The extraction of foreground and CMB maps from multi-frequency observations relies mostly on the different frequency behavior of the different components. Existing Bayesian methods additionally make use of a Gaussian prior for the CMB whose correlati
on structure is described by an unknown angular power spectrum. We argue for the natural extension of this by using non-trivial priors also for the foreground components. Focusing on diffuse Galactic foregrounds, we propose a log-normal model including unknown spatial correlations within each component and cross-correlations between the different foreground components. We present case studies at low resolution that demonstrate the superior performance of this model when compared to an analysis with flat priors for all components.
(abridged) Observations of Faraday rotation for extragalactic sources probe magnetic fields both inside and outside the Milky Way. Building on our earlier estimate of the Galactic contribution, we set out to estimate the extragalactic contributions.
We discuss the problems involved; in particular, we point out that taking the difference between the observed values and the Galactic foreground reconstruction is not a good estimate for the extragalactic contributions. We point out a degeneracy between the contributions to the observed values due to extragalactic magnetic fields and observational noise and comment on the dangers of over-interpreting an estimate without taking into account its uncertainty information. To overcome these difficulties, we develop an extended reconstruction algorithm based on the assumption that the observational uncertainties are accurately described for a subset of the data, which can overcome the degeneracy with the extragalactic contributions. We present a probabilistic derivation of the algorithm and demonstrate its performance using a simulation, yielding a high quality reconstruction of the Galactic Faraday rotation foreground, a precise estimate of the typical extragalactic contribution, and a well-defined probabilistic description of the extragalactic contribution for each data point. We then apply this reconstruction technique to a catalog of Faraday rotation observations. We vary our assumptions about the data, showing that the dispersion of extragalactic contributions to observed Faraday depths is most likely lower than 7 rad/m^2, in agreement with earlier results, and that the extragalactic contribution to an individual data point is poorly constrained by the data in most cases.
We develop a method to infer log-normal random fields from measurement data affected by Gaussian noise. The log-normal model is well suited to describe strictly positive signals with fluctuations whose amplitude varies over several orders of magnitud
e. We use the formalism of minimum Gibbs free energy to derive an algorithm that uses the signals correlation structure to regularize the reconstruction. The correlation structure, described by the signals power spectrum, is thereby reconstructed from the same data set. We show that the minimization of the Gibbs free energy, corresponding to a Gaussian approximation to the posterior marginalized over the power spectrum, is equivalent to the empirical Bayes ansatz, in which the power spectrum is fixed to its maximum a posteriori value. We further introduce a prior for the power spectrum that enforces spectral smoothness. The appropriateness of this prior in different scenarios is discussed and its effects on the reconstructions results are demonstrated. We validate the performance of our reconstruction algorithm in a series of one- and two-dimensional test cases with varying degrees of non-linearity and different noise levels.
We aim to summarize the current state of knowledge regarding Galactic Faraday rotation in an all-sky map of the Galactic Faraday depth. For this we have assembled the most extensive catalog of Faraday rotation data of compact extragalactic polarized
radio sources to date. In the map making procedure we use a recently developed algorithm that reconstructs the map and the power spectrum of a statistically isotropic and homogeneous field while taking into account uncertainties in the noise statistics. This procedure is able to identify some rotation angles that are offset by an integer multiple of pi. The resulting map can be seen as an improved version of earlier such maps and is made publicly available, along with a map of its uncertainty. For the angular power spectrum we find a power law behavior with a power law index of -2.14 for a Faraday sky where an overall variance profile as a function of Galactic latitude has been removed, in agreement with earlier work. We show that this is in accordance with a 3D Fourier power spectrum P(k) proportional to k^-2.14 of the underlying field n_e times B_r under simplifying geometrical and statistical assumptions.
We derive a method to reconstruct Gaussian signals from linear measurements with Gaussian noise. This new algorithm is intended for applications in astrophysics and other sciences. The starting point of our considerations is the principle of minimum
Gibbs free energy which was previously used to derive a signal reconstruction algorithm handling uncertainties in the signal covariance. We extend this algorithm to simultaneously uncertain noise and signal covariances using the same principles in the derivation. The resulting equations are general enough to be applied in many different contexts. We demonstrate the performance of the algorithm by applying it to specific example situations and compare it to algorithms not allowing for uncertainties in the noise covariance. The results show that the method we suggest performs very well under a variety of circumstances and is indeed qualitatively superior to the other methods in cases where uncertainty in the noise covariance is present.
We present a first application of the recently proposed LITMUS test for magnetic helicity, as well as a thorough study of its applicability under different circumstances. In order to apply this test to the galactic magnetic field, the newly developed
critical filter formalism is used to produce an all-sky map of the Faraday depth. The test does not detect helicity in the galactic magnetic field. To understand the significance of this finding, we made an applicability study, showing that a definite conclusion about the absence of magnetic helicity in the galactic field has not yet been reached. This study is conducted by applying the test to simulated observational data. We consider simulations in a flat sky approximation and all-sky simulations, both with assumptions of constant electron densities and realistic distributions of thermal and cosmic ray electrons. Our results suggest that the LITMUS test does indeed perform very well in cases where constant electron densities can be assumed, both in the flat-sky limit and in the galactic setting. Non-trivial distributions of thermal and cosmic ray electrons, however, may complicate the scenario to the point where helicity in the magnetic field can escape detection.
