PH504
Mon 15 SPS 110
Tue 11 KS25
Fri 11 MarLT2
Assignments:
MDS
1 Intro Math
3 Electrostatics
AGhP
3 Magnetostatics
1 Electromagnetic waves
4 Optics
MDS Topics:
1. Complex numbers, partial differentiation
2. Vectors
3. Review of PH301 section on EM
4. Coulomb’s law
5. Gauss’ law
6. Electric dipole
HW 2
7. Dipole in an external electric field HW 2
8. Isotropic dielectrics
HW 2
9. Gauss’ law in dielectrics
HW 2
10. Boundary conditions for E,D
HW 2
11. Capacitors
HW 2
12. Energy density in a capacitor
13. Stress on a conductor
14. Poisson/Laplace
15. Electrical images
HW 3
PH301: topics covered
Electric current. Resistivity, resistance. Electromotive force and
circuits. Energy and power in electric circuits.
Theory of metallic conduction. Resistors in series and in parallel.
Kirchhoff.s rules. Electrical measuring
instruments. RC, RL, LC and LRC circuits. Phasors and alternating
currents. Reactance. LRC series circuits. Series
and parallel resonance Potential dividers ,Thevenin.s theorem,
Maximum power transfer, Potentiometer, Bridge
circuits, The transformer.
Part 1. Mathematics (MDS – 3 lectures
The following provides a brief description and summary of the
mathematics required for PH504. Its main objective is to
provide a revision of the most important and relevant points. It
is not intended to teach the mathematics from scratch. For more
detailed treatments consult your first year mathematics’ notes or
textbooks. Some of the electromagnetism textbooks provide a
chapter or appendix covering the required mathematics.
1. Complex Numbers for AC Circuits Analysis
The voltage produced by a battery is a scalar quantity. So is the
resistance of a piece of wire (ohms), or the current through it (amps).
However, when we begin to analyze alternating current circuits, we find
that quantities of voltage, current, and even resistance (called impedance
in AC) are not the familiar one-dimensional quantities we're used to
measuring in DC circuits. Rather, these quantities, because they're
dynamic (alternating in direction and amplitude), possess other
dimensions that must be taken into account.
Frequency and phase shift are two of these dimensions that come into
play. Even with relatively simple AC circuits, where we're only dealing
with a single frequency, we still have the dimension of phase shift to
contend with in addition to the amplitude.
Here is where we need to abandon scalar numbers for something better
suited: complex numbers. Just like the example of giving directions from
one city to another, AC quantities in a single-frequency circuit have both
amplitude (analogy: distance) and phase shift (analogy: direction). A
complex number is a single mathematical quantity able to express these
two dimensions of amplitude and phase shift at once
When used to describe an AC quantity, the length of a vector represents
the amplitude of the wave while the angle of a vector represents the phase
angle of the wave relative to some other (reference) waveform.
Complex numbers are useful for AC circuit analysis because they provide
a convenient method of symbolically denoting phase shift between AC
quantities like voltage and current. A complex number consists of a real
and an imaginary part. Both the real and imaginary parts are real
numbers, but the imaginary part is multiplied with the square root of -1.
Complex numbers can be expressed in numerous forms.
Rectangular Form
A complex number in rectangular form looks like this

A = a + jb
where a is the real part and b is the imaginary part. j is sqrt(-1)
Adding and subtracting complex numbers in rectangular form is
carried out by adding or subtracting the real parts and then
adding and subtracting the imaginary parts.


(5 + j2) + (2 - j7) = (5 + 2) + j(2 - 7) = 7 - j5
(2 + j4) - (5 + j2) = (2 - 5) + j(4 - 2) = -3 + j2
Multiplying is slightly harder than addition or subtraction. It
must be carried out like the multiplication of two binomials,
multiplying both parts of one by both parts of the other.
(Remember that when you multiply the imaginary parts, j*j =
sqrt(-1) * sqrt(-1) = -1, so that part becomes real).

(2 + j2) (8 - j3) = (2 * 8) + j(2 * 8) + j(2 * -3) + j*j (2 * -3)
= 16 + j16 - j6 + 6 = 22 + j10
Division requires a new idea to be introduced. The complex
conjugate of a number is the number that has the same real part
as the original number but an imaginary part that differs only in
its sign. The complex conjugate is denoted by an asterisk
immediately following the number or variable.


A = (2 + j2)
A* = (2 + j2)* = 2 - j2
When dividing two complex numbers, you must first multiply
both the numerator and denominator by the complex conjugate
of the denominator. This multiplication results in a denominator
that has only a real part.

