Cyclotron

This demonstrates a simple cyclotron as published by Ernest O. Lawrence and M. Stanley Livingston, The Production of High Speed Light Ions Without the Use of High Voltages, Phys. Rev. 40, 19 (1932). DOI: 10.1103/PhysRev.40.19

Run

This example can be run either as:

  • Python script: python3 run_cyclotron.py or

  • ImpactX executable using an input file: impactx input_cyclotron.in

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

Listing 97 You can copy this file from examples/cyclotron/run_cyclotron.py.
#!/usr/bin/env python3
#
# Copyright 2022-2023 ImpactX contributors
# Authors: Axel Huebl, Chad Mitchell
# License: BSD-3-Clause-LBNL
#
# -*- coding: utf-8 -*-

from impactx import ImpactX, distribution, elements

sim = ImpactX()

# set numerical parameters and IO control
sim.particle_shape = 2  # B-spline order
sim.space_charge = False
# sim.diagnostics = False  # benchmarking
sim.slice_step_diagnostics = True

# domain decomposition & space charge mesh
sim.init_grids()

# load initial beam
kin_energy_MeV = 4.0e-3  # reference energy
bunch_charge_C = 1.0e-9  # used with space charge
npart = 10000  # number of macro particles

#   reference particle
ref = sim.particle_container().ref_particle()
ref.set_charge_qe(1.0).set_mass_MeV(938.27208816).set_kin_energy_MeV(kin_energy_MeV)

#   particle bunch
distr = distribution.Waterbag(
    lambdaX=1.0e-3,
    lambdaY=1.0e-3,
    lambdaT=0.3,
    lambdaPx=2.0e-4,
    lambdaPy=2.0e-4,
    lambdaPt=2.0e-5,
    muxpx=-0.0,
    muypy=0.0,
    mutpt=0.0,
)
sim.add_particles(bunch_charge_C, distr, npart)

# add beam diagnostics
monitor = elements.BeamMonitor("monitor", backend="h5")

# design the accelerator lattice)
ns = 1  # number of slices per ds in the element
period = [
    monitor,
    elements.ChrAcc(ds=0.038, ez=1.12188308693e-4, bz=1.0e-14, nslice=ns),
    elements.ExactSbend(ds=0.25, phi=180.0, B=1),
    elements.ChrAcc(ds=0.038, ez=1.12188308693e-4, bz=1.0e-14, nslice=ns),
    elements.ExactSbend(ds=0.25, phi=180.0, B=1),
    monitor,
]

sim.lattice.extend(period)

# number of periods through the lattice
sim.periods = 150

# run simulation
sim.evolve()

# clean shutdown
sim.finalize()
Listing 98 You can copy this file from examples/cyclotron/input_cyclotron.in.
###############################################################################
# Particle Beam(s)
###############################################################################
beam.npart = 10000
beam.units = static
beam.kin_energy = 4.0e-3
beam.charge = 1.0e-9
beam.particle = proton
beam.distribution = waterbag
beam.lambdaX = 1.0e-3
beam.lambdaY = 1.0e-3
beam.lambdaT = 0.3
beam.lambdaPx = 2.0e-4
beam.lambdaPy = 2.0e-4
beam.lambdaPt = 2.0e-5
beam.muxpx = 0.0
beam.muypy = 0.0
beam.mutpt = 0.0


###############################################################################
# Beamline: lattice elements and segments
###############################################################################
lattice.elements = monitor half half monitor
lattice.periods = 150
lattice.nslice = 1

monitor.type = beam_monitor
monitor.backend = h5

half.type = line
half.elements = gap bend

gap.type = uniform_acc_chromatic
gap.ds = 0.038
gap.ez = 1.12188308693e-4
gap.bz = 1.0e-14

bend.type = sbend_exact
bend.ds = 0.25
bend.phi = 180.0
bend.B = 1.0

###############################################################################
# Algorithms
###############################################################################
algo.particle_shape = 2
algo.space_charge = false


