Speaker
Julius Wons
(The University of New South Wales)
Description
Features in the CMB data have been discussed for a long time without striking evidence for or against them. Could the analysis of the data be the reason for this lack of evidence? Is there beyond LCDM physics hiding in the Planck CMB data? Applying a popular machine learning algorithm known as Bayesian Optimisation to Planck CMB can help us to find features in the data. Looking at modulations to the primordial power spectrum, I will compare the results of this novel approach to the current analysis. Further, I will talk about the future of features in the power spectrum.
