Modelling and peeling extended sources with shapelets: a Fornax A case study
| Autor: | Line, J. L. B., Mitchell, D. A., Pindor, B., Riding, J. L., McKinley, B., Webster, R. L., Trott, C. M., Hurley-Walker, N., Offringa, A. R. |
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| Rok vydání: | 2020 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1017/pasa.2020.18 |
| Popis: | To make a power spectrum (PS) detection of the 21 cm signal from the Epoch of Reionisation (EoR), one must avoid/subtract bright foreground sources. Sources such as Fornax A present a modelling challenge due to spatial structures spanning from arc seconds up to a degree. We compare modelling with multi-scale (MS) CLEAN components to 'shapelets', an alternative set of basis functions. We introduce a new image-based shapelet modelling package, SHAMFI. We also introduce a new CUDA simulation code (WODEN) to generate point source, Gaussian, and shapelet components into visibilities. We test performance by modelling a simulation of Fornax A, peeling the model from simulated visibilities, and producing a residual PS. We find the shapelet method consistently subtracts large-angular-scale emission well, even when the angular-resolution of the data is changed. We find that when increasing the angular-resolution of the data, the MS CLEAN model worsens at large angular-scales. When testing on real MWA data, the expected improvement is not seen in real data because of the other dominating systematics still present. Through further simulation we find the expected differences to be lower than obtainable through current processing pipelines. We conclude shapelets are worthwhile for subtracting extended galaxies, and may prove essential for an EoR detection in the future, once other systematics have been addressed. Comment: 17 pages, 11 Figures, accepted for publication in Publications of the Astronomical Society of Australia (18/05/2020). "For the SHAMFI code, see: https://github.com/JLBLine/SHAMFI" . "For the SHAMFI documentation, see: https://shamfi.readthedocs.io/" . "For the WODEN code and documentation see: https://github.com/JLBLine/WODEN" |
| Databáze: | arXiv |
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