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Register a new userWavelet-Bayesian inference of cosmic strings embedded in the cosmic microwave background
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Cosmic strings are a well-motivated extension to the standard cosmological model and could induce a subdominant component in the anisotropies of the cosmic microwave background (CMB), in addition to the standard inflationary component. The detection of strings, while observationally challenging, would provide a direct probe of physics at very high energy scales. We develop a new framework for cosmic string inference, constructing a Bayesian analysis in wavelet space where the string-induced CMB component has distinct statistical properties to the standard inflationary component. Our wavelet-Bayesian framework provides a principled approach to compute the posterior distribution of the string tension $Gmu$ and the Bayesian evidence ratio comparing the string model to the standard inflationary model. Furthermore, we present a technique to recover an estimate of any string-induced CMB map embedded in observational data. Using Planck-like simulations we demonstrate the application of our framework and evaluate its performance. The method is sensitive to $Gmu sim 5 times 10^{-7}$ for Nambu-Goto string simulations that include an integrated Sachs-Wolfe (ISW) contribution only and do not include any recombination effects, before any parameters of the analysis are optimised. The sensitivity of the method compares favourably with other techniques applied to the same simulations.
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We report a search for signatures of cosmic strings in the the Cosmic Microwave Background data from the Wilkinson Microwave Anisotropy Probe. We used a digital filter designed to search for individual cosmic strings and found no evidence for them in the WMAP CMB anisotropies to a level of $Delta T/T sim 0.29$ mK. This corresponds to an absence of cosmic strings with $ Gmu ga 1.07 times 10^{-5}$ for strings moving with velocity $v = c/sqrt{2}$. Unlike previous work, this limit does not depend on an assumed string abundance. We have searched the WMAP data for evidence of a cosmic string recently reported as the CSL-1 object, and found an ``edge with 2$sigma$ significance. However, if this edge is real and produced by a cosmic string, it would have to move at velocity $ga$ 0.94c. We also present preliminary limits on the CMB data that will be returned by the PLANCK satellite for comparison. With the available information on the PLANCK satellite, we calculated that it would be twice as sensitive to cosmic strings as WMAP.
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An algorithm is proposed for denoising the signal induced by cosmic strings in the cosmic microwave background (CMB). A Bayesian approach is taken, based on modeling the string signal in the wavelet domain with generalized Gaussian distributions. Good performance of the algorithm is demonstrated by simulated experiments at arcminute resolution under noise conditions including primary and secondary CMB anisotropies, as well as instrumental noise.
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We apply a messenger field method to solve the linear minimum-variance mapmaking equation in the context of Cosmic Microwave Background (CMB) observations. In simulations, the method produces sky maps that converge significantly faster than those from a conjugate gradient descent algorithm with a diagonal preconditioner, even though the computational cost per iteration is similar. The messenger method recovers large scales in the map better than conjugate gradient descent, and yields a lower overall $chi^2$. In the single, pencil beam approximation, each iteration of the messenger mapmaking procedure produces an unbiased map, and the iterations become more optimal as they proceed. A variant of the method can handle differential data or perform deconvolution mapmaking. The messenger method requires no preconditioner, but a high-quality solution needs a cooling parameter to control the convergence. We study the convergence properties of this new method, and discuss how the algorithm is feasible for the large data sets of current and future CMB experiments.
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