DOI: 10.5281/zenodo.8118023
title: 1D-1V Vlasov-Poisson Simulations of Mutual Impedance Experiments in the presence of small-scale and large-scale plasma inhomogeneities - PART 1

description: =====================================================================================================<br> Author : L. Bucciantini<br> Date : 05/07/2023<br> Laboratory : CNRS-LPC2E, Orléans (France)<br> ===================================================================================================== Dear reader, we thank you for your interest in our dataset. In this document, we describe what you will<br> find in it. In case you need help with using the dataset, or if you are interested in mutual impedance experiments,<br> do not hesitate to contact our team in Orléans (pierre.henri@cnrs-orleans.fr, pierre.henri@oca.eu) =====================================================================================================<br> Topic:<br> This dataset contains the outputs of numerical simulations performed to assess<br> the impact of plasma inhomogeneities on the diagnostic performance<br> of mutual impedance experiments. <br> Numerical model:<br> The outputs are obtained from a numerical model based on the solution of the 1D-1V Vlasov-Poisson<br> system of equations. The scheme used to solve the model is the one developed<br> by Mangeney et al. (2002), A Numerical Scheme for the Integration of the Vlasov-Maxwell System of Equations. Journal of Computational Physics, (doi: https://doi.org/10.1006/jcph.2002.7071).<br> The 1D-1V Vlasov-Poisson version of this model is described in Henri, et al. (2010), Vlasov-Poisson<br> simulations of electrostatic parametric instability for localized Langmuir wave packets in the solar wind,<br> Journal of Geophysical Research (Space Physics), 115, 6106 (2010)<br> -----------------------------------------------------------------------------------------------------<br> What is inside the dataset: The dataset is composed of 7 different mutual impedance measurements, each corresponding to one<br> directory (see below). The measurements (i.e. directory) correspond to small-scale plasma inhomogeneities at different<br> positions with respect to the mutual impedance antennas, or to a large-scale plasma inhomogeneity. Each directory contains a number of folders. Each folder corresponds to the emission of a signal at<br> different frequency.<br> -----------------------------------------------------------------------------------------------------<br> List of directories: (Note : each directory corresponds to one mutual impedance measurement) L : These outputs correspond to one mutual impedance measurement in<br> small antenna emission amplitude, which corresponds to a linear<br> plasma response to the emission. s_xx : Each of these outputs corresponds to one mutual impedance measurement in correspondance of<br> a small-scale plasma inhomogeneity at xx Debye lengths of distance from the emitting antenna<br> -----------------------------------------------------------------------------------------------------<br> List of folders inside the directories: Folders begin with the name "000" and have increasing index. Inside the same directory, each folder<br> represents a different simulation used to build the same mutual impedance measurement. ------------------------------------------------------------------------------------------------------<br> List of files inside the folders: density_e.npz : electron density inside the box, in function of time (tempo) density_p.npz : ion density inside the box, in function of time (tempo) E.npz : electric field in the box, in function of time (tempo) qrho.npz : electric potential in the box, in function of time (tempo) qrho_imposed.npz : electric charge imposed at the emitting antennas, in function of time (tempo) tempo.npz : time-vector for density, electric field, electric potential and charge vectors TEST_Luca.dat : parameters describing the characteristics of the simulated plasma box <br> [<br> Note : the previous files can be opened as follows import numpy as np vector_file_name = np.load('file_name.npz') # Use these for the .npz files<br> characteristics_of_the_box = np.genfromtxt('TEST_Luca.dat',skip_header=1) ] <br> -------------------------------------------------------------------------------------------------------<br> Characteristics of the simulated plasma box (TEST_Luca.dat) nx : amount of spatial grid points xl : physical size of the spatial box, expressed in Debye length tt_w : time resolution for ion and electron density, electric field, electric potential and charge rap_m : ion-to-electron mass ratio R_p : ion-to-electron temperature ratio dt : time step used to evolve in time the numerical simulation emission : emission frequency power : amplitude of the electric charge imposed at the emitting antennas <br> (Note : all parameters not listed here but present inside the TEST_Luca.dat file correspond to additional<br> functionalities of the model. For the use of this dataset, they can be discarded.)