POLARIS: the POLArized radIation simulator for Mie scattering in optically thick dusty plasmas - Kobus, Julia; Reißl, Stefan; Lietzow-Sinjen, Moritz; Bensberg, Alexander; Petersen, Andreas; Greiner, Franko; Wolf, Sebastian (Computer physics communications, 2025)
POLARIS is a 3D Monte-Carlo radiative transfer code written in C++ for simulating the Mie scattering of laser light in optically thick nanodusty plasmas. Originally developed for astrophysical applications, POLARIS has been adapted to address the specific needs of the plasma physics community. To achieve this, a given number of photon packages characterized by their traveling direction d→, wavelength λ, intensity, and polarization state in terms of the Stokes vector S→ is generated to mimic the emission of a laser source with a Gaussian intensity distribution. These photon packages are then tracked along their probabilistic paths through the particle cloud, with scattering processes determined stochastically based on probability density distributions derived from the optical properties of the dust particles. POLARIS allows simulations for arbitrary wavelengths and grain sizes, as long as the far-field approximation holds. This paper introduces this adapted version of POLARIS to the plasma physics community, highlighting its capabilities for modeling light scattering in dusty plasmas and serving as a comprehensive reference for its application. In doing so, POLARIS provides a powerful tool for the in-situ analysis of optically thick dusty plasmas. - Program summary - Program Title: POLARIS CPC Library link to program files: https://doi.org/10.17632/8d3jm3x29t.1 Developer's repository link: https://github.com/polaris-MCRT/POLARIS Licensing provisions: GPLv3 Programming language: C++, Python 3 Nature of problem: Simulating Mie scattering in dense dusty plasmas to enable in-situ analysis of these systems. Solution method: Tracing the random paths of photon packages through a three dimensional grid filled with dust particles making stochastic decisions on scattering processes based on probability density distributions given by the optical properties of the dust particles.
Gesehen am 06.10.2025