Fast inverse transform sampling of non-Gaussian distribution functions in space plasmas
Plasma Physics
2022-04-29 v2 Computational Physics
Space Physics
Abstract
Non-Gaussian distributions are commonly observed in collisionless space plasmas. Generating samples from non-Gaussian distributions is critical for the initialization of particle-in-cell simulations that investigate their driven and undriven dynamics. To this end, we report a computationally efficient, robust tool, Chebsampling, to sample general distribution functions in one and two dimensions. This tool is based on inverse transform sampling with function approximation by Chebyshev polynomials. We demonstrate practical uses of Chebsampling through sampling typical distribution functions in space plasmas.
Keywords
Cite
@article{arxiv.2202.08203,
title = {Fast inverse transform sampling of non-Gaussian distribution functions in space plasmas},
author = {Xin An and Anton Artemyev and Vassilis Angelopoulos and San Lu and Philip Pritchett and Viktor Decyk},
journal= {arXiv preprint arXiv:2202.08203},
year = {2022}
}
Comments
15 pages, 4 figures