Speaker
Description
The next generation of radio telescopes, such as the Square Kilometre Array, set to become the largest radio telescope in the world, will conduct surveys generating catalogues of millions of radio galaxies. Analysing and maximising the scientific return from these enormous astronomical datasets will require the development of innovative techniques.
The 21 cm neutral hydrogen (HI) emission line offers crucial insights into galaxies and the large-scale structure of the universe. However, accurately modelling this emission line is often challenging due to its intrinsically faint nature, especially in low signal-to-noise observations. Building on the work of Harrison, Lochner, and Brown (2017), we introduce an updated Bayesian framework for fitting the HI emission line using the entire Arecibo Legacy Fast ALFA (ALFALFA) catalogue. Our results indicate that foreground interference from our Milky Way galaxy and radio frequency interference pose a significant challenge for accurately measuring the HI line profile. We also demonstrate the effectiveness of using the Bayesian fitting method by comparing the recovered heliocentric velocity and line width with those in the ALFALFA catalogue. To date, we have tested the method on ten thousand ALFALFA galaxies, with advantages of the Bayesian approach being further highlighted through the use of the evidence term. The presentation will detail our modelling approach, highlight the broader implications for understanding galaxy properties and dynamics, as well as outline potential applications for upcoming radio surveys.
| Stream | Science |
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