Skip to main content

Data analysis methods and tools for the next generation of the Cosmic Micorwave Background polarization experiments.

Final Activity Report Summary - CMB DATA ANALYSIS (Data analysis methods and tools for the next generation of the Cosmic Micorwave Background polarization experiments)

The studies of cosmic microwave background (CMB) anisotropies have been recognised as one of the most fruitful way of investigating the Universe, unveiling its composition, constraining the cosmological parameters as well as peering into the physics at the highest energy scales exceeding by many orders of magnitude those achievable in the present day man-made laboratories. The CMB potential can be however only unlocked if observational data gathered by ever growing in size and sophistication CMB experiments are analysed efficiently in a statistically robust way.

The aim of this proposal was to develop statistically sound algorithms and numerical tools which would be useful in achieving such a goal. Its focus was on the methods of producing the maps of the sky in the microwave band, separating them into the maps of the sky signals of different physical origins, and thus effectively cleaning the primordial cosmological CMB signal and then estimating its statistical properties in particular its two point statistics described by its power spectrum. They all belong to key steps of data analysis pipelines of any CMB experiment.

The work performed under the auspices of this proposal resulted in a number of efficient algorithms subsequently implemented in high performance software packages. These were then tested on the simulated data and made available to experimental teams working on a development of the next generation CMB polarisation experiments. The developed software tools are used by the data centres in France and Italy working to prepare the European satellite mission, Planck. They are also expected to become a backbone of the data analysis pipelines of EBEX and PolarBeaR - currently developed balloon-borne and ground-based observations, and are already used in their optimisation and design. The proposed techniques will be also useful in planning and optimisation of future CMB experiments.