Faris manifold
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Text by William G. Faris, dated September 25, 2008, kept in the Sjamaar Forms folder of the archive. The contents list covers 1-forms and the dual space, exact and closed forms, ODEs in the plane with integrating factors, the exterior derivative, integration on manifolds, Green's, Stokes's and Gauss's theorems, the divergence theorem, Riemannian metrics, and length and area. Each chapter ends with problems.
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Vector fields and differential forms
William G. Faris
September 25, 2008
ii
Contents
1 Forms 1
1.1 The dual space . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Differential 1-forms . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Ordinary differential equations in two dimensions . . . . . . . . . 4
1.4 Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2 The exterior derivative 7
2.1 The exterior product . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 Differential r-forms . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3 Properties of the exterior derivative . . . . . . . . . . . . . . . . 9
2.4 The integrability condition . . . . . . . . . . . . . . . . . . . . . . 10
2.5 Gradient, curl, divergence . . . . . . . . . . . . . . . . . . . . . . 11
2.6 Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3 Integration and Stokes’s theorem 13
3.1 One-dimensional integrals . . . . . . . . . . . . . . . . . . . . . . 13
3.2 Integration on manifolds . . . . . . . . . . . . . . . . . . . . . . . 14
3.3 The fundamental theorem . . . . . . . . . . . . . . . . . . . . . . 15
3.4 Green’s theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.5 Stokes’s theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.6 Gauss’s theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.7 The generalized Stokes’s theorem . . . . . . . . . . . . . . . . . . 17
3.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.9 Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4 The divergence theorem 21
4.1 Contraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.2 Duality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3 The divergence theorem . . . . . . . . . . . . . . . . . . . . . . . 23
4.4 Integration by parts . . . . . . . . . . . . . . . . . . . . . . . . . 24
4.5 Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
iii
iv CONTENTS
5 The metric 27
5.1 Inner product . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5.2 Riemannian metric . . . . . . . . . . . . . . . . . . . . . . . . . . 28
5.3 Gradient and divergence . . . . . . . . . . . . . . . . . . . . . . . 29
5.4 Gradient dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.5 The Laplace operator . . . . . . . . . . . . . . . . . . . . . . . . 30
5.6 Curl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.7 Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
6 Length and area 33
6.1 Length . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
6.2 Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
6.3 Divergence and Stokes theorems . . . . . . . . . . . . . . . . . . 35
Chapter 1
Forms
1.1 The dual space
The objects that are dual to vectors are 1-forms. A 1-form is a linear transfor-
mation from the n-dimensional vector space Vto the real numbers. The 1-forms
also form a vector space V∗of dimension n, often called the dual space of the
original space Vof vectors. If αis a 1-form, then the value of αon a vector
vcould be written as α(v), but instead of this we shall mainly use α·v. The
condition of being linear says that
α·(au+bv) =aα·u+bα·v. (1.1)
The vector space of all 1-forms is called V∗. Sometimes it is called the dual
space ofV.
It is important to note that the use of the dot in this context is not meant
to say that this is the inner product (scalar product) of two vectors. In Part
III of this book we shall see how to associate a form guto a vector u, and the
inner product of uwithwwill then be gu·w.
There is a useful way to picture vectors and 1-forms. A vector is pictured as
an arrow with its tail at the origin of the vector space V. A 1-form is pictured by
its contour lines (in two dimensions) or its contour planes (in three dimensions).
These are parallel lines or parallel planes that represent when the values of the
1-form are multiples of some fixed small number δ >0. Sometimes it is helpful
to indicate which direction is the direction of increase. The value α·vof a
1-form αon a vector vis the value associated with the contour that passes
through the head of the arrow.
Each contour line is labelled by a numerical value. In practice one only draws
contour lines corresponding to multiples of some fixed small numerical value.
Since this numerical value is somewhat arbitrary, it is customary to just draw
the contour lines and indicate the direction of increase. The contour line passing
through the origin has value zero. A more precise specification of the 1-form
would give the numerical value associated with at least one other contour line.
1
2 CHAPTER 1. FORMS
A scalar multiple cαof a 1-form αhas contour lines with increased or decreased
spacing, and possibly with reversed direction of increase. The sum α+βof two
1-forms α, βis defined by adding their values. The sum of two 1-forms may
also be indicated graphically by a parallelogram law. The two forms define an
array of parallelograms. The contour lines of the sum of the two forms are lines
through two (appropriately chosen) corners of the parallelograms.
1.2 Differential 1-forms
Adifferential form is a linear transformation from the vector fields to the reals
given by
α=nX
i=1aidxi. (1.2)
We identify a vector field vwith the corresponding directional derivative
v=nX
i=1vi∂
∂xi. (1.3)
The value of αon the vector field vis
α·v=nX
i=1aivi. (1.4)
Ifzis a scalar function on M, then it has a differential given by
dz=nX
i=1∂z
∂xidxi. (1.5)
This is a special kind of differential form. In general, a differential form that is
the differential of a scalar is called an exact differential form.
Ifzis a smooth function on M, and vis a vector field, then the directional
derivative ofzalong vis
dz·v=nX
i=1vi∂z
∂xi. (1.6)
It is another smooth function on M.
Theorem 1 (Necessary condition for exactness) Ifα=Pn
i=1aidxiis an
exact differential form, then its coefficients satisfy the integrability conditions
∂ai
∂xj=∂aj
∂xi. (1.7)
When the integrability condition is satisfied, then the differential form is
said to be closed . Thus the theorem says that every exact form is closed.
1.2. DIFFERENTIAL 1-FORMS 3
In two dimensions an exact differential form is of the form
dh(x, y) =∂h(x, y)
∂xdx+∂h(x, y)
∂ydy. (1.8)
Ifz=h(x, y) this can be written in a shorter notation as
dz=∂z
∂xdx+∂z
∂ydy. (1.9)
It is easy to picture an exact differential form in this two-dimensional case.
Just picture contour curves of the function z=h(x, y). These are curves defined
byz=h(x, y) =c, where the values of care spaced by some small δ >0. Notice
that adding a constant to zis does not change the differential of z. It also does
not change the contour curves of z. For determination of the differential form
what is important is not the value of the function, since this has an arbitrary
constant. Rather it is the spacing between the contour curves that is essential.
In this picture the exact differential form should be thought of a closeup
view, so that on this scale the contour curves look very much like contour lines.
So the differential form at a point depends only on the contour lines very near
this point.
In two dimensions a general differential form is of the form
α=f(x, y)dx+g(x, y)dy. (1.10)
The condition for a closed form is
∂g(x, y)
∂x=∂f(x, y)
∂y. (1.11)
If the form is not closed, then it is not exact. The typical differential form is
not closed.
We could also write this as
α=p dx+q dy. (1.12)
The condition for a closed form is
∂q
∂x=∂p
∂y. (1.13)
It somewhat harder to picture a differential 1-form that is not exact. The
idea is to draw contour lines near each point that somehow join to form contour
curves. However the problem is that these contour curves now must have end
points, in order to keep the density of lines near each point to be consistent with
the definition of the differential form.
Example. A typical example of a differential form that is not exact is y dx.
The contour lines are all vertical. They are increasing to the right in the upper
half plane, and they are increasing to the left in the lower half plane. However
the density of these contour lines must diminish near the xaxis, so that some
4 CHAPTER 1. FORMS
of the lines will have end points at their lower ends (in the upper half plane) or
at their upper ends (in the lower half plane).
A differential form may be expressed in various coordinate systems. Say, for
instance, that
α=p dx+q dy. (1.14)
We may write
dx=∂x
∂udu+∂x
∂vdv, (1.15)
dy=∂y
∂udu+∂y
∂vdv. (1.16)
Inserting this in the expression for the 1-form α, we obtain
α=µ∂x
∂up+∂y
∂uq¶
du+µ∂x
∂vp+∂y
∂v¶
dv. (1.17)
1.3 Ordinary differential equations in two di-
mensions
A classic application of these ideas is ordinary differential equations in the plane.
Such an equation is often written in the form
p dx+q dy= 0. (1.18)
Here p=f(x, y) and q=g(x, y) are functions of x, y. The equation is deter-
mined by the differential form p dx+q dy, but two different forms may determine
equivalent equations. For example, if µ=h(x, y) is a non-zero scalar, then the
form µp dx +µq dy is a quite different form, but it determines an equivalent
differential equation.
