Evidence for Spatial Separation of Galactic Dust Components

Abstract

We present an implementation of a Bayesian mixture model using Hamiltonian Monte Carlo (HMC) techniques to search for spatial separation of Galactic dust components. Utilizing intensity measurements from \Planck High Frequency Instrument (HFI), we apply this model to high-latitude Galactic dust emission. Our analysis reveals a strong preference for a spatially-varying two-population dust model in intensity, with each population being well characterized by a single-component dust spectral-energy distribution (SED). While no spatial information is built into the likelihood, our investigation unveils spatially coherent structures with high significance, pointing to a physical origin for the observed spatial separation. These results are robust to our choice of likelihood and of input data. Furthermore, they are favored over a single-component dust model by Bayesian evidence calculations. Incorporating \IRAS 100\,$\mu m$ to constrain the Wein-side of the blackbody function, we find the dust populations differ at the $2.5\sigma$ level on the spectral index ($\beta_d$) vs. temperature $(T_d)$ plane. The presence of a multi-population dust has implications for component separation techniques frequently employed in the recovery of the Cosmic Microwave Background.Comment: 16 pages, 8 figures. Submitted to Ap