Predictions of polarized dust emission from interstellar clouds: spatial variations in the efficiency of radiative torque alignment
V.-M. Pelkonen (1), M. Juvela (1), P. Padoan (2) ((1) University of, Helsinki, (2) University of California)

TL;DR
This paper investigates how the efficiency of radiative torque alignment of dust grains varies spatially within interstellar clouds and how this affects the observable polarized dust emission used to study magnetic fields.
Contribution
It provides realistic simulations of grain alignment considering spatial variations and grain growth, improving understanding of polarization observations in molecular clouds.
Findings
Radiative torque efficiency is lower than previously assumed, affecting polarization predictions.
Doubling grain size in cores enhances the polarization signal, allowing magnetic field tracing up to higher densities.
Direction-dependent radiative torque efficiency further reduces the observable polarization in dense regions.
Abstract
Polarization carries information about the magnetic fields in interstellar clouds. The observations of polarized dust emission are used to study the role of magnetic fields in the evolution of molecular clouds and the initial phases of star-formation. We study the grain alignment with realistic simulations, assuming the radiative torques to be the main mechanism that spins the grains up. The aim is to study the efficiency of the grain alignment as a function of cloud position and to study the observable consequences of these spatial variations. Our results are based on the analysis of model clouds derived from MHD simulations. The continuum radiative transfer problem is solved with Monte Carlo methods to estimate the 3D distribution of dust emission and the radiation field strength affecting the grain alignment. We also examine the effect of grain growth in cores. We are able to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
