All-sky component separation in the presence of anisotropic noise and dust temperature variations

We present an extension of the harmonic-space maximum-entropy component separation method (MEM) for multifrequency cosmic microwave background observations that allows one to perform the separation with more plausible assumptions about the receiver noise and foreground astrophysical components. Comp...

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Detalles Bibliográficos
Autores: Stolyarov, V., Hobson, M. P., Lasenby, Anthony N., Barreiro, R. Belén
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2005
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/384581
Acceso en línea:http://hdl.handle.net/10261/384581
Access Level:acceso abierto
Palabra clave:Methods: data analysis
Techniques: image processing
Cosmic microwave background
Descripción
Sumario:We present an extension of the harmonic-space maximum-entropy component separation method (MEM) for multifrequency cosmic microwave background observations that allows one to perform the separation with more plausible assumptions about the receiver noise and foreground astrophysical components. Component separation is considered in the presence of spatially varying noise variance and spectral properties of the foreground components. It is shown that, if not taken properly into account, the presence of spatially varying foreground spectra, in particular, can severely reduce the accuracy of the component separation. Nevertheless, by extending the basic method to accommodate such behaviour and the presence of anisotropic noise, we find that the accuracy of the component separation can be improved to a level comparable with previous investigations in which these effects were not present.