SIMBAD references

Present-day cosmic microwave background (CMB) studies require more accurate removal of the Galactic foreground emission. This removal becomes even more essential for CMB polarization measurements. In this paper, we consider a method for filtering out the diffuse Galactic fluctuations on the basis of their statistical properties, namely, the power-law spectra of fluctuations. We focus on the statistical properties of two major Galactic foregrounds that arise from magnetized turbulence, namely, the diffuse synchrotron emission and the thermal emission from dust, and describe how their power laws change with the Galactic latitude. We attribute this change to the change in the geometry of the emission region and claim that the universality of the turbulence spectrum provides a new way of removing Galactic foregrounds. For the Galactic synchrotron emission, we mainly focus on the geometry of the synchrotron emitting regions, which will provide useful information for future polarized synchrotron emission studies. Our model calculation suggests that either a one-component extended halo model or a two-component model, an extended halo component (scale height ≳1 kpc) plus a local component, can explain the observed angular spectrum of the synchrotron emission. For thermal emission from Galactic dust, we discuss general properties of a publicly available 94 GHz total dust emission map and explain how we can obtain a polarized dust emission map. Based on a simple model calculation, we obtain the angular spectrum of the polarized dust emission. Our model calculation suggests that C_l{vprop} l^–11/3 for l ≳ 1000 and a shallower spectrum for l ≲ 1000. We discuss and demonstrate how we can make use of our findings to remove Galactic foregrounds using a template of spatial fluctuations. In particular, we consider examples of spatial filtering of a foreground at small scales, when the separation into CMB signal and foregrounds is done at larger scales. We demonstrate that the new technique of spatial filtering of foregrounds may be promising for recovering the CMB signal in a situation where foregrounds are known at a scale different from the one being studied. It can also improve filtering by combining measurements obtained at different scales.