Spatial Variations of Polarized Synchrotron Emission in the QUIJOTE MFI Data using Neural Networks

Polarized synchrotron emission from ultra-relativistic electrons spiraling the Galactic magnetic field has become one of the most relevant emissions in the Interstellar medium these last years due to the improvement in the quality of low-frequency observations. One of the recent experiments designed to explore this emission is the QUIJOTE experiment. We aim to study the spatial variations of the synchrotron emission in the QUIJOTE MFI data, by dividing the sky into physically separated regions. For such task, we firstly use a novel component separation method based on artificial neural networks to clean the synchrotron maps. After training the network with simulations, we fit both $EE$ and $BB$ spectra by assuming a power-law model. Then, we give estimations for the index $\alpha_{S}$, the amplitude, and the ratio between $B$ and $E$ amplitudes. When analyzing the real data, we found a clear spatial variation of the synchrotron properties along the sky at 11 GHz, obtaining a steeper index in the Galactic plane of $\alpha_{S}^{EE} = -3.1 \pm 0.3$ and $\alpha_{S}^{BB} = -3.1 \pm 0.4$ and a flatter one at high Galactic latitudes of $\alpha_{S}^{EE} = -3.05 \pm 0.2$ and $\alpha_{S}^{B} = -2.98 \pm 0.27$. We found average values at all sky of $\alpha_{S}^{EE} = -3.04 \pm 0.21$ and $\alpha_{S}^{BB} = -3.00 \pm 0.34$. Furthermore, after obtaining an average value of $A_{S}^{EE} = 3.31 \pm 0.17$ $\mu K^{2}$ and $A_{S}^{BB} = 0.93 \pm 0.04$ $\mu K^{2}$, we estimate a ratio between $B$ and $E$ amplitudes of $A_{S}^{BB}/A_{S}^{EE} = 0.28 \pm 0.08$. Based on the results we conclude that, although neural networks seem to be valuable methods to apply on real ISM observations, combined analyses with Planck, WMAP and/or CBASS data are mandatory to reduce the contamination from QUIJOTE maps and then improve the accuracy of the estimations.