Quantifying the Effect of Component Covariances in CMB Extraction from Multi-frequency Data

Abstract

Linear combination methods provide a global method for component separation of multi-frequency data. We present such a method that allows for consideration of possible covariances between the desired cosmic microwave background signal and various foreground signals that are also present. We also recover information on the foregrounds including the number of foregrounds, their spectra and templates. In all this, the covariances, which we would only expect to vanish 'in the mean' are included as parameters expressing the fundamental uncertainty due to this type of cosmic variance. When we make the reasonable assumption that the CMB is Gaussian, we can compute both a mean recovered CMB map and also an RMS error map, The mean map coincides with WMAP's Internal Linear Combination map.