Making maps of cosmic microwave background polarization for B-mode studies: the POLARBEAR example

Abstract

Analysis of cosmic microwave background (CMB) datasets typically requires some filtering of the raw time-ordered data. For instance, in the context of ground-based observations, filtering is frequently used to minimize the impact of low frequency noise, atmospheric contributions and/or scan synchronous signals on the resulting maps. In this work we have explicitly constructed a general filtering operator, which can unambiguously remove any set of unwanted modes in the data, and then amend the map-making procedure in order to incorporate and correct for it. We show that such an approach is mathematically equivalent to the solution of a problem in which the sky signal and unwanted modes are estimated simultaneously and the latter are marginalized over. We investigated the conditions under which this amended map-making procedure can render an unbiased estimate of the sky signal in realistic circumstances. We then discuss the potential implications of these observations on the choice of map-making and power spectrum estimation approaches in the context of B-mode polarization studies. Specifically, we have studied the effects of time-domain filtering on the noise correlation structure in the map domain, as well as impact it may have on the performance of the popular pseudospectrum estimators. We conclude that although maps produced by the proposed estimators arguably provide the most faithful representation of the sky possible given the data, they may not straightforwardly lead to the best constraints on the power spectra of the underlying sky signal and special care may need to be taken to ensure this is the case. By contrast, simplified map-makers which do not explicitly correct for time-domain filtering, but leave it to subsequent steps in the data analysis, may perform equally well and be easier and faster to implement. We focused on polarization-sensitive measurements targeting the B-mode component of the CMB signal and apply the proposed methods to realistic simulations based on characteristics of an actual CMB polarization experiment, POLARBEAR. Our analysis and conclusions are however more generally applicable.

Instrumental systematics biases in CMB lensing reconstruction: A simulation-based assessment

“…We do not use any filtering during the map-making process to avoid the need to correct the reconstructed lensing potential power spectrum by additional MC corrections due to filter-induced biases. While some filtering procedures [19,21] or other map-making-stage modifications [22][23][24] may mitigate some systematic effects, in this work we only demonstrate to leading order the potential lensing biases which may result from systematics alone. We use the process described above to obtain three groups of simulations:…”

Spin characterization of systematics in CMB surveys – a comprehensive formalism

“…It is possible to extend this method to any number of spins provided there are sufficient redundancies in the scanning strategy. Note that the less optimal the scan strategy, the less well conditioned the matrix inversion will be, as such necessitating cuts of ill-conditioned pixels (Kurki-Suonio et al 2009;Poletti et al 2017).…”

Bandpass mismatch error for satellite CMB experiments II: correcting for the spurious signal

“…Similar approaches to map-making for CMB observations while solving for nuisance terms in this way have been used in other contexts [42][43][44].…”