POMME is a new estimator that marginalizes signals varying slower than the HWP rotation timescale to produce unbiased CMB polarisation maps with near-optimal noise in the presence of strong contaminants.
Removing 1/f noise stripes in cosmic microwave background anisotropy observations
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abstract
Removal of systematic effects is crucial in present and future CMB experiments mapping large fraction of the sky. Accurate CMB measurements ask for multi-feed array instruments observing the sky with a redundant scanning strategy covering the same region of the sky on different time scales and with different detectors for a better control of systematic effects. We investigate here the capability to suppress 1/f noise features in Time Ordered Data (TOD) by using the destriping technique described in Maino et al. (1999), under realistic assumptions for crossing condition between different scan circles and sky signal fluctuations on small angular scales. We consider as working case, Planck-LFI simulated observations with few arminutes pixel size convolved with LFI beam resolutions. We also extend the analysis to high values of the knee-frequency and found a residual additional noise rms ~31% larger than the pure white noise rms at fk=1 Hz which could be a critical issue in the extraction of the CMB angular power spectrum. Furthermore we verified that destriping quality does not significantly depend on the receiver sensitivity whereas it improves proportionally to the improvement of sampling rate. Therefore given a noise level, the higher the sampling rate, the better the destriping quality.
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Robust CMB polarisation mapmaking with a rotating half-wave plate
POMME is a new estimator that marginalizes signals varying slower than the HWP rotation timescale to produce unbiased CMB polarisation maps with near-optimal noise in the presence of strong contaminants.