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On the simultaneous modelling of dust and stellar populations for interpretation of galaxy properties.
- Source :
- Monthly Notices of the Royal Astronomical Society; Aug2022, Vol. 514 Issue 4, p5706-5724, 19p
- Publication Year :
- 2022
-
Abstract
- The physical properties of galaxies are encoded within their spectral energy distribution and require comparison with models to be extracted. These models must contain a synthetic stellar population and, where infrared data are to be used, also consider prescriptions for energy reprocessing and re-emission by dust. While many such models have been constructed, there are few analyses of the impact of stellar population model choice on derived dust parameters, or vice versa. Here, we apply a simple framework to compare the impact of these choices, combining three commonly used stellar population synthesis models and three dust emission models. We compare fits to the ultraviolet to far-infrared spectral energy distributions of a validation sample of infrared-luminous galaxies. We find that including different physics, such as binary stellar evolution, in the stellar synthesis model can introduce biases and uncertainties in the derived parameters of the dust and stellar emission models, largely due to differences in the far-ultraviolet emission available for reprocessing. This may help to reconcile the discrepancy between the cosmic star formation rate and stellar mass density histories. Notably the inclusion of a dusty stellar birth cloud component in the dust emission model provides more flexibility in accommodating the stellar population model, as its re-emission is highly sensitive to the ultraviolet radiation field spectrum and density. Binary populations favour a longer birth cloud dissipation time-scale than is found when assuming only single star population synthesis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00358711
- Volume :
- 514
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Monthly Notices of the Royal Astronomical Society
- Publication Type :
- Academic Journal
- Accession number :
- 158209749
- Full Text :
- https://doi.org/10.1093/mnras/stac1667