Ifp dx+q dyis exact, then p dx+q dy=dz, for some scalar zdepending
onxandy. The solution of the differential equation is then given implicitly by
z=c, where cis constant of integration.
Ifp dx+q dyis not exact, then one looks for an integrating factor µsuch
that
µ(p dx+q dy) =dz (1.19)
is exact. Once this is done, again the solution of the differential equation is then
given implicitly by z=c, where cis constant of integration.
Theorem 2 Suppose that α=p dx+q dyis a differential form in two dimen-
sions that is non-zero near some point. Then αhas a non-zero integrating factor
µnear the point, so µα=dsfor some scalar.
This theorem follows from the theory of solutions of ordinary differential
equations. Finding the integrating factor may not be an easy matter. However,
there is a strategy that may be helpful.
1.3. ORDINARY DIFFERENTIAL EQUATIONS IN TWO DIMENSIONS 5
Recall that if a differential form is exact, then it is closed. So if µis an
integrating factor, then
∂µp
∂y−∂µq
∂x= 0. (1.20)
This condition may be written in the form
p∂µ
∂y−q∂µ
∂x+µ∂p
∂y−∂q
∂x¶
µ= 0. (1.21)
Say that by good fortune there is an integrating factor µthat depends only
onx. Then this gives a linear ordinary differential equation for µthat may be
solved by integration.
Example. Consider the standard problem of solving the linear differential
equation
dy
dx=−ay+b, (1.22)
where a, bare functions of x. Consider the differential form ( ay−b)dx+dy. Look
for an integrating factor µthat depends only on x. The differential equation for
µis−dµ/dx =aµ. This has solution µ=eA, where Ais a function of xwith
dA/dx =a. Thus
eA(ay−b)dx+eAdy=d(eAy−S), (1.23)
where Sis a function of xwith dS/dx =eAb. So the solution of the equation is
y=e−A(S+c).
Theorem 3 Consider a differential form α=p dx+q dyin two dimensions.
Suppose that near some point αis not zero. Suppose also that αis not closed
near this point. Then near this point there is a new coordinate system u, vwith
α=u dv.
The proof is to note that if α=p dx+q dyis not zero, then it has a non-zero
integrating factor with µα=dv. So we can write α=u dv, where u= 1/µ.
Since u dv=p dx+q dy, we have u∂v/∂x =pandu∂v/∂y =q. It follows that
∂q/∂x −∂p/∂y =∂u/∂x∂v/∂y −∂u/∂y∂v∂x . Since this is non-zero, the inverse
function theorem shows that this is a legitimate change of coordinates.
The situation is already considerably more complicated in three dimensions,
the canonical form is relatively complicated. The differential equations book by
Ince [9] treats this situation.
6 CHAPTER 1. FORMS
1.4 Problems
1.Exact differentials. Is ( x2+y2)dx+ 2xy dy an exact differential form? If
so, write it as the differential of a scalar.
2.Exact differentials. Is (1 + ex)dy+ex(y−x)dxan exact differential? If
so, write it as the differential of a scalar.
3.Exact differentials. Is eydx+x(ey+ 1)dyan exact differential? If so,
write it as the differential of a scalar.
4.Constant differential forms. A differential form usually cannot be trans-
formed into a constant differential form, but there are special circum-
stances when that can occur. Is it possible to find coordinates u and v
near a given point (not the origin) such that
−y dx+x dy=du? (1.24)
5.Constant differential forms. A differential form usually cannot be trans-
formed into a constant differential form, but there are special circum-
stances when that can occur. Is it possible to find coordinates u and v
near a given point (not the origin) such that
−y
x2+y2dx+x
x2+y2dy=du? (1.25)
6.Ordinary differential equations. Solve the differential equation ( xy2+
y)dx−x dy= 0 by finding an integrating factor that depends only on y.
Chapter 2
The exterior derivative
2.1 The exterior product
LetV×Vbe the set of ordered pairs u,vof vectors in V. A2-form σis an
anti-symmetric bilinear transformation σ:V×V→R. Thus for each fixed v
the function u/mapsto→σ(u,v) is linear, and for each fixed uthe function v/mapsto→(u,v)
is linear. Furthermore, σ(u,v) =−σ(v,u). The vector space of all 2-forms is
denoted Λ2V∗. It is a vector space of dimension n(n−1)/2.
A 2-form has a geometric interpretation. First consider the situation in the
plane. Given two planar 2-forms, at least one of them is a multiple of the other.
So the space of planar 2-forms is one-dimensional. However we should not think
of such a 2-form as a number, but rather as a grid of closely spaced points.
The idea is that the value of the 2-form is proportional to the number of points
inside the parallelogram spanned by the two vectors. The actual way the points
are arranged is not important; all that counts is the (relative) density of points.
Actually, to specify the 2-form one needs to specify not only the points but also
an orientation, which is just a way of saying that the sign of the answer needs
to be determined.
In three-dimensional space one can think of parallel lines instead of points.
The space of 2-forms in three-dimensional space has dimension 3, because these
line can have various directions as well as different spacing. The value of the 2-
form on a pair of vectors is proportional to the number of lines passing through
the parallelogram spanned by the two vectors. Again, there is an orientation
associated with the line, which means that one can perhaps think of each line
as a thin coil wound in a certain sense.
The sum of two 2-forms may be given by a geometrical construction that
somewhat resembles vector addition.
Theexterior product (or wedge product) α∧βof two 1-forms is a 2-form.
This is defined by
(α∧β)(u,v) = det·α·uα·v
β·uβ·v¸
= (α·u)(β·v)−(β·u)(α·v).(2.1)
7
8 CHAPTER 2. THE EXTERIOR DERIVATIVE
Notice that α∧β=−β∧α. In particular α∧α= 0.
The exterior product of two 1-forms has a nice geometrical interpretation.
On two dimensions each of the two 1-forms is given by a family of parallel lines.
The corresponding 2-form consists of the points at the intersection of these lines.
In three dimensions each of the two 1-forms is given by a collection of parallel
planes. The corresponding 2-form consists of the lines that are the intersections
of these planes.
In a similar way, one can define a 3-form τas an alternating trilinear function
from ordered triples of vectors to the reals. In three dimensions a 3-form is
pictured by a density of dots.
One way of getting a 3-form is by taking the exterior product of three 1-
forms. The formula for this is
(α∧β∧γ)(u,v,w) = det2
4α·uα·vα·w
β·uβ·vβ·w
γ·uγ·vγ·w3
5 (2.2)
In a similar way one can define r-forms on an ndimensional vector space
V. The space of such r-forms is denoted ΛrV∗, and it has dimension given by
the binomial coefficient¡n
r¢
. It is also possible to take the exterior product of
r1-forms and get an r-form. The formula for this multiple exterior product is
again given by a determinant.
The algebra of differential forms is simple. The sum of two r-forms is an r
form. The product of an r-form and an s-form is an r+s-form. This multipli-
cation satisfies the associative law. It also satisfies the law
β∧α= (−1)rsα∧β, (2.3)
where αis an r-form and βis an s-form. For instance, if r=s= 1, then
α∧β=−β∧α. On the other hand, if r= 1, s= 2, then αβ=βα.
2.2 Differential r-forms
One can also have differential r-forms on a manifold. For instance, on three
dimensions one might have a differential 2-form such as
σ=a dy∧dz+b dz∧dx+c dx∧dy. (2.4)
Here x, y, z are arbitrary coordinates, and a, b, c are smooth functions of x, y, z .
Similarly, in three dimensions a typical 3-form might have the form
τ=s dx∧dy∧dz. (2.5)
Notice that these forms are created as linear combinations of exterior products
of 1-forms.