(4 + j3) / (2 + j2) = ((4 + j3) (2 - j2)) / ((2 + j2) (2 - j2)) =
((8 + 6) + j(8 - 6)) / ((4 + 4) + j(4 - 4)) = (14 + j2) / 8
= 7/4 + j/4
Polar Form
Another way to represent complex numbers is in polar form. If
you look at the real and imaginary parts of a complex number as
coordinates in a plane, then the real part would be the x
coordinate and the imaginary part the y coordinate. In
rectangular form, the x and y coordinate are specified in that
way. In polar form, the point in the plane is instead defined by a
magnitude and an angle. Polar form relates to rectangular form
in the following way.


(magnitude) r = sqrt(a² + b²)
(angle) theta = tan-1 b/a
and


a = r cos (theta)
b = r sin (theta)
A complex number is then represented as

A = r | theta
where r = magnitude = |A| and theta = angle = ang A
To find the conjugate of a complex number in polar form,
simply reverse the sign of the angle.


A = 5 | 25°
A* = 5 | -25°
Multiplication and division are much simpler for numbers in
polar form. With multiplication you multiply the magnitudes
and add the angles, and with division you divide the second
magnitude from the first and subtract the second angle from the
first.


(5 | 45° ) (2 | 20°) = (5)(2) | (45 + 20)° = 10 | 65°
(4 | 90°) / (2 | 45°) = 4/2 | (90 - 45)°
= 2 | 45°
To add or subtract we basically need to convert the numbers
back into rectangular form

(2 | 45°) + (8 | 30°)
= (2 cos 45° + 8 cos 30°) + j(2 sin 45° + 8 sin 30°)
= 8.342 + j2.414
The answer can then be converted back to polar form if desired



r = sqrt(8.342² + 2.414²) = 8.684
theta = tan-1 (2.414/8.342) = 16.1°
(2 | 45°) + (8 | 30°) = 8.684 | 16.1°
If possible is it best to add and subtract in rectangular form and
multiply and divide in rectangular form.
Complex Exponential Form
The complex exponential form is another way of representing a
complex number. The following formula shows how it relates
to rectangular and polar form

