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Deciphering the radio-star formation correlation on kpc-scales I. Adaptive kernel smoothing experiments

Published 6 Nov 2019 in astro-ph.GA | (1911.02253v1)

Abstract: (abridged) Within nearby galaxies, variations in the radio-FIR correlation have been observed, mainly because the cosmic ray electrons migrate before they lose their energy via synchrotron emission or escape. The major cosmic ray electron transport mechanisms within the plane of galactic disks are diffusion and streaming. A predicted radio continuum map can be obtained by convolving the map of comic ray electron sources, represented by that of the star formation, with adaptive Gaussian and exponential kernels. The ratio between the smoothing lengthscales at 6cm and 20cm can be used to distinguish between diffusion and streaming as the dominant transport mechanism. Star formation maps of eight rather face-on local and Virgo cluster spiral galaxies were constructed from Spitzer and Herschel infrared and GALEX UV observations.These maps were convolved with adaptive Gaussian and exponential smoothing kernels to obtain model radio continuum emission maps. It is found that in asymmetric ridges of polarized radio continuum emission the total power emission is enhanced with respect to the star formation rate. The typical lengthscale for the transport of cosmic ray electrons is l=0.9kpc at 6cm and l=1.8kpc at 20cm. Perturbed spiral galaxies tend to have smaller lengthscales. This is a natural consequence of the enhancement of the magnetic field caused by the interaction. The discrimination between the two cosmic ray electron transport mechanisms, diffusion and streaming, is based on (i) the convolution kernel (Gaussian or exponential),(ii) the dependence of the smoothing kernel on the local magnetic field and hence on the local star formation rate, (iii) the ratio between the two smoothing lengthscales via the frequency-dependence of the smoothing kernel, and (iv) the dependence of the smoothing kernel on the ratio between the ordered and the turbulent magnetic field.

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