Evidence for cloud-to-cloud variations in the ratio of polarized thermal dust emission to starlight polarization

The correlation between optical starlight polarization and polarized thermal dust emission can be used to infer intrinsic dust properties. This correlation is quantified by the ratio R P / p , which has been measured by the Planck Collaboration to be 5.42 ± 0.05 MJy sr −1 at 353 GHz when averaged over large areas of the sky. We investigated this correlation using newly published stellar polarimetric data densely sampling a continuous sky region of about four square degrees at intermediate Galactic latitude. We combined RoboPol optical polarization measurements for 1430 stars with submillimeter data from the Planck satellite at 353 GHz. We performed linear fits between the Planck ( Q s , U s ) and optical ( q v , u v ) Stokes parameters, taking into account the differences in resolution between the two datasets as well as the distribution of clouds along the line of sight. We find in this region of the sky that the R P / p value is 3.67 ± 0.05 MJy sr −1 , indicating a significantly shallower slope than that found previously using different stellar samples. We also find significant differences in the fitted slopes when fitting the Q s – q v and U s – u v data separately. We explore two explanations using mock data: the miscalibration of the polarization angle and the variations in R P / p along the line of sight due to multiple clouds. We show that the former can produce differences in the correlations of Q s – q v and U s – u v , but large miscalibration angles would be needed to reproduce the magnitude of the observed differences. Our simulations favor the interpretation that R P / p differs between the two dominant clouds that overlap on the sky in this region. The difference in R P / p suggests that the two clouds may have distinct dust polarimetric properties. With knowledge from the tomographic decomposition of the stellar polarization, we find that one cloud appears to dominate the correlation of U s – u v , while both clouds contribute to the correlation of the Q s – q v data.