Since these expressions are so common, it is customary in many contexts
to omit the explicit symbol for the exterior product. Thus the forms might be
written
σ=a dy dz +b dz dx +c dx dy (2.6)
2.3. PROPERTIES OF THE EXTERIOR DERIVATIVE 9
and
τ=s dx dy dz. (2.7)
The geometric interpretation of such forms is quite natural. For instance, in
the three dimensional situation of these examples, a 1-form is represented by a
family of surfaces, possibly ending in curves. Near each point of the manifold
the family of surfaces looks like a family of parallel contour planes. A 2-form
is represented by a family of curves, possibly ending in points. Near each point
of the manifold they look like a family of parallel lines. Similarly, a 3-form is
represented by a cloud of points. While the density of points near a given point
of the manifold is constant, at distant points of the manifold the densities may
differ.
2.3 Properties of the exterior derivative
The exterior derivative of an r-form αis an r+ 1-form dα. It is defined by
taking the differentials of the coefficients of the r-form. For instance, for the
1-form
α=p dx+q dy+r dz (2.8)
the differential is
dα=dp dx +dq dy +dr dz. (2.9)
This can be simplified as follows. First, note that
dp=∂p
∂xdx+∂p
∂ydy+∂p
∂zdz. (2.10)
Therefore
dp dx =∂p
∂ydy dx +∂p
∂zdz dx =−∂p
∂ydx dy +∂p
∂zdz dx. (2.11)
Therefore, the final answer is
dα=d(p dx+q dy+r dz) =µ∂r
∂y−∂q
∂z¶
dy dz +µ∂p
∂z−∂r
∂x¶
dz dx +µ∂q
∂x−∂p
∂y¶
dx dy.
(2.12)
Similarly, suppose that we have a 2-form
σ=a dy dz +b dz dx +c dx dy. (2.13)
Then
dσ=da dy dz +db dz dx +dc dx dy =∂a
∂xdx dy dz +∂b
∂ydy dz dx +∂c
∂zdz dx dy.
(2.14)
This simplifies to
dσ=d(a dy dz +b dz dx +c dx dy ) =µ∂a
∂x+∂b
∂y+∂c
∂z¶
dx dy dz. (2.15)
10 CHAPTER 2. THE EXTERIOR DERIVATIVE
The geometrical interpretation of the exterior derivative is natural. Consider
first the case of two dimension. If αis a 1-form, then it is given by a family of
curves, possibly with end points. The derivative dαcorresponds to these end
points. They have an orientation depending on which end of the curve they are
at.
In three dimensions, if αis a 1-form, then it is given by contour surfaces,
possibly ending in curves. The 2-form dαis given by the curves. Also, if σis
a 2-form, then it is given by curves that may terminate. Then dσis a 3-form
represented by the termination points.
The exterior derivative satisfies various general properties. The exterior
derivative of an r-form is an r+ 1 form. There is a product rule
d(α∧β) =dα∧β+ (−1)rα∧dβ, (2.16)
where αis an r-form and βis an s-form. The reason for the ( −1)ris that the
dhas to be moved past the rform, and this picks up rfactors of −1. Another
important property is that applying the exterior derivative twice always gives
zero, that is, for an arbitrary s-form βwe have
ddβ= 0. (2.17)
2.4 The integrability condition
This last property has a geometrical interpretation. Take for example a scalar
s. Its differential is α=ds, which is an exact differential. Therefore dsis rep-
resented by curves without end points (two dimensions) or by surfaces without
ending curves (three dimensions). This explains why dα=dds= 0.
Similarly, consider a 1-form αin three dimensions. Its differential is a 2-form
σ=dα. The 1-form αis represented by surfaces, which may terminate in closed
curves. These closed curves represent the 2 form dα. Since they have no end
points, we see that dσ=ddα= 0.
In general, if dβ= 0, then we say that βis a closed form. If β=dα, we
say that βis an exact form. The general fact is that if βis exact, then βis
closed. The condition that dβ= 0 is called the integrability condition, since it
is necessary for the possibility that βcan be integrated to get αwith β=dα.
Example. Consider the 2-form y dx. This is represented by vertical lines
that terminate at points in the plane. The density of these lines is greater as
one gets farther from the xaxis. The increase is to the right above the xaxis,
and it is to the left below the yaxis. The differential of y dxisdy dx =−dx dy .
This 2-form represents the cloud of terminating points, which has a uniform
density. The usual convention that the positive orientation is counterclockwise.
So the orientations of these source points are clockwise. This is consistent with
the direction of increase along the contours lines.
2.5. GRADIENT, CURL, DIVERGENCE 11
2.5 Gradient, curl, divergence
Consider the case of three dimensions. Anyone familiar with vector analysis will
notice that if sis a scalar, then the formula for dsresembles the formula for the
gradient in cartesian coordinates. Similarly, if αis a 1-form, then the formula
fordαresembles the formula for the curl in cartesian coordinates. The formula
dds= 0 then corresponds to the formula curl grad s= 0.
In a similar way, if σis a 2-form, then the formula for dσresembles the
formula for the divergence in cartesian coordinates. The formula ddα= 0 then
corresponds to the formula div curl v= 0.
There are, however, important distinctions. First, the differential form for-
mulas take the same form in arbitrary coordinate systems. This is not true for
the formulas for the divergence, curl, and divergence. The reason is that the
usual definitions of divergence, curl, and divergence are as operations on vector
fields, not on differential forms. This leads to a much more complicated theory,
except for the very special case of cartesian coordinates on Euclidean space. We
shall examine this issue in detail in the third part of this book.
Second, the differential form formulas have natural formulations for mani-
folds of arbitrary dimension. While the gradient and divergence may also be
formulated in arbitrary dimensions, the curl only works in three dimensions.
This does not mean that notions such as gradient of a scalar (a vector field)
or divergence of a vector field (a scalar) are not useful and important. Indeed,
in some situations they play an essential role. However one should recognize
that these are relatively complicated objects. Their nature will be explored in
the second part of this book (for the divergence) and in the third part of this
book (for the gradient and curl).
The same considerations apply to the purely algebraic operations, at least
in three dimensions. The exterior product of two 1-forms resembles in some
way the cross product of vectors, while the exterior product of a 1-form and a
2-form resembles a scalar product of vectors. Thus the wedge product of three
1-forms resembles the triple scalar product of vector analysis. Again these are
not quite the same thing, and the relation will be explored in the third part of
this book.
12 CHAPTER 2. THE EXTERIOR DERIVATIVE
2.6 Problems
1.Say that the differential 1-form α=p dx+q dy+r dzhas an integrating
factor µ/negationslash= 0 such that µα=ds. Prove that α∧dα= 0. Also, express this
condition as a condition on p, q, r and their partial derivatives.
2.Show that α=dz−y dx−dyhas no integrating factor.
3.Show that the differential 1-form α=yz dx +xz dy +dzpasses the test
for an integrating factor.
4.In the previous problem it might be difficult to guess the integrating factor.
Show that µ=exyis an integrating factor, and find swith µα=ds.
5.The differential 2-form ω= (2xy−x2)dx dy is of the form ω=dα, where
αis a 1-form. Find such an α. Hint: This is too easy; there are many
solutions.
6.The differential 3-form σ= (yz+x2z2+ 3xy2z)dx dy dz is of the form
σ=dω, where ωis a 2-form. Find such an ω. Hint: Many solutions.
7.Letσ=xy2z dy dz −y3z dz dx +(x2y+y2z2)dx dy . Show that this 2-form
σsatisfies dσ= 0.
8.The previous problem gives hope that σ=dαfor some 1-form α. Find
such an α. Hint: This may require some experimentation. Try αof the
form α=p dx+q dy, where p, qare functions of x, y, z . With luck, this may
work. Remember that when integrating with respect to zthe constant of
integration is allowed to depend on x, y.
Chapter 3
Integration and Stokes’s
theorem
3.1 One-dimensional integrals
A one-dimensional manifold Cis described by a single coordinate t. Consider
an interval on the manifold bounded by t=aandt=b. There are two possible
orientations of this manifold, from t=atot=b, or from t=btot=a.
Suppose for the sake of definiteness that the manifold has the first orientation.
Then the differential form f(t)dthas the integral
Z
Cf(t)dt=Zt=b
t=af(t)dt. (3.1)
Ifsis another coordinate, then tis related to sbyt=g(s). Furthermore,
there are numbers p, qsuch that a=g(p) and b=g(q). The differential form
is thus f(t)dt=f(g(s))g/prime(s)ds. The end points of the manifold are s=pand
s=q. ThusZ
Cf(t)dt=Zs=q
s=pf(g(s))g/prime(s)ds. (3.2)
The value of the integral thus does not depend on which coordinate is used.