###############################################################################
# Diagnostics
###############################################################################
diag.slice_step_diagnostics = true

Analyze

We run the following script to analyze correctness:

Script analysis_cyclotron.py
Listing 99 You can copy this file from examples/cyclotron/analysis_cyclotron.py.
#!/usr/bin/env python3
#
# Copyright 2022-2023 ImpactX contributors
# Authors: Axel Huebl, Chad Mitchell
# License: BSD-3-Clause-LBNL
#
# -*- coding: utf-8 -*-

import numpy as np
import openpmd_api as io
from scipy.stats import moment


def get_moments(beam):
    """Calculate standard deviations of beam position & momenta
    and emittance values

    Returns
    -------
    sigx, sigy, sigt, emittance_x, emittance_y, emittance_t
    """
    sigx = moment(beam["position_x"], moment=2) ** 0.5  # variance -> std dev.
    sigpx = moment(beam["momentum_x"], moment=2) ** 0.5
    sigy = moment(beam["position_y"], moment=2) ** 0.5
    sigpy = moment(beam["momentum_y"], moment=2) ** 0.5
    sigt = moment(beam["position_t"], moment=2) ** 0.5
    sigpt = moment(beam["momentum_t"], moment=2) ** 0.5

    epstrms = beam.cov(ddof=0)
    emittance_x = (sigx**2 * sigpx**2 - epstrms["position_x"]["momentum_x"] ** 2) ** 0.5
    emittance_y = (sigy**2 * sigpy**2 - epstrms["position_y"]["momentum_y"] ** 2) ** 0.5
    emittance_t = (sigt**2 * sigpt**2 - epstrms["position_t"]["momentum_t"] ** 2) ** 0.5

    return (sigx, sigy, sigt, emittance_x, emittance_y, emittance_t)


# initial/final beam
series = io.Series("diags/openPMD/monitor.h5", io.Access.read_only)
last_step = list(series.iterations)[-1]
initial = series.iterations[1].particles["beam"].to_df()
final = series.iterations[last_step].particles["beam"].to_df()

# compare number of particles
num_particles = 10000
assert num_particles == len(initial)
assert num_particles == len(final)

print("Initial Beam:")
sigx, sigy, sigt, emittance_x, emittance_y, emittance_t = get_moments(initial)
print(f"  sigx={sigx:e} sigy={sigy:e} sigt={sigt:e}")
print(
    f"  emittance_x={emittance_x:e} emittance_y={emittance_y:e} emittance_t={emittance_t:e}"
)

atol = 0.0  # ignored
rtol = 1.8 * num_particles**-0.5  # from random sampling of a smooth distribution
print(f"  rtol={rtol} (ignored: atol~={atol})")

assert np.allclose(
    [sigx, sigy, sigt, emittance_x, emittance_y, emittance_t],
    [
        1.0e-3,
        1.0e-3,
        3.0e-1,
        2.0e-7,
        2.0e-7,
        6.0e-6,
    ],
    rtol=rtol,
    atol=atol,
)


print("")
print("Final Beam:")
sigx, sigy, sigt, emittance_x, emittance_y, emittance_t = get_moments(final)
print(f"  sigx={sigx:e} sigy={sigy:e} sigt={sigt:e}")
print(
    f"  emittance_x={emittance_x:e} emittance_y={emittance_y:e} emittance_t={emittance_t:e}"
)

atol = 0.0  # ignored
rtol = 2.0 * num_particles**-0.5  # from random sampling of a smooth distribution
print(f"  rtol={rtol} (ignored: atol~={atol})")

assert np.allclose(
    [sigx, sigy, sigt, emittance_x, emittance_y, emittance_t],
    [
        1.040898e-03,
        2.221367e-03,
        3.426366e-01,
        1.151532e-08,
        1.160797e-08,
        3.440357e-07,
    ],
    rtol=rtol,
    atol=atol,
)

Visualize

Note

TODO :)