Gaussian Beam

This example initializes a Gaussian beam distribution.

Run

This example can be run either as:

  • Python script: python3 PICMI_inputs_gaussian_beam.py or

  • WarpX executable using an input file: (TODO)

For MPI-parallel runs, prefix these lines with mpiexec -n 4 ... or srun -n 4 ..., depending on the system.

Listing 39 You can copy this file from Examples/Tests/gaussian_beam/PICMI_inputs_gaussian_beam.py.
#!/usr/bin/env python3

#from warp import picmi
import argparse

from pywarpx import picmi

parser = argparse.ArgumentParser(description="Gaussian beam PICMI example")

parser.add_argument('--diagformat', type=str,
                    help='Format of the full diagnostics (plotfile, openpmd, ascent, sensei, ...)',
                    default='plotfile')
parser.add_argument('--fields_to_plot', type=str,
                    help='List of fields to write to diagnostics',
                    default=['E', 'B', 'J', 'part_per_cell'],
                    nargs = '*')

args = parser.parse_args()

constants = picmi.constants

nx = 32
ny = 32
nz = 32

xmin = -2.
xmax = +2.
ymin = -2.
ymax = +2.
zmin = -2.
zmax = +2.

number_sim_particles = 32768
total_charge = 8.010883097437485e-07

beam_rms_size = 0.25
electron_beam_divergence = -0.04*constants.c

em_order = 3

grid = picmi.Cartesian3DGrid(number_of_cells = [nx, ny, nz],
                             lower_bound = [xmin, ymin, zmin],
                             upper_bound = [xmax, ymax, zmax],
                             lower_boundary_conditions = ['periodic', 'periodic', 'open'],
                             upper_boundary_conditions = ['periodic', 'periodic', 'open'],
                             lower_boundary_conditions_particles = ['periodic', 'periodic', 'absorbing'],
                             upper_boundary_conditions_particles = ['periodic', 'periodic', 'absorbing'],
                             warpx_max_grid_size=16)

solver = picmi.ElectromagneticSolver(grid = grid,
                                     cfl = 1.,
                                     stencil_order=[em_order,em_order,em_order])

electron_beam = picmi.GaussianBunchDistribution(n_physical_particles = total_charge/constants.q_e,
                                                rms_bunch_size = [beam_rms_size, beam_rms_size, beam_rms_size],
                                                velocity_divergence = [electron_beam_divergence, electron_beam_divergence, electron_beam_divergence])

proton_beam = picmi.GaussianBunchDistribution(n_physical_particles = total_charge/constants.q_e,
                                              rms_bunch_size = [beam_rms_size, beam_rms_size, beam_rms_size])

electrons = picmi.Species(particle_type='electron', name='electrons', initial_distribution=electron_beam)
protons = picmi.Species(particle_type='proton', name='protons', initial_distribution=proton_beam)

field_diag1 = picmi.FieldDiagnostic(name = 'diag1',
                                    grid = grid,
                                    period = 10,
                                    data_list = args.fields_to_plot,
                                    warpx_format = args.diagformat,
                                    write_dir = '.',
                                    warpx_file_prefix = 'Python_gaussian_beam_plt')

part_diag1 = picmi.ParticleDiagnostic(name = 'diag1',
                                      period = 10,
                                      species = [electrons, protons],
                                      data_list = ['weighting', 'momentum'],
                                      warpx_format = args.diagformat)

sim = picmi.Simulation(solver = solver,
                       max_steps = 10,
                       verbose = 1,
                       warpx_current_deposition_algo = 'direct',
                       warpx_use_filter = 0)

sim.add_species(electrons, layout=picmi.PseudoRandomLayout(n_macroparticles=number_sim_particles))
sim.add_species(protons, layout=picmi.PseudoRandomLayout(n_macroparticles=number_sim_particles))

sim.add_diagnostic(field_diag1)
sim.add_diagnostic(part_diag1)

# write_inputs will create an inputs file that can be used to run
# with the compiled version.
#sim.write_input_file(file_name = 'inputs_from_PICMI')

# Alternatively, sim.step will run WarpX, controlling it from Python
sim.step()

Note

TODO: This input file should be created following the PICMI_inputs_gaussian_beam.py file.

Analyze

Note

This section is TODO.

Visualize

Note

This section is TODO.