A non-parametric consistency test of the $\Lambda$CDM model with Planck CMB data
Abstract
Non-parametric reconstruction methods, such as Gaussian process (GP) regression, provide a model-independent way of estimating an underlying function and its uncertainty from noisy data. We demonstrate how GP-reconstruction can be used as a consistency test between a given data set and a specific model by looking for structures in the residuals of the data with respect to the model's best-fit. Applying this formalism to the Planck temperature and polarisation power spectrum measurements, we test their global consistency with the predictions of the base CDM model. Our results do not show any serious inconsistencies, lending further support to the interpretation of the base CDM model as cosmology's gold standard.
Keywords
Cite
@article{arxiv.1705.05234,
title = {A non-parametric consistency test of the $\Lambda$CDM model with Planck CMB data},
author = {Amir Aghamousa and Jan Hamann and Arman Shafieloo},
journal= {arXiv preprint arXiv:1705.05234},
year = {2017}
}
Comments
11 pages, 4 figures; v2: matches version published in JCAP