Polarisation spectral synthesis for Type Ia supernova explosion models
M. Bulla, S. A. Sim, M. Kromer

TL;DR
This paper introduces a Monte Carlo radiative transfer method with virtual packets to generate low-noise synthetic spectropolarimetry for multi-dimensional supernova models, validated on Type Ia supernovae.
Contribution
The paper presents a novel virtual-packet approach within Monte Carlo radiative transfer to improve synthetic spectropolarimetry calculations for supernova models.
Findings
Reduced Monte Carlo noise in spectropolarimetry simulations.
Accurate recovery of zero polarization in spherical models.
Synthetic polarisation spectra for aspherical supernova ejecta.
Abstract
We present a Monte Carlo radiative transfer technique for calculating synthetic spectropolarimetry for multi-dimensional supernova explosion models. The approach utilises "virtual-packets" that are generated during the propagation of the Monte Carlo quanta and used to compute synthetic observables for specific observer orientations. Compared to extracting synthetic observables by direct binning of emergent Monte Carlo quanta, this virtual-packet approach leads to a substantial reduction in the Monte Carlo noise. This is vital for calculating synthetic spectropolarimetry (since the degree of polarisation is typically very small) but also useful for calculations of light curves and spectra. We first validate our approach via application of an idealised test code to simple geometries. We then describe its implementation in the Monte Carlo radiative transfer code ARTIS and present test…
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