# A non-parametric consistency test of the $\Lambda$CDM model with Planck CMB data

## TL;DR

This paper uses Gaussian process regression to perform a non-parametric, model-independent consistency test of the Planck CMB data against the base CDM model, finding no significant inconsistencies.

## Contribution

It introduces a novel application of Gaussian process reconstruction as a model-independent consistency test for cosmological data against CDM predictions.

## Key findings

- No significant inconsistencies found in Planck data with CDM model
- Supports CDM as the standard cosmological model
- Demonstrates the effectiveness of GP-based residual analysis

## 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 $\Lambda$CDM model. Our results do not show any serious inconsistencies, lending further support to the interpretation of the base $\Lambda$CDM model as cosmology's gold standard.