e j = cos () + j sin () = 1 | 
Basically, the complex exponential works in the same way as
polar form, multiplication and division are carried out simply by
multiplying (for multiplication) or dividing (for division) the
coefficients, and then adding (for multiplication) or subtracting
(for division) the angle. The complex exponential is important
for deriving formulas and is the basis for some of the methods of
circuit analysis, but from an algebraic standpoint it behaves in a
similar way as polar form.
http://www.shef.ac.uk/physics/teaching/phy205/mathematics
_for_electromagnetism.htm#solid
2. Partial Differentiation
Many physical quantities are a function of more than one
variable (e.g. the pressure of a gas depends upon both
temperature and volume, a magnetic field may be a
function of the three spatial co-ordinates (x,y,z) and time
(t)). Hence when differentiating a function there is usually
a choice of which variable we differentiate with respect to.
For example consider the function f which depends upon
the variables x and y (f(x,y)). We can differentiate f with
respect to x or y. When we differentiate with respect to a
given variable we proceed in the same manner as in basic
differentiation for functions which depend upon one
variable. However for functions of more than one variable
all other variables are treated as if they are constants. The
symbols for the differential are modified (‘’ is used instead
of ‘d’).
The derivatives of f with respect to x or y are written as
respectively.
Example f(x,y)=3x3+yx2+4xy2+5y3
We can also take higher order derivatives, e.g.
differentiate twice with respect to x
or differentiate with respect to one variable (say x ) and
then a second (y)
Note that for all well behaved functions the order in which
we differentiate (e.g. x then y or y then x) is unimportant,
i.e.
3. Angles and Solid Angles
We need to consider both normal (one-dimensional) and
solid (two-dimensional angles)
In (a) the line of length dl has a component dl cosalong
the arc of the circle. The angle is defined as this
component divided by the radius of the circle r.
The units are radians. As the circumference of a circle is
2r there are 2r/r=2 radians in a circle.
In (b) the area da makes an angle  to the surface of the
sphere radius r. The projection of da onto the surface of
the sphere is hence da cos  and the solid angle is
defined as this projection divided by the square of the
radius
The units are steradians. As the area of a sphere is 4r2
there are 4r2/r2=4 steradians in a sphere.
4. Vectors – Vector Analysis
Many physical quantities have a direction as well as a
magnitude. Examples are force velocity and, in
electromagnetism, electric and magnetic fields. We
describe such quantities using vectors. At each point in
space we can imagine an arrow whose length gives the
magnitude of the quantity it describes and whose direction
corresponds to the direction of the quantity.
We want: displacement + angular displacement
Vector components
In dealing with vectors it is often convenient to describe a
vector in terms of components. Because space has three-
dimensions, three components lying along three
orthogonal directions are required to describe any vector.
The most common system is the Cartesian one where the
three directions are the x, y and z-axes.
To define any vector A in the Cartesian system we need
the size of the components along the three axes (Ax, Ay
and Az) and three unit vectors that are parallel to the three
axes (i, j and k parallel to x, y and z respectively).
The vector A is given by
The magnitude of A is given by
Non-Cartesian Systems
Although the Cartesian system is the most common one
and the easiest to visualise and use, There are two other
system that are useful when considering problems with
cylindrical or spherical symmetry.
In the cylindrical system the three components of the
vector are defined as lying along the radial direction in the
x-y plane (r), the angle between the projection onto the x-y
plane and the x-axis (f) and the vertical or z component
(z).
In the spherical system the three components are along
the radial direction (r), the angle between the projection
onto the x-y plane and the x-axis (f) and the angle
between the vector and the z-axis ().
Addition of Vectors: associative and commutative
Multiplication of Vectors
There are two types of multiplication, the dot product,
resulting in a scalar and the vector product resulting in a
vector.
The dot product of two vectors (scalar product)
If we have two vectors A and B then the dot product of A
and B is defined as
where A and B are the magnitudes of vectors A and B
and  is the angle between the two vectors.
The dot product is commutative
Physically the dot product represents the projection of
one of the vectors on to the other times the magnitude of
the other. If the two vectors are mutually perpendicular
then the dot product is zero (cos 90o=0).
In Cartesian co-ordinates, if we have two vectors A and
B with components (Ax, Ay, Az) and (Bx, By, Bz)
respectively then
Physical application of the dot product
We know from mechanics that if a force F moves through
a distance L then the work done is equal to the component
of the force along the direction of movement multiplied by
L. In the diagram below the component of F along the
direction of movement is Fcos. Hence the work done is
FLcos . However if we use vectors F and L to describe
the force and the movement respectively we have from
the definition of the dot product . Hence when a force F is
moved by a distance L the work done is simply the dot
product of the two vectors. This is an application of the dot
product which we will use many times in the
electromagnetism course.
The cross product of two vectors (vector product)
If we have two vectors A and B then the cross product of
A and B is defined as
AB = AB sin n
Where n is a unit vector normal to the plane containing
the two vectors A and B and whose direction is given by
the right-hand rule.
The cross product of two vectors is not commutative as
sin(-) = - sin.
AB = - BA
In Cartesian co-ordinates the cross product of the
vectors A and B with components (Ax, Ay, Az) and (Bx,
By, Bz) is given by
AB = (AyBz-AzBy)i + (AzBx-AxBz)j + (AxBy-AyBx)k
The cross product of a vector with itself is zero as the
angle between the two vectors is 0 and sin(0)=0.
Physical application of the cross product
A force F acts at a distance r from a point of rotation. The
torque (T) about this point is the distance from where F
acts to the point of rotation (r) multiplied by the normal
component of F. T = rFsin , where  is the angle between
F and the line drawn through the point of rotation.
