Astrophysical components separation of COBE-DMR 4yr data with FastICA

We present an application of the fast Independent Component Analysis FastICA method to the COBE-DMR 4yr data. Although the signal-to-noise ratio in the COBE-DMR data is typically ∼ 1, the approach is able to extract the CMB signal with high confidence when working at high galactic latitudes. However, the foreground emission components have too low a S/N ratio to be reconstructed by this method (moreover, the number of components which can be reconstructed is directly limited by the number of input channels). The reconstructed CMB map shows the expected frequency scaling of the CMB. We fit the resulting CMB component for the rms quadrupole normalisation Qrms−PS and primordial spectral index n and find results in excellent agreement with those derived from the minimum-noise combination of the 90 and 53 GHz DMR channels without galactic emission correction. We extend the analysis by including additional channels (priors) such as the Haslam map of radio emission at 408 MHz and the DIRBE 140μm map of galactic infra-red emission. Subsequently, the FastICA algorithm is able to both detect galactic foreground emission and separate it from the dominant CMB signal. Fitting the resulting CMB component for Qrms−PS and n we find good agreement with the results from Górski et al. (1996) in which the galactic emission has been taken into account by subtracting that part of the DMR signal observed to be correlated with these galactic template maps. FastICA is therefore able to extract foreground emission from the DMR data and recover a “clean” CMB component. We further investigate the ability of FastICA to evaluate the extent of foreground contamination in the COBE-DMR data. We include an all-sky Hα survey (Dickinson, Davies & Davis 2003) to determine a reliable free-free template of the diffuse interstellar medium which we use in conjunction with the previously described synchrotron and dust templates. The derived frequency scalings of the recovered foregrounds is consistent with previous correlation studies (Banday et al. 2003). In particular we find that, after subtraction of the thermal dust emission predicted by the Finkbeiner, Davis & Schlegel (1999) model 7, this component is the dominant foreground emission at 31.5 GHz. This indicates the presence of an anomalous dust correlated component which is well fitted by a power law spectral shape ν with β ∼ 2.5 in agreement with Banday et al. (2003).