Notice that this calculation depends on the fact that dt/ds =g/prime(s) is non-
zero. However we could also consider a smooth function uon the manifold that
is not a coordinate. Several points on the manifold could give the same value of
u, and du/ds could be zero at various places. However we can express u=h(s)
anddu/ds =h/prime(s) and define an integral
Z
Cf(u)du=Zs=q
s=pf(h(s))h/prime(s)ds. (3.3)
Thus the differential form f(u)dualso has a well-defined integral on the mani-
fold, even though uis not a coordinate.
13
14 CHAPTER 3. INTEGRATION AND STOKES’S THEOREM
3.2 Integration on manifolds
Next look at the two dimensional case. Say that we have a coordinate system
x, yin a two-dimensional oriented manifold. Consider a region Rbounded by
curves x=a,x=b, and by y=c,y=d. Suppose that the orientation is such
that one goes around the region in the order a, bthen c, dthen b, athen d, c.
Then the differential form f(x, y)dx dy has integral
Z
Rf(x, y)dx dy =Zd
c"Zb
af(x, y)dx#
dy=Zb
a"Zd
cf(x, y)dy#
, dx. (3.4)
The limits are taken by going around the region in the order given by the
orientation, first a, bthen c, d. We could also have taken first b, athen d, cand
obtained the same result.
Notice, by the way, that we could also define an integral with dy dx in place
ofdx dy . This would be
Z
Rf(x, y)dy dx =Za
b"Zd
cf(x, y)dy#
dx=Zd
c·Za
bf(x, y)dx¸
, dy. (3.5)
The limits are taken by going around the region in the order given by the
orientation, first c, dthen b, a. We could also have taken d, cthen a, band
obtained the same result. This result is precisely the negative of the previous
result. This is consistent with the fact that dy dx =−dx dy .
These formula have generalizations. Say that the region is given by letting
xgo from atobandyfrom h(x) tok(x). Alternatively, it might be given by
letting ygo from ctodandxfrom p(y) toq(y). This is a more general region
than a rectangle, but the same kind of formula applies:
Z
Rf(x, y)dx dy =Zd
c"Zq(y)
p(y)f(x, y)dx#
dy=Zb
a"Zk(x)
h(x)f(x, y)dy#
, dx.
(3.6)
There is yet one more generalization, to the case where the differential form
isf(u, v)du dv , but u, vdo not form a coordinate system. Thus, for instance,
the 1-form dumight be a multiple of dvat a certain point, so that du dv would
be zero at that point. However we can define the integral by using the customary
change of variable formula:
Z
Rf(u, v)du dv =Z
Rf(u, v)µ∂u
∂x∂v
∂y−∂v
∂x∂u
∂y¶
dx dy. (3.7)
In fact, since du=∂u/∂x dx +∂u/∂y dy anddv=∂v/∂x dx +∂v/∂y dy , this is
just saying that the same differential form has the same integral.
In fact, we could interpret this integral directly as a limit of sums involving
only the u, vincrements. Partition the manifold by curves of constant xand
3.3. THE FUNDAMENTAL THEOREM 15
constant y. This divides the manifold into small regions that look something
like parallelograms. Then we could write this sum as
Z
Rf(u, v)du dv≈X
f(u, v) (∆ux∆vy−∆vx∆uy). (3.8)
Here the sum is over the parallelograms. The quantity ∆ uxis the increment in
ufrom xtox+ ∆x, keeping yfixed, along one side of the parallelogram. The
quantity ∆ vyis the increment in vfrom ytoy+ ∆y, keeping yfixed, along one
side of the parallelogram. The other quantities are defined similarly. The u, v
value is evaluated somewhere inside the parallelogram. The minus sign seems a
bit surprising, until one realizes that going around the oriented boundary of the
parallelogram the proper orientation makes a change from xtox+ ∆xfollowed
by a change from ytoy+∆y, or a change from ytoy+∆yfollowed by a change
from x+ ∆xtox. So both terms have the form ∆ u∆v, where the changes are
now taken along two sides in the proper orientation, first the change in u, then
the change in v.
3.3 The fundamental theorem
The fundamental theorem of calculus says that for every scalar function swe
have Z
Cds=s(Q)−s(P). (3.9)
Here Cis an oriented path from point Pto point Q. Notice that the result does
not depend on the choice of path. This is because dsis an exact form.
As an example, we can take a path in space. Then ds=∂s/∂x dx +
∂s/∂y dy +∂s/∂z dz . So
Z
Cds=Z
C∂s
∂xdx+∂s
∂ydy+∂z
∂zdz=Z
Cµ∂s
∂xdx
dt+∂s
∂ydy
dt+∂z
∂zdz
dt¶
dt.(3.10)
By the chain rule this is just
Z
Cds=Z
Cds
dtdt=s(Q)−s(P). (3.11)
3.4 Green’s theorem
The next integral theorem is Green’s theorem. It says that
Z
Rµ∂q
∂x−∂p
∂y¶
dx dy =Z
∂Rp dx+q dy. (3.12)
Here Ris an oriented region in two dimensional space, and ∂Ris the curve that
is its oriented boundary. Notice that this theorem may be stated in the succinct
form Z
Rdα=Z
∂Rα. (3.13)
16 CHAPTER 3. INTEGRATION AND STOKES’S THEOREM
The proof of Green’s theorem just amounts to applying the fundamental
theorem of calculus to each term. Thus for the second term one applies the
fundamental theorem of calculus in the xvariable for fixed y.
Z
R∂q
∂xdx dy =Zd
c"Z
Cyq dx#
dy=Zd
c£
q(C+
y)−q(C−
y)¤
dy. (3.14)
This isZd
cq(C+
y)dy+Zc
dq(C−
y)dy=Z
∂Rq dy. (3.15)
The other term is handled similarly, except that the fundamental theorem of
calculus is applied with respect to the xvariable for fixed y. Then such regions
can be pieced together to give the general Green’s theorem.
3.5 Stokes’s theorem
The most common version of Stokes’s theorem says that for a oriented two
dimensional surface Sin a three dimensional manifold with oriented boundary
curve ∂Swe have
Z
Sµ∂r
∂y−∂q
∂z¶
dy dz +µ∂p
∂z−∂r
∂x¶
dz dx +µ∂q
∂x−∂p
∂y¶
dx dy =Z
∂S(p dx+q dy+r dz).
(3.16)
Again this has the simple form
Z
Sdα=Z
∂Sα. (3.17)
This theorem reduces to Green’s theorem. The idea is to take coordinates
u, von the surface Sand apply Green’s theorem in the u, vcoordinates. In the
theorem the left hand side is obtained by taking the form p dx+q dy+r dzand
applying dto it. The key observation is that when the result of this is expressed
in the u, vcoordinates, it is the same as if the form p dx+q dy+r dzwere first
expressed in the u, vcoordinates and then dwere applied to it. In this latter
form Green’s theorem applies directly.
Here is the calculation. To make it simple, consider only the p dx term.
Then taking dgives
d(p dx) =µ∂p
∂xdx+∂p
∂ydy+∂p
∂zdz¶
dx=∂p
∂zdz dx−∂p
∂ydx dy. (3.18)
Inu, vcoordinates this is
d(p dx) =·∂p
∂zµ∂z
∂u∂x
∂v−∂x
∂u∂z
∂v¶
−∂p
∂yµ∂x
∂u∂y
∂v−∂y
∂u∂x
∂v¶¸
du dv. (3.19)
There are four terms in all.
3.6. GAUSS’S THEOREM 17
Now we do it in the other order. In u, vcoordinates we have
p dx=p∂x
∂udu+p∂x
∂vdv. (3.20)
Taking dof this gives
dµ
p∂x
∂udu+p∂x
∂vdv¶
=·∂
∂uµ
p∂x
∂v¶
−∂
∂vµ
p∂x
∂u¶¸
du dv. (3.21)
The miracle is that the second partial derivatives cancel. So in this version
dµ
p∂x
∂udu+p∂x
∂vdv¶
=·∂p
∂u∂x
∂v−∂p
∂v∂x
∂u¸
du dv. (3.22)
Now we can express ∂p/∂u and∂p/∂v by the chain rule. This gives at total of
six terms. But two of them cancel, so we get the same result as before.
