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Register a new userUsing rotation measure grids to detect cosmological magnetic fields -- a Bayesian approach
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Determining magnetic field properties in different environments of the cosmic large-scale structure as well as their evolution over redshift is a fundamental step toward uncovering the origin of cosmic magnetic fields. Radio observations permit the study of extragalactic magnetic fields via measurements of the Faraday depth of extragalactic radio sources. Our aim is to investigate how much different extragalactic environments contribute to the Faraday depth variance of these sources. We develop a Bayesian algorithm to distinguish statistically Faraday depth variance contributions intrinsic to the source from those due to the medium between the source and the observer. In our algorithm the Galactic foreground and the measurement noise are taken into account as the uncertainty correlations of the galactic model. Additionally, our algorithm allows for the investigation of possible redshift evolution of the extragalactic contribution. This work presents the derivation of the algorithm and tests performed on mock observations. With cosmic magnetism being one of the key science projects of the new generation of radio interferometers we have made predictions for the algorithms performance on data from the next generation of radio interferometers. Applications to real data are left for future work.
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Using cosmological MHD simulations of the magnetic field in galaxy clusters and filaments we evaluate the possibility to infer the magnetic field strength in filaments by measuring cross-correlation functions between Faraday Rotation Measures (RM) and the galaxy density field. We also test the reliability of recent estimates considering the problem of data quality and Galactic foreground (GF) removal in current datasets. Besides the two self-consistent simulations of cosmological magnetic fields based on primordial seed fields and galactic outflows analyzed here, we also explore a larger range of models scaling up the resulting magnetic fields of one of the simulations. We find that, if an unnormalized estimator for the cross-correlation functions and a GF removal procedure is used, the detectability of the cosmological signal is only possible for future instruments (e.g. SKA and ASKAP). However, mapping of the observed RM signal to the underlying magnetization of the Universe (both in space and time) is an extremely challenging task which is limited by the ambiguities of our model parameters, as well as to the weak response of the RM signal in low density environments. Therefore, we conclude that current data cannot constrain the amplitude and distribution of magnetic fields within the large scale structure and a detailed theoretical understanding of the build up and distribution of magnetic fields within the Universe will be needed for the interpretation of future observations.
Accurate distances to celestial objects are key to establishing the age and energy density of the Universe and the nature of dark energy. A distance measure using active galactic nuclei (AGN) has been sought for more than forty years, as they are extremely luminous and can be observed at very large distances. We report here the discovery of an accurate luminosity distance measure using AGN. We use the tight relationship between the luminosity of an AGN and the radius of its broad line region established via reverberation mapping to determine the luminosity distances to a sample of 38 AGN. All reliable distance measures up to now have been limited to moderate redshift -- AGN will, for the first time, allow distances to be estimated to z~4, where variations of dark energy and alternate gravity theories can be probed.
We present a novel method to significantly speed up cosmological parameter sampling. The method relies on constructing an interpolation of the CMB-log-likelihood based on sparse grids, which is used as a shortcut for the likelihood-evaluation. We obtain excellent results over a large region in parameter space, comprising about 25 log-likelihoods around the peak, and we reproduce the one-dimensional projections of the likelihood almost perfectly. In speed and accuracy, our technique is competitive to existing approaches to accelerate parameter estimation based on polynomial interpolation or neural networks, while having some advantages over them. In our method, there is no danger of creating unphysical wiggles as it can be the case for polynomial fits of a high degree. Furthermore, we do not require a long training time as for neural networks, but the construction of the interpolation is determined by the time it takes to evaluate the likelihood at the sampling points, which can be parallelised to an arbitrary degree. Our approach is completely general, and it can adaptively exploit the properties of the underlying function. We can thus apply it to any problem where an accurate interpolation of a function is needed.
RM Synthesis was recently developed as a new tool for the interpretation of polarized emission data in order to separate the contributions of different sources lying on the same line of sight. Until now the method was mainly applied to discrete sources in Faraday space (Faraday screens). Here we consider how to apply RM Synthesis to reconstruct the Faraday dispersion function, aiming at the further extraction of information concerning the magnetic fields of extended sources, e.g. galaxies. The main attention is given to two related novelties in the method, i.e. the symmetry argument in Faraday space and the wavelet technique. We give a relation between our method and the previous applications of RM Synthesis to point-like sources. We demonstrate that the traditional RM Synthesis for a point-like source indirectly implies a symmetry argument and, in this sense, can be considered as a particular case of the method presented here. Investigating the applications of RM Synthesis to polarization details associated with small-scale magnetic fields, we isolate an option which was not covered by the ideas of the Burn theory, i.e. using quantities averaged over small-scale fluctuations of magnetic field and electron density. We describe the contribution of small-scale fields in terms of Faraday dispersion and beam depolarization. We consider the complex polarization for RM Synthesis without any averaging over small-scale fluctuations of magnetic field and electron density and demonstrate that it allows us to isolate the contribution from small-scale field.
A variety of observations impose upper limits at the nano Gauss level on magnetic fields that are coherent on inter-galactic scales while blazar observations indicate a lower bound $sim 10^{-16}$ Gauss. Such magnetic fields can play an important astrophysical role, for example at cosmic recombination and during structure formation, and also provide crucial information for particle physics in the early universe. Magnetic fields with significant energy density could have been produced at the electroweak phase transition. The evolution and survival of magnetic fields produced on sub-horizon scales in the early universe, however, depends on the magnetic helicity which is related to violation of symmetries in fundamental particle interactions. The generation of magnetic helicity requires new CP violating interactions that can be tested by accelerator experiments via decay channels of the Higgs particle.
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