Non-linear parallel solver for detecting point sources in CMB maps using Bayesian techniques

In this work we present a suitable computational tool to deal with large matrices and solve systems of non-linear equations. This technique is applied to a very interesting problem: the detection and flux estimation of point sources in Cosmic Microwave Background (CMB) maps, which allows a good determination of CMB primordial fluctuations and leads to a better knowledge of the chemistry at the early stages of the Universe. The method uses previous information about the statistical properties of the sources, so that this knowledge is incorporated in a Bayesian scheme. Simulations show that our approach allows the detection of more sources than previous non-Bayesian techniques, with a small computation time.