We investigate the impact of bursty star formation on several galaxy scaling relations of dwarf galaxies using the $\texttt{GRUMPY}$ galaxy formation model. While this model reproduces the star formation rate (SFR)-stellar mass, stellar mass-gas mass, and stellar mass-metallicity relations, the scatter of these relations in the original model is smaller than observed. We explore the effects of additional stochasticity of SFR on the scaling relations using a model that reproduces the level of SFR burstiness in high-resolution zoom-in simulations. The additional SFR stochasticity increases the scatter in the SFR-stellar mass relation to a level similar to that exhibited by most nearby dwarf galaxies. The most extreme observed starbursting dwarfs, however, require higher levels of SFR stochasticity. We find that bursty star formation increases the scatter in the colour-magnitude distribution (CMD) for brighter dwarf galaxies $(M_V < -12)$ to the observed level, but not for fainter ones for which scatter remains significantly smaller than observed. This is due to the predominant old stellar populations in these faint model galaxies and their generally declining SFR over the past 10 Gyrs, rather than quenching caused by reionization. We examine the possibility that the colour scatter is due to scatter in metallicity, but show that the level of scatter required leads to an overestimation of scatter in the metallicity-mass relation. This illustrates that the scatter of observed scaling relations in the dwarf galaxy regime represents a powerful constraint on the properties of their star formation.
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Characterizing the Conditional Galaxy Property Distribution Using Gaussian Mixture Models
Line-intensity mapping (LIM) is a promising technique to constrain the global distribution of galaxy properties. To combine LIM experiments probing different tracers with traditional galaxy surveys and fully exploit the scientific potential of these observations, it is necessary to have a physically motivated modeling framework. As part of developing such a framework, in this work, we introduce and model the conditional galaxy property distribution (CGPD), i.e., the distribution of galaxy properties conditioned on the host halo mass and redshift. We consider five galaxy properties, including the galaxy stellar mass, molecular gas mass, galaxy radius, gas-phase metallicity, and star formation rate (SFR), which are important for predicting the emission lines of interest. The CGPD represents the full distribution of galaxies in the five-dimensional property space; many important galaxy distribution functions and scaling relations, such as the stellar mass function and SFR main sequence, can be derived from integrating and projecting it. We utilize two different kinds of cosmological galaxy simulations, a semi-analytic model and the IllustrisTNG hydrodynamic simulation, to characterize the CGPD and explore how well it can be represented using a Gaussian mixture model (GMM). We find that with just a few (approximately three) Gaussian components, a GMM can describe the CGPD of the simulated galaxies to high accuracy for both simulations. The CGPD can be mapped to LIM or other observables by constructing the appropriate relationship between galaxy properties and the relevant observable tracers, which will be discussed in future works.
more » « less- PAR ID:
- 10424041
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 950
- Issue:
- 2
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 159
- Size(s):
- Article No. 159
- Sponsoring Org:
- National Science Foundation
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