3.6 Gauss’s theorem
LetWbe an oriented three dimensional region, and let ∂Wbe the oriented
surface that forms its boundary. Then Gauss’s theorem states that
Z
Wµ∂a
∂x+∂b
∂y+∂c
∂z¶
dx dy dz =Z
∂Wa dy dz +b dz dx +c dx dy. (3.23)
Again this has the form Z
Wdσ=Z
∂Wσ, (3.24)
where now σis a 2-form. The proof of Gauss’s theorem is similar to the proof
of Green’s theorem.
3.7 The generalized Stokes’s theorem
The generalized Stoke’s theorem says that
Z
Ωdω=Z
∂Ωω. (3.25)
Here ωis a (k−1)-form, and dωis ak-form. Furthermore, Ω is a kdimensional
region, and ∂Ω is its ( k−1)-dimensional oriented boundary. The forms may be
expressed in arbitrary coordinate systems.
3.8 References
A classic short but rigorous account of differential forms is given in the book of
Spivak [15]. The book by Agricola and Friedrich [1] gives a more advanced
18 CHAPTER 3. INTEGRATION AND STOKES’S THEOREM
treatment. Other books on differential forms include those by Cartan [2],
do Carmo [3], Edelen [4], Flanders [7], Screiber [14], and Weintraub [17]. There
are also advanced calculus texts by Edwards [5] and by Hubbard and Hub-
bard [8].
There are many sources for tensor analysis; a classical treatment may be
found in Lovelock and Rund [10]. There is a particularly unusual and sophis-
ticated treatment in the book of Nelson [12]. Differential forms are seen to be
special kinds of tensors: covariant alternating tensors.
The most amazing reference that this author has encountered is an elemen-
tary book by Weinreich [16]. He presents the geometric theory of differential
forms in pictures, and these pictures capture the geometrical essence of the sit-
uation. The principal results of the theory are true by inspection. However his
terminology is most unusual. He treats only the case of dimension three. Thus
he has the usual notion of covariant 1-form, 2-form, and 3-form. In his termi-
nology the corresponding names for these are stack, sheaf, and scalar density
(or swarm). There are also corresponding contravariant objects corresponding
to what are typically called 1-vector, 2-vector (surface element), and 3-vector
(volume element). The names in this case are arrow, thumbtack, and scalar
capacity. The correspondence between his objects and the usual tensors may
actually be slightly more complicated than this, but the intent is certainly to
explicate the usual calculus geometrically. In particular, he gives geometric ex-
planations of the usual algebraic and differential operations in all these various
cases.
3.9. PROBLEMS 19
3.9 Problems
1.LetCbe the curve x2+y2= 1 in the first quadrant from (1 ,0) to (0 ,1).
Evaluate Z
Cxy dx + (x2+y2)dy. (3.26)
2.LetCbe a curve from (2 ,0) to (0 ,3). Evaluate
Z
C2xy dx + (x2+y2)dy. (3.27)
3.Consider the problem of integrating the differential form
α=−y
x2+y2dx+x
x2+y2dy (3.28)
from (1 ,0) to ( −1,0) along some curve avoiding the origin. There is are
an infinite set of possible answers, depending on the curve. Describe all
such answers.
4.LetRbe the region x2+y2≤1 with x≥0 and y≥0. Let ∂Rbe its
boundary (oriented counterclockwise). Evaluate directly
Z
∂Rxy dx + (x2+y2)dy. (3.29)
5.This continues the previous problem. Verify Green’s theorem in this spe-
cial case, by explicitly calculating the appropriate integral over the region
R.
6.Let
α=−y dx+x dy+xy dz. (3.30)
Fixa >0. Consider the surface Sthat is the hemisphere x2+y2+z2=
a2with z≥0. Integrate αover the boundary ∂Sof this surface (a
counterclockwise circle in the x, yplane).
7.This continues the previous problem. Verify Stokes’s theorem in this spe-
cial case, by explicitly calculating the appropriate integral over the surface
S.
8.Letσ=xy2z dy dz −y3z dz dx + (x2y+y2z2)dx dy . Integrate σover the
sphere x2+y2+z2=a2. Hint: This should be effortless.
20 CHAPTER 3. INTEGRATION AND STOKES’S THEOREM
Chapter 4
The divergence theorem
4.1 Contraction
There is another operation called interior product (or contraction). In the case
of interest to us, it is a way of defining the product of a vector with a k-form
to get a k−1 form. We shall mainly be interested in the case when k= 1,2,3.
When k= 1 this is already familiar. For a 1-form αthe interior product u⌋αis
defined to be the scalar α·v.
The interior product of a vector uwith a 2-form σis a 1-form u⌋σ. It is
defined by
(u⌋σ)·v=σ(u,v). (4.1)
This has a nice picture in two dimensions. The vector uis an arrow. In two
dimensions the 2-form σis given by a density of points. The contour lines of
the interior product 1-form are parallel to the arrow. The get them, arrange the
points defining the 2-form to be spaced according to the separation determined
by the arrow (which may require some modification in the other direction to
preserve the density). Then take the contour lines to be spaced according to
the new arrangement of the points. These contour lines are the contour lines
corresponding to the interior product 1-form.
In three dimensions the 2-form σis given by lines. The arrow uand the lines
determining σdetermine a family of parallel planes. To get these contour planes,
do the following. Arrange the lines that determine σto be spaced according to
the separation determined by the arrow (which may require some modification
in the other direction to preserve the density). Then take the contour planes
to be spaced according to the new separation between the lines. The resulting
planes are the contour planes of the interior product 1-form.
The interior product u⌋ωof a vector uwith a 3-form ωis a 2-form u⌋ω. It
is defined by
(u⌋ω)(v,w) =ω(u,v,w). (4.2)
(The case of a general r-form is similar.)
21
22 CHAPTER 4. THE DIVERGENCE THEOREM
The picture is similar. Consider three dimensions. The vector uis an arrow,
and the associated 2-form u⌋ωis given by lines that are parallel to the arrow.
To get these contour lines, do the following. Arrange the points that determine
ωto be spaced according to the separation determined by the arrow. Then
take the contour lines to be spaced according to the new separation between the
points.
One interesting property of the interior product is that if αis an r-form and
βis an s-form, then
u⌋(α∧β) = (u⌋α)∧β+ (−1)rα∧(u⌋β). (4.3)
This is a kind of triple product identity.
In particular, we may apply this when r= 1 and s=n. Since βis an n-form,
it follows that α∧β= 0. Hence we have in this special case
(α·u)β=α∧(u⌋β). (4.4)
Another application is with two 1-forms βandγ. In this case it gives
a⌋(β∧γ) = (β·a)γ−(γ·a)β. (4.5)
So the interior product of a vector with β∧γis a linear combination of βand
γ.
Later we shall see the connection with classical vector algebra in three di-
mensions. The exterior product β∧γis an analog of the cross product, while
α∧β∧γis an analog of the triple scalar product. The combination −a⌋(β∧γ)
will turn out to be an analog of the triple vector product.
4.2 Duality
Consider an n-dimensional manifold. The new feature is a given n-form, taken
to be never zero. We denote this form by vol. In coordinates it is of the form
vol =√g du 1···dun. (4.6)
This coefficient√gdepends on the coordinate system. The choice of the no-
tation√gfor the coefficient will be explained in the following chapter. (Then√gwill be the square root of the determinant of the matrix associated with the
Riemannian metric for this coordinate system.)
The most common examples of volume forms are the volume in vol =
dx dy dz in cartesian coordinates and the same volume vol = r2sin(θ)dr dθ dφ
in spherical polar coordinates. The convention we are using for spherical polar
coordinates is that θis the co-latitude measured from the north pole, while φis
the longitude. We see from these coordinates that the√gfactor for cartesian
coordinates is 1, while the√gfactor for spherical polar coordinates is r2sin(θ).
