Evidence for Spatial Separation of Galactic Dust Populations

TL;DR

This study uses Bayesian mixture modeling with Hamiltonian Monte Carlo to identify and characterize two spatially-varying Galactic dust populations from Planck data, revealing significant large-scale structures and differences in dust properties.

Contribution

It introduces a Bayesian mixture model with HMC to detect spatial separation of dust populations, demonstrating the existence of two distinct or temperature-variant dust components in the Galaxy.

Findings

Two dust populations are statistically favored over one.

Large-scale spatially coherent structures are identified.

Dust populations differ at 2.5σ in spectral index and temperature.

Abstract

We present an implementation of a Bayesian mixture model using Hamiltonian Monte Carlo (HMC) techniques to search for spatial separation of Galactic dust populations. 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 over a one-population dust model, when the latter must capture the total variance in the sky. Each dust population is well characterized by a single-component spectral energy distribution (SED) and accommodates small variations. These populations could signify two distinct components, or may originate from a one-component model with different temperatures resulting in different SED scalings. While no spatial information is built into the likelihood, our investigation unveils large-scale spatially coherent structures with high significance, pointing to a physical origin for the observed spatial variation. These results are robust to our choice of likelihood and of input data. Furthermore, this spatially varying two-population model is the most favored from 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 in the spectral index ($\beta_d$) vs. temperature ($T_d$) plane. The presence of multiple dust populations has implications for component separation techniques frequently employed in the recovery of the cosmic microwave background.