The neutral hydrogen (HI) in galaxies provides the gas reservoir out of which stars are formed. The ability to determine the HI masses for statistically significant samples of galaxies can provide information about the connection between this gas reservoir and the star formation that drives galaxy evolution. However, there are relatively few galaxies for which HI masses are known because these measurements are significantly more difficult to make than optical observations. Artificial neural networks are a type of nonlinear technique that have been used estimate the gas masses from their optical properties (Teimoorinia et al. 2017). We present HI observations of 51 galaxies with gas and stellar properties that are rare in the Arecibo Legacy Fast ALFA Survey (ALFALFA, Haynes et al. 2018) which was used to train the Artificial Neural Network developed by Teimoorinia et al. (ANN, 2017). These sources provide a test of the Artificial Neural Network predictions of HI mass and include some rare and interesting systems including galaxies that are extremely massive in both stellar mass (log M_∗> 11.0) and HI mass (log M_HI> 10.2) with large HI line widths (w_50> 500 km/s). We find that this Artificial Neural Network systematically overestimates the gas fraction of the galaxies in our selected sample, suggesting that care must be taken when using these techniques to predict gas masses for galaxies from a broad range of optical properties.
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A new technique to isolate kinematically anomalous gas in HI data cubes
HI line observations of nearby galaxies often reveal the presence of extraplanar and/or kinematically anomalous gas that deviates from the general circular flow. In this work, we study the dependence of kinematically anomalous HI gas in galaxies taken from the SIMBA cosmological simulation on galaxy properties such as HI mass fraction, specific star formation rate, and local environmental density. To identify kinematically anomalous gas, we use a simple yet effective decomposition method to separate it from regularly rotating gas in the galactic disc; this method is well-suited for application to observational data sets but has been validated here using the simulation. We find that at fixed atomic gas mass fraction, the anomalous gas fraction increases with the specific star formation rate. We also find that the anomalous gas fraction does not have a significant dependence on a galaxy’s environment. Our decomposition method has the potential to yield useful insights from future HI surveys.
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- Award ID(s):
- 1814421
- PAR ID:
- 10481853
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Volume:
- 518
- Issue:
- 4
- ISSN:
- 0035-8711
- Page Range / eLocation ID:
- 5942 to 5952
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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