Spatial Variations of Polarized Synchrotron Emission in the QUIJOTE MFI Data

Abstract

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 $α_{S}$, 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 $α_{S}^{EE} = -3.1 \pm 0.3$ and $α_{S}^{BB} = -3.1 \pm 0.4$ and a flatter one at high Galactic latitudes of $α_{S}^{EE} = -3.05 \pm 0.2$ and $α_{S}^{B} = -2.98 \pm 0.27$. We found average values at all sky of $α_{S}^{EE} = -3.04 \pm 0.21$ and $α_{S}^{BB} = -3.00 \pm 0.34$. Furthermore, after obtaining an average value of $A_{S}^{EE} = 3.31 \pm 0.08$ $μK^{2}$ and $A_{S}^{BB} = 0.93 \pm 0.02$ $μK^{2}$, 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.

Figures (13)

• Figure 1: Mollview projection of the data used in this work. Left panel: QUIJOTE $Q$ MFI sky at 11 GHz. Right panel: polarized synchrotron regions defined by FUS14. It is shown in grey the regions that cannot be used in this work due to QUIJOTE coverage and patch sizes.
• Figure 2: Example of the kind of data we are using in this work, which represents in this case a patch of the $Q$ sky as seen by QUIJOTE MFI in the North Polar Spur (sky Region 13) at the position [lon, lat] = [45$^{\circ}$, 45$^{\circ}$] for, from top to bottom and left to right: our simulations, the QUIJOTE MFI observations at 11 GHz, the difference between them, the synchrotron patch output from the neural network, the output from the same trained network but using the real data, the difference between these two last maps, the synchrotron s5 model at this sky patch and then the difference between the outputs from the network and the synchrotron model when using both simulations and observations, respectively. Colorbars show the $\mu k_{CMB}$ units for each patch.
• Figure 3: Scheme of the architecture of the neural network used in this work. We show for visualization purposes the kind of input and output patches the network reads and outputs, respectively.
• Figure 4: Polarized synchrotron index $\alpha_{S}$ comparison at 11 GHz between the input s5 model (blue dots) and the outputs from the neural network (in red), after fitting both $EE$ (left panel) and $BB$ spectra (right panel) for each sky region, while bottom subpanel displays the absolute error between them. The average index is shown in both panels as a dashed blue and red lines, respectively. The average difference is represented as a dashed black line. The errorbars for each point show the 1$\sigma$ uncertainty for each sky region evaluated over 100 simulations. Shaded colored areas show the 1$\sigma$ uncertainties for each average value.
• Figure 5: Polarized synchrotron amplitude $A_{S}$ comparison at 11 GHz in logarithmic scale between the input s5 model (blue dots) and the outputs from the neural network (in red), after fitting both $EE$ (left panel) and $BB$ spectra (right panel) for each sky region, while bottom subpanel displays in linear scale the absolute error between them. The average difference is represented as a dashed black line. The errorbars for each point show the 1$\sigma$ uncertainty for each sky region evaluated over 100 simulations. Shaded colored area show the 1$\sigma$ uncertainty for the absolute error average value.