Fast Inverse Transform Sampling of Non‐Gaussian Distribution Functions in Space Plasmas

Non-Gaussian distributions are commonly observed in collisionless space plasmas. Generating samples from non-Gaussian 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 one two dimensions. This tool based on inverse transform sampling with function approximation by Chebyshev polynomials. We demonstrate practical uses Chebsampling through typical