A Bayesian technique for the detection of point sources in cosmic microwave background maps
The detection and flux estimation of point sources in cosmic microwave background (CMB) maps is a very important task in order to clean the maps and also to obtain relevant astrophysical information. In this paper we propose a maximum a posteriori (MAP) approach detection method in a Bayesian scheme...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2011 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/28440 |
| Acceso en línea: | https://hdl.handle.net/10902/28440 |
| Access Level: | acceso abierto |
| Palabra clave: | Methods: data analysis Techniques: image processing Cosmic background radiation Radio continuum: galaxies |
| Sumario: | The detection and flux estimation of point sources in cosmic microwave background (CMB) maps is a very important task in order to clean the maps and also to obtain relevant astrophysical information. In this paper we propose a maximum a posteriori (MAP) approach detection method in a Bayesian scheme which incorporates prior information about the source flux distribution, the locations and the number of sources. We apply this method to CMB simulations with the characteristics of the Planck satellite channels at 30, 44, 70 and 100 GHz. With a similar level of spurious sources, our method yields more complete catalogues than the matched filter with a 5? threshold. Besides, the new technique allows us to fix the number of detected sources in a non-arbitrary way. |
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