Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 1906.10052

The Power Spectra of Polarized, Dusty Filaments

Kevin M. Huffenberger·Aditya Rotti·David C. Collins
View original source ↗Read source document ↗Export metadata ↓

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 $B$-mode power to $E$-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 $TE$ 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) $TB$ correlation. The skewing of the misalignment angle necessary to explain $TB$ will cause a yet-unobserved, positive $EB$ dust correlation, a possible target for future experiments.

Explore related subjects

astro-ph.COastro-ph.GA

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kevin M. Huffenberger, Aditya Rotti, David C. Collins. 2019-09-04. The Power Spectra of Polarized, Dusty Filaments. https://doi.org/10.3847/1538-4357%2Fab9df9

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Constraints on the Thomson optical depth to the CMB from the Lyman-$α$ forest

We present the first constraints on the electron optical depth to reionization, $τ_{\mathrm{e}}$, from the Lyman-$α$ forest alone for physically motivated reionization models that match the reionization's end-point, $z_{\rm{end}}$, required by the same astrophysical probe, and for symmetric reionization models with fixed duration, $Δz$, commonly adopted in CMB reionization analyses. Compared to traditional estimates from the latter, the Lyman-$α$ forest traces the ionization state of the IGM through its coupling with the thermal state. We find an explicit mapping between the two solving the chemistry and temperature evolution equations for hydrogen and helium. Our results yield $τ_{\mathrm{e}}$=$0.040^{+0.042}_{-0.018}$ (95\% C.L) and $τ_{\mathrm{e}}$=$0.041^{+0.028}_{-0.017}$ for reionization models with $z_{\rm{end}}$ and $Δz$-fixed, respectively. With mock Lyman-$α$ forest data that mimics the precision of future larger quasar sample datasets, we would potentially obtain tighter $τ_{\mathrm{e}}$ constraints, paving the way for CMB-independent constraints on the epoch of reionization from a large-scale structure probe.

astro-ph.CO↗
arXiv2026

Non-minimally Coupled Running Curvaton for DESI-motivated Dynamical Dark Energy

Recent DESI BAO data combined with CMB and supernova measurements suggest a dynamical dark energy that can cross the phantom divide. We show that introducing a non-minimal coupling $ξχ^2R$ to the running-curvaton framework allows a single field to drive early-universe curvature perturbations and late-time phantom-crossing cosmic acceleration without ghost instabilities. Using MCMC background likelihoods with DESI DR2 BAO, Pantheon+ SNe, and a reduced CMB prior, we constrain the cosmological parameters: $H_0 = 67.88^{+0.53}_{-0.61}\,{\rm km\,s^{-1}\,Mpc^{-1}}$, $Ω_m = 0.3072^{+0.0059}_{-0.0054}$, $w_0 = -0.922^{+0.055}_{-0.063}$, and $w_a = -0.205^{+0.173}_{-0.182}$. Parameter degeneracies leave the coupling constants weakly constrained, highlighting the need for full perturbation-level analysis using CMB spectra and lensing.

astro-ph.CO↗
arXiv2026

On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods

We develop a field-level posterior for cosmological data by marginalizing over initial conditions and noise in a general forward model. While our focus is on large-scale structure data, the results generalize to any weakly non-Gaussian observable. Moreover, the construction is non-perturbative with respect to the forward model and applies equally well to perturbative calculations, simulation-based predictions, and more general effective descriptions. Expanding the FLP around its Gaussian limit, we derive a general expression for the Fisher matrix and reorganize the field-level information into contributions associated with the connected correlators of the evolved field. This makes explicit which terms are captured by likelihood analyses based on the power spectrum, the bispectrum, or finite sets of summary statistics, and which are lost under compression. We recover the standard Gaussian-covariance result for the power spectrum, show that the Gaussian bispectrum likelihood reproduces the corresponding field-level contribution, and show how cross-covariances among summaries progressively reconstruct more of the full field-level information. As an application to the BAO scale, we show how the field contains all the information required for its optimal reconstruction in the presence of noise, and identify the contributions in the FLP needed to attain this limit. We also show that the reconstruction of the initial field arises naturally as a byproduct of our approach, yielding the optimal estimate of the initial conditions given the data and the noise. Our results provide a unified framework to compare field-level and correlator-based inference, to quantify the information loss induced by compression, and to explore the role of stochasticity.

astro-ph.CO↗