DOI: 10.5281/zenodo.3951729
title: Data for Kinetic Entropy-Based Measures of Distribution Function Non-Maxwellianity: Theory and Simulations

description: *************************************************<br> Data for Fig. 1:<br> *************************************************<br> nonmax_bimax_kp_1.csv is a CSV file with the data for the black curve in Figure 1. There are 1000 lines, and each line contains two numbers - the analytic value of Kaufmann and Paterson non-Maxwellianity for a bi-Maxwellian distribution and T_perp / T_parallel. nonmax_bimax_kp_2.csv is a CSV file with the data for the red curve in Figure 1. There are 1099 lines, and each line contains two numbers - the analytic value of Kaufmann and Paterson non-Maxwellianity for a bi-Maxwellian distribution and T_perp / T_parallel. *************************************************<br> Data for Fig. 2:<br> *************************************************<br> Below are the general instructions which might be useful for reproducing Fig 2 plots<br> 1. read in the .csv files and associate the variable according to the file names<br> 2. To plot Fig 2 (a), do a 2D plot of (b,Phi) vs s_Eg. b corresponds the column of s_Eg and Phi corresponds to the row of s_Eg.<br> Similarly, to plot Fig 2 (d), do a 2D plot of (b,Phi) vs Mbar_KP. Again, b corresponds the column of Mbar_KP and Phi corresponds to the row of Mbar_KP.<br> 3. Fig 2 (b) and (c) are cuts of (a) at particular values of Phi and b respectively.<br> Similarly,Fig 2 (e) and (f) are cuts of (d) at particular values of Phi and b respectively. *************************************************<br> Data for Fig. 3:<br> *************************************************<br> Below are the general instructions which might be useful for reproducing Fig 3 plots<br> 1. read in the .csv files and associate the variable according to the file names. Here, n_norm = n/n_infinity.<br> 2. To plot Fig 3 (a), do a 2D plot of (b,n_norm) vs s_Eg. b corresponds the column of s_Eg and n_norm corresponds to the row of s_Eg.<br> Similarly, to plot Fig 3 (d), do a 2D plot of (b,n_norm) vs Mbar_KP. Again, b corresponds the column of Mbar_KP and n_norm corresponds to the row of Mbar_KP.<br> 3. Fig 3 (b) and (c) are cuts of (a) at particular values of n_norm and b respectively.<br> Similarly, Fig 3 (e) and (f) are cuts of (d) at particular values of n_norm and b respectively. *************************************************<br> Data for Fig. 4:<br> *************************************************<br> nonmax_bimax_1.csv is a CSV file with the data for the black curve in Figure 4. There are 1000 lines, and each line contains two numbers - the analytic value of the non-Maxwellianity for a bi-Maxwellian distribution and T_perp / T_parallel. nonmax_bimax_2.csv is a CSV file with the data for the red curve in Figure 4. There are 399997 lines, and each line contains two numbers - the analytic value of non-Maxwellianity for a bi-Maxwellian distribution and the base 10 logarithm of T_perp / T_parallel. *************************************************<br> Mbar for Figs. 5-9:<br> *************************************************<br> The Mbar_data.csv is a CSV file saving magnetic field Bx, By, the Kaufmann and Paterson non-Maxwellianity (Mbare_KP for electrons, Mbari_KP for ions) and the new defination of non-Maxwellianity (Mbare_norm for electrons, Mbari_norm for ions) as a function of location (x,y) in the simulation domain. The x consists of 4096 data points from 0.00625 to 51.19375.<br> The y consists of 2048 data points from 0.00625 to 25.59375. The x-point location is (x0,y0)=(11.15625,19.24375). The plots in Figures 5-6,7a,8a, and 9a are used relative coordinates (x-x0,y-y0). The magnetic field data can be used to plot the field lines as contours of vector potential Az(x,y) as a function of Bx(x,y) and By(x,y) in Figures 5-6. Figures 7a, 8a, 9a are cuts at x-x0=0,8,13 respectively. *************************************************<br> Distribution Functions for Figs 7-9:<br> *************************************************<br> The CSV files are named as "DF_X#_Y#.csv". The two "#" are the (x-x0,y-y0) coordinates of the distribution function. In each of the files, the data includes three columns. The first two columns are either the vx and vy for Figure 7b or v_par and v_perp1 for Figures 8b and 9b. The last column is the corresponding values of the distribution functions.