CO Component Estimation Based on the Independent Component Analysis
  Fast Independent Component Analysis (FastICA) is a component separation
algorithm based on the levels of non-Gaussianity. Here we apply the FastICA to
the component separation problem of the microwave background including carbon
monoxide (CO) line emissions that are found to contaminate the PLANCK High
Frequency Instrument (HFI) data. Specifically we prepare 100GHz, 143GHz, and
217GHz mock microwave sky maps including galactic thermal dust, NANTEN CO line,
and the Cosmic Microwave Background (CMB) emissions, and then estimate the
independent components based on the kurtosis. We find that the FastICA can
successfully estimate the CO component as the first independent component in
our deflection algorithm as its distribution has the largest degree of
non-Gaussianity among the components. By subtracting the CO and the dust
components from the original sky maps, we will be able to make an unbiased
estimate of the cosmological CMB angular power spectrum.