In two dimensions it is perhaps more natural to call this area. So in cartesian
coordinates area = dx dy , while in polar coordinates area = r dr dφ .
4.3. THE DIVERGENCE THEOREM 23
For each scalar field sthere is an associated n-form svol. The scalar field
and the n-form determine each other in an obvious way. They are said to be
dual to each other, in a certain special sense.
For each vector field vthere is an associated n−1 form given by v⌋vol.
The vector field and the n−1 form are again considered to be dual to each
other, in this same sense. If vis a vector field, then v⌋vol might be called the
corresponding flux. It is an n−1 form that describes how much vis penetrating
a given n−1 dimensional surface.
In two dimensions a vector field is of the form
u=a∂
∂u+b∂
∂v. (4.7)
The area form is
area =√g du dv. (4.8)
The corresponding flux is
u⌋area =√g(a dv−b du). (4.9)
In three dimensions a vector field is of the form
u=a∂
∂u+b∂
∂v+c∂
∂w. (4.10)
The volume form is
vol =√g du dv dw. (4.11)
The corresponding flux is
√g(a dv dw +b dw du +c du dv ). (4.12)
4.3 The divergence theorem
The divergence of a vector field vis defined to be the scalar div vsuch that
d(u⌋vol) = div uvol. (4.13)
In other words, it is the dual of the differential of the dual.
The general divergence theorem then takes the form
Z
Wdivuvol =Z
∂Wu⌋vol. (4.14)
In two dimensions the divergence theorem says that
Z
R1√gµ∂√ga
∂u+∂√gb
∂v¶
area =Z
∂R√g(a dv−b du). (4.15)
Here the area form is√g du dv , where the particular form of√gis that associ-
ated with the u, vcoordinate system. Notice that the coefficients in the vector
24 CHAPTER 4. THE DIVERGENCE THEOREM
field are expressed with respect to a coordinate basis. We shall see in the next
part of this book that this is not the only possible choice.
A marvellous application of the divergence theorem in two dimensions is the
formula Z
Rdx dy =1
2Z
∂Rx dy−y dx. (4.16)
This says that one can determine the area by walking around the boundary. It
is perhaps less mysterious when one realizes that x dy−y dx=r2dφ.
In three dimensions the divergence theorem says that
Z
W1√gµ∂√ga
∂u+∂√gb
∂v+∂√gc
∂w¶
vol =Z
∂W√g(a dv dw +b dw du +c du dv ).
(4.17)
Here the volume form is√g du dv dw , where the particular form of√gis that
associated with the u, v, w coordinate system. Again the coefficients a, b, c of the
vector field are expressed in terms of the coordinate basis vectors ∂/∂u, ∂/∂v, ∂/∂w .
This is the the only possible kind of basis for a vector field, so in some treat-
ments the formulas will appear differently. They will be ultimately equivalent
in terms of their geometrical meaning.
The divergence theorem says that the integral of the divergence of a vector
field over Wwith respect to the volume is the integral of the flux of the vector
field across the bounding surface ∂W. A famous application in physics is when
the vector field represents the electric field, and the divergence represents the
density of charge. So the amount of charge in the region determines the flux of
the electric field through the boundary.
4.4 Integration by parts
An important identity for differential forms is
d(sω) =ds∧ω+sdω. (4.18)
This gives an integration by parts formula
Z
Wds∧ω+Z
Wsdω=Z
∂Wsω. (4.19)
Apply this to ω=u⌋vol and use ds∧u⌋vol = ds·uvol. This gives the
divergence identity
div (su) =ds·u+sdivu. (4.20)
From this we get another important integration by parts identity
Z
Wds·uvol +Z
Wsdivuvol =Z
∂Wsu⌋vol. (4.21)
4.5. PROBLEMS 25
4.5 Problems
1.Letr2=x2+y2+z2, and let
v=1
r3µ
x∂
∂x+y∂
∂y+z∂
∂z¶
. (4.22)
Let vol = dx dy dz . Show that
σ=v⌋vol =1
r3(x dy dz +y dz dx +z dx dy ). (4.23)
2.In the preceding problem, show directly that dσ= 0 away from r= 0.
3.Find σin spherical polar coordinates. Hint: This can be done by blind
computation, but there is a better way. Express vin spherical polar
coordinates, using Euler’s theorem
r∂
∂r=x∂
∂x+y∂
∂y+z∂
∂z. (4.24)
Then use vol = r2sin(θ)dr dθ dφ to calculate σ=v⌋vol.
4.In the preceding problem, show that dσ= 0 away from r= 0 by a spherical
polar coordinate calculation.
5.LetSbe the sphere of radius a >0 centered at the origin. Calculate the
integral of σoverS.
6.LetQbe the six-sided cube with side lengths 2 Lcentered at the origin.
Calculate the integral of σoverQ. Hint: Given the result of the preceding
problem, this should be effortless.
26 CHAPTER 4. THE DIVERGENCE THEOREM
Chapter 5
The metric
5.1 Inner product
Aninner product on a vector space Vis a real function gthat takes a pair of
input vectors u,vand produces a number gu·v. It is required to be a bilinear,
symmetric, positive, non-degenerate form. That is, it satisfies the following
axioms:
1.The form is bilinear: The function gu·vis linear in uand also linear in
v.
2.The form is symmetric: gu·v=gv·u.
3.The form is non-degenerate: gu·u= 0 implies u= 0.
4.The form is positive: gu·u≥0,
An inner product gdefines a linear transformation g:V→V∗. That is,
the value of gonuinVis the linear function from Vto the real numbers that
sends vtogu·v. Thus guis such a function, that is, an element of the dual
space V∗.
Since the form gis non-degenerate, the linear transformation gfrom VtoV∗
is an isomorphism of vector spaces. Therefore it has an inverse g−1:V∗→V.
Thus if ωis a linear form in V∗, the corresponding vector u=g−1ωis the
unique vector usuch that gu·v=ω·v.
In short, once one has a given inner product, one has a tool that tends to
erase the distinction between a vector space and its dual space. It is worth
noting that in relativity theory there is a generalization of the notion of inner
product in which the form is not required to be positive. However it still gives
such an isomorphism between vector space and dual space.
27
28 CHAPTER 5. THE METRIC
5.2 Riemannian metric
A smooth assignment of an inner product for the tangent vectors at each point
of a manifold is called a Riemannian metric . It is very convenient to choose
coordinates so that the Riemannian metric is diagonal with respect to this
coordinate system. In this case it has the form
g=h2
1du2
1+h2
2du2
2+···+h2
ndu2
n. (5.1)
Here each coefficient hiis a function of the coordinates u1, . . . , u n. The differ-
entials is not interpreted in the sense of differential forms. Rather, what this
means is that gtakes vector fields to differential forms by
gµ
a1∂
∂u1+···an∂
∂un¶
=a1h2
1du1+···anh2
ndun (5.2)
It is not always possible to find such a coordinate system for which the Rieman-
nian metric is diagonal. However this can always be done when the dimension
n≤3, and it is very convenient to do so. Such a coordinate system is called a
system of orthogonal coordinates . See the book by Eisenhart [6] for a discussion
of this point.
When we have orthogonal coordinates, it is tempting to make the basis
vectors have length one. Thus instead of using the usual coordinate basis vectors
∂
∂uione uses the normalized basis vectors1
hi∂
∂ui. Similarly, instead of using
the usual coordinate differential forms duione uses the normalized differentials
hidui. Then
gµ
a11
h1∂
∂u1+···an1
hn∂
∂un¶
=a1h1du1+···anhndun (5.3)
When you use the normalized basis vectors, the coefficients do not change.
In orthogonal coordinates the volume is given by
vol =√g du 1···dun=h1···hndu1∧ ··· ∧ dun. (5.4)
A simple example of orthogonal coordinates is that of polar coordinates r, φ
in the plane. These are related to cartesian coordinates x, yby
x=rcos(φ) (5.5)
y=rsin(φ) (5.6)
The Riemannian metric is expressed as
g=dr2+r2dφ2. (5.7)
The normalized basis vectors are∂
∂rand1
r∂
∂φ. The normalized basis forms are
drandr dφ. The area form is r dr∧dφ.
