Blind Map Level Systematics Cleaning: A Quadratic Estimator Approach
  We present the first detailed case study using quadratic estimators (QE) to
diagnose and remove systematics present in observed Cosmic Microwave Background
(CMB) maps. In this work we focus on the temperature to polarization leakage.
We use an iterative QE analysis to remove systematics, in analogy to
de-lensing, recovering the primordial B-mode signal and the systematic maps. We
introduce a new Gaussian filtering scheme crucial to stable convergence of the
iterative cleaning procedure and validate with comparisons to semi-analytical
forecasts. We study the limitations of this method by examining its performance
both on idealized simulations and on more realistic, non-ideal simulations,
where we assume varying de-lensing efficiencies. Finally, we quantify the
systematic cleaning efficiency by presenting a likelihood analysis on the
tensor to scalar ratio, $r$, and demonstrate that the blind cleaning results in
an un-biased measurement of $r$, reducing the systematic induced B-mode power
by nearly two orders of magnitude.
