About
Developed by J. D. McDonnell
In this set of exercises, the student will write code to calculate and visualize the trajectories of charged particles under the influence of both uniform and interesting nonuniform magnetic fields, including the earth’s magnetic field.
Subject Area  Electricity & Magnetism 

Level  Beyond the First Year 
Available Implementation  IPython/Jupyter Notebook 
Learning Objectives 
Students who complete this set of exercises will

Time to Complete  120 min 
EXERCISE 1: MOTION OF A CHARGED PARTICLE IN A UNIFORM MAGNETIC FIELD
Consider a uniform magnetic field, of strength T, in the direction. An particle enters the magnetic field at initial position , with an initial velocity in the direction.
 What do you expect the particle’s trajectory to be shaped like?
 Write the equations of motion for the particle in the uniform magnetic field. Solve the equations analytically.
 Describe in words (or pseudocode) a procedure to numerically solve these equations of motion for the trajectory of the particle.
 Now, use your numerical method or a differential equation solver to find a numerical solution to the equations of motion you wrote down. The special case of a uniform magnetic field has an analytical solution, but many cases do not. Validate your code: Does the shape of the particle’s trajectory match your expectation and your analytical calculation?
 How would your results be different for an ion that enters the magnetic field? Confirm by running the code with parameters for the ion with the same initial velocity that the particle had. Plot the particle’s trajectory and the negative ion’s trajectory on the same plot.
%matplotlib inline
import numpy
import matplotlib.pyplot as mpl
from mpl_toolkits.mplot3d import Axes3D
# Parameters for plot attributes
mpl.rc("xtick", labelsize="large")
mpl.rc("ytick", labelsize="large")
mpl.rc("axes", labelsize="xxlarge")
mpl.rc("axes", titlesize="xxlarge")
mpl.rc("figure", figsize=(8,8))
Exercise 1. Uniform Magnetic Field
# define key constants
m_p = 1.67E27 # mass of proton: kg
qe = 1.602E19 # charge of proton: C
# now, setting up an alpha particle
m = 4.0*m_p
q = 2.0*qe
QoverM = q/m
dt = 1.0E8
t = numpy.arange(0.0, 0.002, dt)
rp = numpy.zeros((len(t), 3))
vp = numpy.zeros((len(t), 3))
v0 = numpy.sqrt(2.0*QoverM*10.0)
# negative ion
mn = 1.0 * m_p
qn = 1.0*qe
QoverMn = qn/mn
rn = numpy.zeros((len(t), 3))
vn = numpy.zeros((len(t), 3))
# Strength of Magnetic Field
B0 = 1.0E4
expected_R = m*v0/(q*B0)
expected_T = 2.0*numpy.pi*expected_R / v0
print("v0 = ", v0)
print("Expected trajectory radius = ", expected_R)
print("Expected cyclotron period = ", expected_T)
# initial condition
rp[0,:] = numpy.array([0.0, 0.0, 0.0])
vp[0,:] = numpy.array([v0, 0.0, 0.0])
# initial condition for negative ion
rn[0,:] = numpy.array([0.0, 0.0, 0.0])
vn[0,:] = numpy.array([v0, 0.0, 0.0])
# Euler time steps
for it in range(0, len(t)1):
Bp = numpy.array([0.0, 0.0, B0])
Ap = QoverM * numpy.cross(vp[it,:], Bp)
vp[it+1] = vp[it] + dt*Ap
rp[it+1] = rp[it] + dt*vp[it]
An = QoverMn * numpy.cross(vn[it,:], Bp)
vn[it+1] = vn[it] + dt*An
rn[it+1] = rn[it] + dt*vn[it]
# Plot the particle's trajectory, in the xyplane
mpl.plot(rp[:,0], rp[:,1], label="Alpha particle")
mpl.plot(rn[:,0], rn[:,1], linestyle = "", label="H\(^\) ion")
mpl.xlabel("\(x\)")
mpl.ylabel("\(y\)")
mpl.title("Particle Trajectories in Uniform Magnetic Field")
mpl.legend(fontsize="xlarge")
mpl.xlim(13,13)
mpl.ylim(13,13)
Translations
Code  Language  Translator  Run  

Software Requirements
Android  iOS  Windows  MacOS  
with best with  Chrome  Chrome  Chrome  Chrome 
support fullscreen?  Yes. Chrome/Opera No. Firefox/ Samsung Internet  Not yet  Yes  Yes 
cannot work on  some mobile browser that don't understand JavaScript such as.....  cannot work on Internet Explorer 9 and below 
Credits
Fremont Teng; Loo Kang Wee
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Version:
 https://www.compadre.org/PICUP/exercises/exercise.cfm?I=111&A=ParticleInMagField
 http://weelookang.blogspot.com/2018/06/motionofchargedparticleinuniform.html
Other Resources
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end faq
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