Warning: Even though coordinate forms like dφare closed forms, a normal-
ized form like r dφ need not be a closed form. In fact, in this particular case
d(rφ) =dr∧dφ/negationslash= 0.
5.3. GRADIENT AND DIVERGENCE 29
Another example of orthogonal coordinates is that of spherical polar coor-
dinates r, θ, φ . These are related to cartesian coordinates x, y, z by
x=rcos(φ) sin(θ) (5.8)
y=rsin(φ) sin(θ) (5.9)
z=rcos(θ) (5.10)
The Riemannian metric is expressed as
g=dr2+r2dθ2+r2sin2(θ)dφ2. (5.11)
The normalized basis vectors are∂
∂rand1
r∂
∂θand1
rsin(θ)∂
∂φ. The normalized
basis forms are drandr dθandrsin(θ)dφ. The volume form is r2sin(θ)dr∧
dθ∧dφ.
In these examples one could always use cartesian coordinates. However there
are manifolds that cannot be naturally described by cartesian coordinates, but
for which orthogonal coordinates are available. A simple example is the sphere
of constant radius a. The Riemannian metric is expressed by
g=a2dθ2+a2sin2(θ)dφ2. (5.12)
The normalized basis vectors are1
a∂
∂θand1
asin(θ)∂
∂φ. The normalized basis
forms are a dθandasin(θ)dφ. The area form is a2sin(θ)dθ∧dφ.
5.3 Gradient and divergence
Iffis a scalar field, then its gradient is
∇f= grad f=g−1d f. (5.13)
Since duis a 1-form, and the inverse of the metric g−1maps 1-forms to vector
fields, the gradient ∇fis a vector field.
In orthogonal coordinates ∇fhas the form
∇f=nX
i=11
h2
i∂f
∂ui∂
∂ui. (5.14)
In terms of normalized basis vectors this has the equivalent form
∇f=nX
i=11
hi∂f
∂ui1
hi∂
∂ui. (5.15)
Ifuis a vector field, then its divergence ∇ ·uis a scalar field given by
requiring that
(divu)vol = ( ∇ ·u)vol = d(u⌋vol). (5.16)
30 CHAPTER 5. THE METRIC
Here vol = h1···hndu1∧···dunis the volume form. Say that uhas an expres-
sion in terms of normalized basis vectors of the form
u=nX
i=1ai1
hi∂
∂ui. (5.17)
Then
divu=∇ ·u=nX
i=11
h1···hn∂
∂uiµh1···hn
hiai¶
. (5.18)
5.4 Gradient dynamics
A scalar function fhas both a differential d fand a gradient g−1d f. What can
the gradient do that the differential cannot do? Well, the gradient is a vector
field, so it has an associated system of differential equations
dui
dt=1
h2
i∂f
∂ui. (5.19)
Along a solution of this equation the function fsatisfies
d f
dt=nX
i=1∂f
∂ui∂ui
∂t=nX
i=11
h2
iµ∂f
∂ui¶2
≥0. (5.20)
In more geometrical language this says that
d f
dt=d f·g−1d f≥0. (5.21)
Along every solution fis increasing in time. If instead you want decrease, you
can follow the negative of the gradient.
5.5 The Laplace operator
The Laplace operator ∇2is defined as
∇2f=∇ · ∇ f. (5.22)
This can also be written
∇2f= div grad f. (5.23)
In coordinates the Laplacian has the form
∇2f=1
h1···hnnX
i=1∂
∂uiµh1···hn
h2
i∂f
∂ui¶
(5.24)
For example, in three dimensions with cartesian coordinates it is
∇2f=∂2f
∂x2+∂2f
∂y2+∂2f
∂z2. (5.25)
5.6. CURL 31
In spherical polar coordinates it is
∇2f=1
r2sin(θ)·∂
∂rr2sin(θ)∂f
∂r+∂
∂θsin(θ)∂f
∂θ+∂
∂φ1
sin(θ)∂f
∂φ¸
.(5.26)
This is often written
∇2f=1
r2∂
∂rr2∂f
∂r+1
r2·1
sin(θ)∂
∂θsin(θ)∂f
∂θ+1
sin2(θ)∂2f
∂φ2¸
. (5.27)
5.6 Curl
The remaining objects are in three dimensions.
The cross product of two vectors vandwis defined as the unique vector
v×wsuch that
(v×w)⌋vol = gv∧gw. (5.28)
In other words, it is the operation on vectors that corresponds to the exterior
product on forms.
The curl of a vector field vis defined by
(curlv)⌋vol = d(gv). (5.29)
The curl has a rather complicated coordinate representation. Say that in a
system of orthogonal coordinates
v=a1
hu∂
∂u+b1
hv∂
∂v+c1
hw∂
∂w. (5.30)
Thus the vector field is expressed in terms of normalized basis vectors. Then
gv=ahudu+bhvdv+chwdw. (5.31)
So
d(gv) =µ∂hwc
∂v−∂hvb
∂w¶
dv∧dw+µ∂hua
∂w−∂hwc
∂u¶
dw∧du+µ∂hvb
∂u−∂hua
∂v¶
du∧dv.
(5.32)
It follows that
curlv=1
hvhwµ∂hwc
∂v−∂hvb
∂w¶1
hu∂
∂u+1
huhwµ∂hua
∂w−∂hwc
∂u¶1
hv∂
∂hv+1
huhvµ∂hvb
∂u−∂hua
∂v¶1
hw∂
∂hw.
(5.33)
The reason for writing it this way is to express it again in terms of normal-
ized basis vectors. Notice also that if we express the derivatives as normalized
derivatives, then the expression is reasonably natural. For instance, the first
term is 1 /hwtimes the derivative (1 /hv)∂/∂v ) ofhwtimes the coefficient. The
only odd thing is that the hwis inside the derivative, while the 1 /hwis outside
the derivative.
32 CHAPTER 5. THE METRIC
It is easy to see that curl grad f= 0 and that div curl v= 0.
Stokes’s theorem says that
Z
Scurlv⌋vol =Z
∂Sgv. (5.34)
Of course, this is just saying that
Z
Sd(gv) =Z
∂Sgv, (5.35)
which is much simpler, since most of the effect of the metric has now cancelled
out.
5.7 Problems
1.This problem is three dimensional. Compute the Laplacian of 1 /rvia a
cartesian coordinate calculation.
2.This problem is three dimensional. Compute the Laplacian of 1 /rvia
spherical polar coordinates.
Chapter 6
Length and area
6.1 Length
Sometimes it is useful to consider coordinates on a manifold that are not or-
thogonal coordinates. The simplest case is that of a two-dimensional manifold.
Write the metric as
g=E du2+ 2F du dv +G dv2. (6.1)
Here E, F, G are functions of u, v. They of course depend on the choice of
coordinates. What is required is that E > 0, G > 0 and the determinant
EF−G2>0. When F= 0 we are in the case of orthogonal coordinates.
One way that such a metric arises is from a surface in three-dimensional
space. Suppose the metric is given in orthogonal coordinates x, y, z byh2
xdx2+
h2
ydy2+h2
zdz2. (If one chooses cartesian coordinates, then hx=hy=hz= 1.)
The length of a curve is
s=Z
Cq
h2xdx2+h2ydy2+h2zdz2. (6.2)
The meaning of this equation is that
s=Zb
as
h2xµdx
dt¶2
+h2yµdy
dt¶2
+h2zµdz
dt¶2
dt, (6.3)
where tis a coordinate on the curve, and the end points are where t=aand
t=b.
Suppose that the curve is in the surface. Then the length is
s=Zb
as
Eµdu
dt¶2
+ 2Fdu
dtdv
dt+Gµdv
dt¶2
dt. (6.4)
Here the coefficients are
E=h2
xµ∂x
∂u¶2
+h2
yµ∂y
∂u¶2
+h2
zµ∂z
∂u¶2
, (6.5)
33
34 CHAPTER 6. LENGTH AND AREA
and
F=h2
x∂x
∂u∂x
∂v+h2
y∂y
∂u∂y
∂v+h2
z∂z
∂u∂z
∂v, (6.6)
and
G=h2
xµ∂x
∂v¶2
+h2
yµ∂y
∂v¶2
+h2
zµ∂z
∂v¶2
. (6.7)
Of course for cartesian coordinates x, y, z we have hx=hy=hz= 1. This
gives the explicit formula for the metric on the surface in terms of the equations
giving x, y, z in terms of u, vthat define the surface. Often one writes the result
for the length of a curve in the surface in the form
s=Z
Cp
E du2+ 2F du dv +G dv2. (6.8)
This just means that one can use any convenient parameter.
