Foreground removal from Planck Sky Model temperature maps using a MLP neural network

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Unfortunately, the Cosmic Microwave Background (CMB) radiation is contaminated by emission originating in the Milky Way (synchrotron, free-free and dust emission). Since the cosmological information is statistically in nature, it is essential to remove this foreground emission and leave the CMB with no systematic errors. To demonstrate the feasibility of a simple multilayer perceptron (MLP) neural network for extracting the CMB temperature signal, we have analyzed a specific data set, namely the Planck Sky Model maps, developed for evaluation of different component separation methods before including them in the Planck data analysis pipeline. It is found that a MLP neural network can provide a CMB map of about 80% of the sky to a very high degree uncorrelated with the foreground components. Also the derived power spectrum shows little evidence for systematic errors.
Original languageEnglish
JournalAstronomische Nachrichten
Volume330
Issue number8
Pages (from-to)863-870
ISSN0004-6337
DOIs
Publication statusPublished - 2009

Keywords

  • cosmic microwave background
  • method: data analysis

Cite this