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We present a new map-making method for CMB measurements. The method is based on the destriping technique, but it also utilizes information about the noise spectrum. The low-frequency component of the instrument noise stream is modelled as a superposition of a set of simple base functions, whose amplitudes are determined by means of maximum-likelihood analysis, involving the covariance matrix of the amplitudes. We present simulation results with $1/f$ noise and show a reduction in the residual noise with respect to ordinary destriping. This study is related to Planck LFI activities.
With the temperature power spectrum of the cosmic microwave background (CMB) at least four orders of magnitude larger than the B-mode polarisation power spectrum, any instrumental imperfections that couple temperature to polarisation must be carefull
Madam is a CMB map-making code, designed to make temperature and polarization maps of time-ordered data of total power experiments like Planck. The algorithm is based on the destriping technique, but it also makes use of known noise properties in the
Future cosmic microwave background (CMB) polarisation experiments aim to measure an unprecedentedly small signal - the primordial gravity wave component of the polarisation field B-mode. To achieve this, they will analyse huge datasets, involving yea
We present ROMA, a parallel code to produce joint optimal temperature and polarisation maps out of multidetector CMB observations. ROMA is a fast, accurate and robust implementation of the iterative generalised least squares approach to map-making. W
We present a Gibbs sampling solution to the map-making problem for CMB measurements, building on existing destriping methodology. Gibbs sampling breaks the computationally heavy destriping problem into two separate steps; noise filtering and map binn