Kratos-polrad: Novel GPU system for Monte-Carlo simulations with consistent polarization calculations
4 affiliations
- 1Institute for Astronomy, School of Physics, Zhejiang University , 886 Yuhangtang Road, Hangzhou 310027 ,
- 2Center for Cosmology and Computational Astrophysics, Institute for Advanced Study in Physics, Zhejiang University , Hangzhou 310027 ,
- 3The Kavli Institute for Astronomy and Astrophysics, Peking University , Beijing 100871 ,
- 4School of Physics, Peking University Department of Astronomy, , Beijing 100871 ,
Abstract
Polarized radiation serves as a vital diagnostic tool in astrophysics, providing unique insights into magnetic field geometries, scattering processes, and three-dimensional structures in diverse astrophysical scenarios. To address these applications, we present Kratos-polrad, a novel GPU-accelerated Monte Carlo Radiative Transfer code built upon the heterogeneous computing framework of Kratos, designed for self-consistent and efficient polarization calculations. It utilizes a comprehensive treatment of the Stokes parameters throughout photon propagation, featuring grain–lab frame transformations using quaternion algebra and a consistent analytical integration of polarized extinction and emission within each cell, which are useful in modeling radiative transfer processes with scatterings by aligned dust grains. The code implements two-step polarimetry imaging that decouples Monte Carlo sampling of scattering physics from imaging geometry, enabling efficient synthesis maximizing the utilization of photon packets. Extensive validation against analytical solutions and established codes demonstrates accurate treatment of diverse polarization phenomena, including self-scattering polarization, dichroic extinction in aligned dust grains, and complex polarization patterns in twisted magnetic field configurations. By leveraging massive GPU parallelism, optimized memory access patterns, and analytical approaches for optically thick cells, Kratos-polrad achieves performance improvements of ∼102 times compared to CPU-based methods, enabling previously prohibitive studies in polarimetric astrophysics.
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BibTeX
@article{yang2026kratospolrad,
title = {{Kratos-polrad: Novel GPU system for Monte-Carlo simulations with consistent polarization calculations}},
author = {Haifeng Yang and Lile Wang},
journal = {Monthly Notices of the Royal Astronomical Society},
year = {2026},
month = oct,
doi = {10.1093/mnras/stag2002},
url = {https://academic.oup.com/mnras/advance-article/doi/10.1093/mnras/stag2002/8965444},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Kratos-polrad: Novel GPU system for Monte-Carlo simulations with consistent polarization calculations
AU - Haifeng Yang
AU - Lile Wang
PY - 2026
DA - 2026/10/21
JO - Monthly Notices of the Royal Astronomical Society
DO - 10.1093/mnras/stag2002
UR - https://academic.oup.com/mnras/advance-article/doi/10.1093/mnras/stag2002/8965444
AB - Polarized radiation serves as a vital diagnostic tool in astrophysics, providing unique insights into magnetic field geometries, scattering processes, and three-dimensional structures in diverse astrophysical scenarios. To address these applications, we present Kratos-polrad, a novel GPU-accelerated Monte Carlo Radiative Transfer code built upon the heterogeneous computing framework of Kratos, designed for self-consistent and efficient polarization calculations. It utilizes a comprehensive treatment of the Stokes parameters throughout photon propagation, featuring grain–lab frame transformations using quaternion algebra and a consistent analytical integration of polarized extinction and emission within each cell, which are useful in modeling radiative transfer processes with scatterings by aligned dust grains. The code implements two-step polarimetry imaging that decouples Monte Carlo sampling of scattering physics from imaging geometry, enabling efficient synthesis maximizing the utilization of photon packets. Extensive validation against analytical solutions and established codes demonstrates accurate treatment of diverse polarization phenomena, including self-scattering polarization, dichroic extinction in aligned dust grains, and complex polarization patterns in twisted magnetic field configurations. By leveraging massive GPU parallelism, optimized memory access patterns, and analytical approaches for optically thick cells, Kratos-polrad achieves performance improvements of ∼102 times compared to CPU-based methods, enabling previously prohibitive studies in polarimetric astrophysics.
SN - 0035-8711
SN - 1365-2966
ER -