Introduction to Python Steering
The following is a tour of the basic layout of CRPropa 3, showing how to setup and run a 1D simulation of the extragalactic propagation of UHECR protons from a Python shell.
Simulation setup
We start with a ModuleList
, which is a container for simulation modules, and represents the simulation.
The first module in a simulation should be a propagation module, which will move the cosmic rays. In a 1D simulation magnetic deflections of charged particles are not considered, thus we can use the SimplePropagation
module for rectalinear propagation.
Next we add modules for photo-pion and electron-pair production with the cosmic microwave background and a module for neutron and nuclear decay. Finally we add a minimum energy requirement: Cosmic rays are stopped once they reach the minimum energy. In general the order of modules doesn’t matter much for sufficiently small propagation steps. For good practice, we recommend the order: Propagator –> Interactions -> Break conditions -> Observer / Output.
Please note that all input, output and internal calculations are done using SI-units to enforce expressive statements such as E = 1 * EeV
or D = 100 * Mpc
.
[4]:
from crpropa import *
# simulation: a sequence of simulation modules
sim = ModuleList()
# add propagator for rectalinear propagation
sim.add(SimplePropagation())
# add interaction modules
sim.add(PhotoPionProduction(CMB()))
sim.add(ElectronPairProduction(CMB()))
sim.add(NuclearDecay())
sim.add(MinimumEnergy(1 * EeV))
Propagating a single particle
The simulation can now be used to propagate a cosmic ray, which is called candidate. We create a 100 EeV proton and propagate it using the simulation. The propagation stops when the energy drops below the minimum energy requirement that was specified. The possible propagation distances are rather long since we are neglecting cosmology in this example.
[5]:
cosmicray = Candidate(nucleusId(1, 1), 200 * EeV, Vector3d(100 * Mpc, 0, 0))
sim.run(cosmicray)
print(cosmicray)
print('Propagated distance', cosmicray.getTrajectoryLength() / Mpc, 'Mpc')
CosmicRay at z = 0
source: Particle 1000010010, E = 200 EeV, x = 100 0 0 Mpc, p = -1 0 0
current: Particle 1000010010, E = 0.970856 EeV, x = -13950.9 0 0 Mpc, p = -1 0 0
Propagated distance 14050.929516298673 Mpc
Defining an observer
To define an observer within the simulation we create a Observer
object. The convention of 1D simulations is that cosmic rays, starting from positive coordinates, propagate in the negative direction until the reach the observer at 0. Only the x-coordinate is used in the three-vectors that represent position and momentum.
[6]:
# add an observer
obs = Observer()
obs.add(Observer1D()) # observer at x = 0
sim.add(obs)
print(obs)
Observer
ObserverPoint: observer at x = 0
Flag: '' -> ''
MakeInactive: yes
Defining the output file
enable(XXXColumn)
and disable(XXXColumn)
[7]:
# trajectory output
output1 = TextOutput('trajectories.txt', Output.Trajectory1D)
#sim.add(output1) # generates a lot of output
#output1.disable(Output.RedshiftColumn) # don't save the current redshift
#output1.disableAll() # disable everything to start from scratch
#output1.enable(Output.CurrentEnergyColumn) # current energy
#output1.enable(Output.CurrentIdColumn) # current particle type
# ...
If in the example above output1
is added to the module list, it is called on every propagation step to write out the cosmic ray information. To save only cosmic rays that reach our observer, we add an output to the observer that we previously defined. This time we are satisfied with the output type Event1D.
[8]:
# event output
output2 = TextOutput('events.txt', Output.Event1D)
obs.onDetection(output2)
#sim.run(cosmicray)
#output2.close()
MinimumEnergy
module to save those cosmic rays that fall below the minimum energy, and so on.Defining the source
To avoid setting each individual cosmic ray by hand we defince a cosmic ray source. The source is located at a distance of 100 Mpc and accelerates protons with a power law spectrum and energies between 1 - 200 EeV.
[9]:
# cosmic ray source
source = Source()
source.add(SourcePosition(100 * Mpc))
source.add(SourceParticleType(nucleusId(1, 1)))
source.add(SourcePowerLawSpectrum(1 * EeV, 200 * EeV, -1))
print(source)
Cosmic ray source
SourcePosition: 100 0 0 Mpc
SourceParticleType: 1000010010
SourcePowerLawSpectrum: Random energy E = 1 - 200 EeV, dN/dE ~ E^-1
Running the simulation
Finally we run the simulation to inject and propagate 10000 cosmic rays. An optional progress bar can show the progress of the simulation.
[10]:
sim.setShowProgress(True) # switch on the progress bar
sim.run(source, 10000)
(Optional) Plotting
This is not part of CRPropa, but since we’re at it we can plot the energy spectrum of detected particles to observe the GZK suppression. The plotting is done here using matplotlib, but of course you can use whatever plotting tool you prefer.
[11]:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
output2.close() # close output file before loading
data = np.genfromtxt('events.txt', names=True)
print('Number of events', len(data))
logE0 = np.log10(data['E0']) + 18
logE = np.log10(data['E']) + 18
plt.figure(figsize=(10, 7))
h1 = plt.hist(logE0, bins=25, range=(18, 20.5), histtype='stepfilled', alpha=0.5, label='At source')
h2 = plt.hist(logE, bins=25, range=(18, 20.5), histtype='stepfilled', alpha=0.5, label='Observed')
plt.xlabel('log(E/eV)')
plt.ylabel('N(E)')
plt.legend(loc = 'upper left', fontsize=20)
Number of events 10000
[11]:
<matplotlib.legend.Legend at 0x10c14faf0>