that a change to the model is required to prevent accumulation of gas on to dwarf galaxies in the local Universe.
Funding
Astrophysics and Cosmology - Sussex Consolidated Grant; G1291; STFC-SCIENCE AND TECHNOLOGY FACILITIES COUNCIL; ST/L000652/1
History
Publication status
- Published
File Version
- Published version
Journal
Monthly Notices Of The Royal Astronomical SocietyISSN
0035-8711Publisher
Oxford University PressExternal DOI
Issue
2Volume
472Page range
1981-1990Department affiliated with
- Physics and Astronomy Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2017-11-07First Open Access (FOA) Date
2017-11-07First Compliant Deposit (FCD) Date
2017-11-07Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC