DOI: 10.5061/dryad.jm63xsjjs
title: Data for: Alfvén Pulse-Driven Spicule-like jets in the presence of thermal conduction and ion-neutral collision in a two-fluid regime

description: The uploaded folder consists of the numerical simulation data and analyses
 routines of two-fluid JOANNA code that studied the Alfvén pulse-driven
 spicule-like jets in the presence of thermal conduction and Ion-neutral
 collision. The code produced the data in .xmf and .h5 formats, which are
 available for the analysis in the Data folder. The slices folder within
 Data consists of grid information in X- and -Y, as well as time. Apart
 from that, these slices consist of the temporal variations of various
 physical variables, e.g., pressure, density, velocity for ions and
 neutrals, magnetic field, etc. These slices are utilized in making the
 distance-time maps as presented in Figs 4-5 in the paper. Each physical
 variable is finally converted from code units to physical units (S.I or
 C.G.S. as required) and presented in the paper. The data and its analysis
 tree are self-descriptive, and each folder contains the instruction files
 in this context.
description: # Data for: Alfvén Pulse-Driven Spicule-like jets in the presence of
 thermal conduction and ion-neutral collision in a two-fluid regime
 [https://doi.org/10.5061/dryad.jm63xsjjs](https://doi.org/10.5061/dryad.jm63xsjjs) ## Code/Software Numerical data is available in the folder that can be analyzed by the given routine. ### Figure 1 #### **Figure (A)** The plot is generated utilizing files with the extension ".xmf" located in the "Data" folder through the "VisIt" visualization software. Alternatively, other visualization software such as IDL and Paraview can be employed. In the simulated solar atmosphere, the total density is represented through a pseudocolor plot, while the streamlined magnetic field is visualized using the integral curve operator within VisIt. #### **Figure (B)** The plot is generated using the Python routine "plot_profile.py". It reads temperature and height values from the "z_T_norm.dat" data file, converts them into arrays, and plots temperature against height. ### Figure 2 #### **Figure (A)** step1: Place 'plot_density_i.py','plot_density_n.py' and 'density.py' in '/Data/Spicule_Alfven_Wave/slices/slices' folder. step2: Run 'plot_density_i.py' and 'plot_density_n.py' individually. Two numpy arrays with the names 'Data_Rho_i.npz' and'Data_Rho_n.npz' are saved in the slices folder. step3: Run 'density.py' to obtain the desired plot. Note: Make sure before executing 'density.py' that the 'Data_Rho_i.npz','Data_Rho_n.npz' are in the same folder/location. .npz files are created and saved to process larger data stored in slices and converted into multiple arrays. These arrays are easy to load, process, and save for further analysis or visualization using Python routines. These Python routines 'plot_density_i.py' and 'plot_density_n.py' are used to convert the large data of density of ions and neutrals into structured arrays in numpy. #### **Figure (B)** step1: Place 'plot_pressure.py' and 'pressure.py' in '/Data/Spicule_Alfven_Wave/slices/slices' folder. step2: Set "Prs_i" as a variable to be plotted in 'plot_pressure.py'. A compressed numpy array with the name 'Data_Prs_i.npz' will be saved. Similarly, repeat the process and set "Prs_n" as a variable to be plotted in 'plot_pressure.py'. A compressed numpy array with the name 'Data_Prs_n.npz' will be saved. Also, make sure to find and replace 'Prs_i' with 'Prs_n' everywhere in the 'plot_pressure.py' when repeating the process for neutral pressure. step3: Run 'pressure.py' to obtain the desired plot. Note: Make sure before executing 'pressure.py' that the 'Data_Prs_i.npz', and 'Data_Prs_n.npz' are in the same folder/location. This python routine 'plot_pressure.py' is used to convert the large data of pressure of ions and neutrals into structured arrays in numpy. #### **Figure (C)** step1: Place 'plot_cs.py' and 'sound_speed.py' in '/Data/Spicule_Alfven_Wave/slices/slices' folder. step2: Run 'plot_cs.py'. A compressed numpy array with the name 'Data_cs.npz' will be saved. Also, make sure to place the previous 'Data_Rho_i.npz', 'Data_Rho_n.npz', 'Data_Prs_i.npz', 'Data_Prs_i.npz' from Figure 2 (A) and (B) in the same folder/location as 'sound_speed.py' step3: Run 'sound_speed.py' to obtain the desired plot. #### **Figure (D)** "magf.py" python routine loads the generated "output0000.vtk" file and plots the magnetic field variation with height. #### **Figure (E)** "alfven.py" python routine loads the generated "output0000.vtk" file and plots the alfven speed variation with height. #### Figure (F) "beta.py" python routine loads the generated "visit_ex_db.vtk" file and plots the plasma beta variation with height. ### Figure 3 The plot is generated utilizing files with the extension ".xmf" located in the "Data" folder through the "VisIt" visualization software. Alternatively, other visualization software such as IDL and Paraview can be employed. In the simulated solar atmosphere, the density of ions and neutrals is depicted using a pseudocolor plot, while their velocity vectors are overlaid within the VisIt software. ### Figure 4 step1: Place 'slices2.py' and 'plot_slices2.py' in '/Data/Spicule_Alfven_Wave/slices/slices' folder. step2: Set "Rho_i" as a variable to be plotted in 'plot_slices2.py'. step3: Run 'plot_slices2.py' in the terminal, set the height for the desired slit eg. python3 plot_slices2.py --height 2,6 Figure 4 (A) and (B) depict schematic representations of the vertical slit ranging from 2Mm to 6Mm. The actual observation of this vertical slit is shown in Figure 4 (C) and (D). ### Figure 5 step1: Place 'slices2.py' and 'plot_slices2.py' in '/Data/Spicule_Alfven_Wave/slices/slices' folder. step2: Set "Vx3_i","Vx3_n" as variable to be plotted in 'plot_slices2.py'. step3: Run 'plot_slices2.py' in the terminal, set the height for the desired slit eg. python3 plot_slices2.py --height 2,6 step4: Similarly, repeat the above steps for variables "Vx2_i" and "Vx2_n" step5: To get the Time evolution plots (fig 5e) run 'plot_slices_time_evolution.py' in terminal, set height as 3,3.00002. Make sure to first put variables as "Vx2_i", and "Vx3_i" in 'plot_slices_time_evolution.py'. Repeat this process for variables "Vx2_n", and "Vx3_n" to get Figure 5f. ### Figure 6 The mass flux of ions and neutrals are estimated at 3 Mm height and saved in Mf_i and Mf_n respectively. The wavelet_power.pro routine of IDL will estimate the power spectra as depicted in Fig. 6 of the paper.