However if we define torque in terms of a vector whose
magnitude gives the size of the torque and whose
direction points along the axis of rotation then
T= rF where r is the vector from the point of rotation to
the point where F acts. The direction of T gives the sense
of rotation from the right-hand screw rule.
Triple scalar and vector products
>>>>>>>>>>>>>>>>>
5. Calculus of scalars and vectors
Much of physics is concerned with how one quantity
varies when one or more other quantities change. As in
other areas of physics, in electromagnetism we will be
concerned with the spatial variation (or derivative) of both
scalar and vector quantities.
The mathematics can be summarised by the use of a
differential operator called 'del' (symbol ) which itself has
directional properties.
There are three physically meaningful ways in which 
can be applied to scalars and vectors: it can be applied to
a scalar to give a vector (gradient), it can form the dot
product with a vector to give a scalar (divergence) and it
can form the cross product with a vector to give another
vector (curl).
Gradient 
The gradient of a scalar function f is written f or grad f
and is given in the Cartesian system by
The resultant quantity is a vector.
e.g. if f(x,y,z)=2x2+y3+z2xy then
f= i(4x+z2y) + j(3y2+z2x) + k 2xyz
Physical significance of the gradient. At any point the
gradient of a function points in the direction corresponding
to that for which the function varies most rapidly. The
magnitude of the gradient vector gives the size of this
maximum variation: the maximum directional derivative.
Example: If f(x,y) gives the height (or alternatively the z
co-ordinate) of a surface as a function of the x and y coordinates then at any point Ñf will point in the direction of
maximum slope of the surface.
A small ball placed on the surface will tend to roll along
the direction opposite to f. The gravitational force acting
on the ball is -mgf where m is its mass and g is the
acceleration due to gravity. The negative sign arises
because the force acts in the opposite direction to Ñf.
Alternatively if we define U(x,y) as the gravitational
potential energy of the ball (U(x,y)=mg f(x,y)) then the
gravitational force = -U. This is a general result: Force =
-gradient(potential energy). The potential energy may be
gravitational, electrical etc.
Divergence 
The divergence of a vector A is written as A or div A
and is given by
the resultant quantity is a scalar
e.g. if A = 3x2yz i + x2z2 j + z2k then ×A=6xyz+2z
Physical significance. When the divergence of a vector
is positive at a given point then there is a source of the
vector field at that point. A negative divergence implies a
sink for the vector field. We can hence think of the
divergence of a vector as telling us how much of the
vector field starts (or terminates) at a given point.
In (a) the vector has a constant magnitude so its
divergence is zero. In (b) the x-component increases
along the x-direction. This vector hence has a non-zero,
positive divergence.
Curl 
The curl of a vector A is written as A or curl A and is
given by
=
The latter is called the determinant.
The resultant is a vector
eg A = yzi-2x2yzj+3x2y2zk
A = (6x2yz--2x2z)i+(y-6xy2z)j+(-4xyz-z)k
Physical significance. A non-zero curl implies that the
corresponding vector field has a sort of rotational property.
One way to look for a curl is to imagine that the vector
field corresponds to the flow of water. If we place a small
paddle wheel in the field then the presence of a non-zero
curl suggests that the wheel will rotate.
In the above examples for (a) although the field increases
along the direction in which it points it produces no
rotation of the wheel. However in (b) the field points along
x but increases along the y-axis and hence produces a
rotation of the wheel. Hence the curl is related to how the
field changes as we move across the field. This can also
be seen because the expression for curl contains terms
Ax/y etc.
To some extent curl and div are complementary. The latter
requires that the field increases when moving along the
field direction, the former that the field increases when
moving across the field direction.
Relationships
From the definitions of grad, div and curl the following
relationships can be established
(f)=0 the curl of a gradient is equal to zero
(A)=0 the divergence of a curl is equal to zero
The Laplacian:
(f)=2f=
gradient 
this is the divergence of a
Non-cartesian co-ordinates
All of the previous examples are for cartesian co-
ordinates. For other systems related, but different,
expressions exist for grad, div and curl
e.g. in cylindrical co-ordinates the gradient is given by
For this course you do not need to remember the
expressions for non-cartesian systems but you need to
know how to apply them where necessary.
6. Integration
There are two main types of integration for vectors, line
and surface
Line integrals
The line integral of a vector A between the points a and b
is given by
as we move along a path between the points a and b, at
each step we take the component of A which lies along
the direction we are moving (given by the vector dl) and
multiply it by the distance we move through. The line
integral is the sum of all these individual values as we
move from a to b.
In general the path taken between the points a and b must
be specified. However for a certain class of vectors the
result of the integral is independent of the path taken.
Such vectors are said to be conservative.
If the line integral is performed around a closed path
(initial and final points are the same) then a circle is
placed on the integral symbol
If the vector A represents a force then the line integral of A
between two points gives the work done in moving
between these two points.
Surface integrals
The surface integral of the vector A over the surface s is
defined as
the surface is split into an infinite number of infinitesimally
small sections. For each section the product of the area of
the section (dS) and the component of A normal to the
surface is formed. The integral is the sum of all these
products. If the surface is a closed one (no edges) then a
circle is placed on the integral sign
Relationships between integrals
Divergence theorem (Gauss)
This states
in words 'The surface integral of any vector over a
closed surface S is equal to the divergence of that vector
integrated over the volume 

enclosed by S.'
Stokes' theorem
This states
- in words 'The line integral of any vector around a
closed path is equal to the surface integral of the curl of
that vector integrated over a surface S which is bounded
by the path of the line integral.'
THE END