6.2 Area
The formula for the area of a surface is
A=Z
Sarea =Z
S√g du∧dv=Z
Sp
EG−F2du∧dv. (6.9)
Here g=EG−F2is the determinant of the metric tensor. This is particularly
simple in the case of orthogonal coordinates, in which case F= 0.
As an example, take the surface given in cartesian coordinates by z=x2+y2
with z≤1. There are various parameterizations. Take, for instance, x=
rcos(φ),y=rsin(φ),z=r2. Then E= 1 + 4 r2,F= 0, and G=r2. So with
these parameters the area form is√g dr∧dφ=r√
1 + 4 r2dr∧dφ. The area is
2πtimes the integral from 0 to 1 of r√
1 + 4 r2dr. The area is thus ( π/6)(53
2−1).
Again, take the surface z=x2+y2with z≤1. This time use x, yas
parameters. Then E= 1 + 4 x2,F= 4xy, and G= 1 + 4 y2. So with these
parameters the area form is√g dx∧dy=p
1 + 4 x2+ 4y2dx∧dy. This is
integrated over the region x2+y2= 1. The answer is of course the same.
There is an alternative expression for the surface area of a surface inside
Euclidean space that is sometimes convenient. This is
A=Z
Sarea =Z
Ss
h2yh2zµdy∧dz
du∧dv¶2
+h2zh2xµdz∧dx
du∧dv¶2
+h2xh2yµdx∧dy
du∧dv¶2
du∧dv.
(6.10)
Again for cartesian coordinates x, y, z we have hx=hy=hz= 1. Here a
fraction such as dy∧dzdivided by du∧dvis a ratio of 2-forms on the surface
S. As we know, such a ratio is just a Jacobian determinant of y, zwith respect
tou, v.
Once again, take the surface given in cartesian coordinates by z=x2+y2
with z≤1. Use x, yas parameters. Then ( dy∧dz)/(dx∧dy) =−2xand
(dz∧dx)/(dx∧dy) =−2yand ( dx∧dy)/(dx∧dy) = 1. So the area form is√g dx∧dy=p
4x2+ 4y2+ 1dx∧dyas before.
6.3. DIVERGENCE AND STOKES THEOREMS 35
6.3 Divergence and Stokes theorems
This section has a discussion of the form that the divergence and Stokes’s the-
orems have in the context of orthogonal coordinates.
The first topic is the divergence theorem in two dimensions. Say that the
vector field vhas an expression in terms of normalized basis vectors of the form
v=a1
hu∂
∂u+b1
hv∂
∂v. (6.11)
Recall that the area form is
area = huhvdu dv. (6.12)
Then the corresponding differential 2-form is
v⌋area = ahvdv−bhudu. (6.13)
The divergence theorem in two dimensions is obtained by applying Greens’s
theorem for 1-forms to this particular 1-form. The result is
Z
R·1
huhvµ∂
∂u(hva) +∂
∂v(hub)¶¸
huhvdu dv =Z
∂Rahvdv−bhudu. (6.14)
The expression in brackets on the left is the divergence of the vector field. On
the right the integrand measures the amount of the vector field crossing normal
to the curve.
The next topic is the divergence theorem in three dimensions. Say that the
vector field vhas an expression in terms of normalized basis vectors of the form
v=a1
hu∂
∂u+b1
hv∂
∂v+c1
hw∂
∂w. (6.15)
Recall that the volume form is
vol = huhvhwdu dv dw. (6.16)
Then the corresponding differential 2-form is
v⌋vol = ahvhwdv dw +bhwhudw du +chuhvdu dv. (6.17)
The divergence theorem in three dimensions is obtained by applying Gauss’s
theorem for 2-forms to this particular 2-form. The result is
Z
V·1
huhvhwµ∂
∂u(hvhwa) +∂
∂v(hwhub) +∂
∂w(huhvc)¶¸
huhvhwdu dv dw =
Z
∂Vahvhwdv dw +bhwhudw du +chuhvdu dv. (6.18)
The expression in brackets is the divergence of the vector field.
36 CHAPTER 6. LENGTH AND AREA
The divergence theorem works the same way in ndimensions. A vector field
gives rise to an n−1 form whose differential is an nform. This nform is a
scalar times the volume form.
The next topic is the classical Stokes’s theorem in three dimensions. Say
that the vector field vhas an expression in terms of normalized basis vectors of
the form
v=a1
hu∂
∂u+b1
hv∂
∂v+c1
hw∂
∂w. (6.19)
Thus the vector field is expressed in terms of normalized basis vectors. Then
there is a corresponding differential 1-form
gv=ahudu+bhvdv+chwdw. (6.20)
The classical Stokes’s theorem in three dimensions is obtained by applying
Stokes’s theorem for 1-forms to this particular 1-form. This gives on the left
hand side
Z
S·1
hvhwµ∂hwc
∂v−∂hvb
∂w¶¸
hvhwdv dw +·1
huhwµ∂hua
∂w−∂hwc
∂u¶¸
hwhudw du +
·1
huhvµ∂hvb
∂u−∂hua
∂v¶¸
huhvdu dv (6.21)
and on the right hand side
Z
∂Sahudu+bhvdv+chwdw. (6.22)
The terms in square brackets are the components of the curl of the vector
field expressed in terms of normalized basis vectors. Notice that the fact that
the curl may be expressed as a vector field depends on three dimensions. In
general a vector field gives rise to a 1-form whose differential is a 2-form. In
two dimensions this 2-form may be identified as a scalar times the area, while
in three dimensions this 2-form may be associated with a vector field.
The situation with the cross product is similar. Two vectors give two 1-
forms, whose exterior product is a 2-form. In two dimensions this gives a scalar,
while in three dimensions it gives a vector.
Bibliography
[1]Ilka Agricola and Thomas Friedrich, Global analysis: Differential forms in
analysis, geometry and physics .
[2]Henri Cartan, Differential forms , Houghton Mifflin, Boston, Massachusetts,
1970.
[3]Manfredo P. do Carmo, Differential forms and applications , Springer-
Verlag, Berlin, 1994.
[4]Dominic G. G. Edelen, Applied exterior calculus , John Wiley & Sons, New
York, 1985.
[5]Harold M. Edwards, Differential forms: A differential forms approach ,
Birkh¨ auser, Boston, 1969.
[6]Luther Pfahler Eisenhart, Riemannian geometry , Princeton University
Press, Princeton, New Jersey, 1949.
[7]Harley Flanders, Differential forms with applications to the physical sci-
ences , Academic Press, New York, 1963.
[8]John Hamal Hubbard and Barbara Burke Hubbard, Vector calculus, linear
algebra, and differential forms: A unified approach , second ed., Prentice-
Hall, Upper Saddle River, New Jersey, 2002.
[9]E. L. Ince, Ordinary differential equations , Dover Publications, New York,
1956.
[10]David Lovelock and Hanno Rund, Tensors, differential forms, and varia-
tional principles , Dover Publications, New York, 1989.
[11]John Milnor, Morse theory , Annals of Mathematics Studies, no. 51, Prince-
ton University Press, Princeton, New Jersey, 1969.
[12]Edward Nelson, Tensor analysis , Princeton University Press, Princeton,
NJ, 1967.
[13] ,Topics in dynamics I: Flows , Princeton University Press, Prince-
ton, NJ, 1969.
37
38 BIBLIOGRAPHY
[14]M. Schreiber, Differential forms: A heuristic introduction .
[15]Michael Spivak, Calculus on manifolds: A modern approach to classical
theorems of advanced calculus , Addison-Wesley, Reading, Massachusetts,
1965.
[16]Gabriel Weinreich, Geometrical vectors , University of Chicago Press,
Chicago, 1998.
[17]Steven H. Weintraub, Differential forms: A complement to vector calculus ,
Academic Press, San Diego, 1997.