The Power Spectra of Polarized, Dusty Filaments
Abstract
We develop an analytic model for the power spectra of polarized filamentary structures as a way to study the Galactic polarization foreground to the Cosmic Microwave Background. Our approach is akin to the cosmological halo-model framework, and reproduces the main features of the Planck 353 GHz power spectra. We model the foreground as randomly-oriented, three-dimensional, spheroidal filaments, accounting for their projection onto the sky. The main tunable parameters are the distribution of filament sizes, the filament physical aspect ratio, and the dispersion of the filament axis around the local magnetic field direction. The abundance and properties of filaments as a function of size determine the slopes of the foreground power spectra, as we show via scaling arguments. The filament aspect ratio determines the ratio of -mode power to -mode power, and specifically reproduces the Planck-observed dust ratio of one-half when the short axis is roughly one-fourth the length of the long axis. Filament misalignment to the local magnetic field determines the cross-correlation, and to reproduce Planck measurements, we need a (three-dimensional) misalignment angle with a root mean squared dispersion of about 50 degrees. These parameters are not sensitive to the particular filament density profile. By artificially skewing the distribution of the misalignment angle, this model can reproduce the Planck-observed (and parity-violating) correlation. The skewing of the misalignment angle necessary to explain will cause a yet-unobserved, positive dust correlation, a possible target for future experiments.
Keywords
Cite
@article{arxiv.1906.10052,
title = {The Power Spectra of Polarized, Dusty Filaments},
author = {Kevin M. Huffenberger and Aditya Rotti and David C. Collins},
journal= {arXiv preprint arXiv:1906.10052},
year = {2020}
}
Comments
14 pages, 10 figures, comments welcome. This version corrects a bug in the weight assigned to filaments near the line of sight, resulting in a shift in the best-fitting model. The methods, discussion, and conclusions are essentially unchanged. This version submitted to ApJ