# Recovering Cosmic Microwave Background Polarization Signals with Machine Learning

## TL;DR

This paper presents a deep learning approach using CNNs to effectively remove foreground emissions from CMB maps, enabling more accurate detection of primordial B-mode polarization signals, and demonstrates its application on simulated and real Planck data.

## Contribution

The paper introduces a novel CNN-based method for foreground subtraction in CMB observations, improving signal recovery accuracy at the sensitivity level of CMB-S4 and applying it successfully to Planck data.

## Key findings

- CNN model effectively removes foregrounds from simulated CMB maps.
- The method accurately recovers CMB EE and BB power spectra with reduced noise.
- Application to Planck data shows clean foreground removal and consistent power spectra.

## Abstract

Primordial B-mode detection is one of the main goals of current and future cosmic microwave background (CMB) experiments. However, the weak B-mode signal is overshadowed by several Galactic polarized emissions, such as thermal dust emission and synchrotron radiation. Subtracting foreground components from CMB observations is one of the key challenges in searching for the primordial B-mode signal. Here, we construct a deep convolutional neural network (CNN) model, called \texttt{CMBFSCNN} (Cosmic Microwave Background Foreground Subtraction with CNN), which can cleanly remove various foreground components from simulated CMB observational maps at the sensitivity of the CMB-S4 experiment. Noisy CMB Q (or U) maps are recovered with a mean absolute difference of $0.018 \pm 0.023\ \mu$K (or $0.021 \pm 0.028\ \mu$K). To remove the residual instrumental noise from the foreground-cleaned map, inspired by the needlet internal linear combination method, we divide the whole data set into two ``half-split maps,'' which share the same sky signal, but have uncorrelated noise, and perform a cross-correlation technique to reduce the instrumental noise effects at the power spectrum level. We find that the CMB EE and BB power spectra can be precisely recovered with significantly reduced noise effects. Finally, we apply this pipeline to current Planck observations. As expected, various foregrounds are cleanly removed from the Planck observational maps, with the recovered EE and BB power spectra being in good agreement with the official Planck results.