advanced calculus ii - math.nthu.edu.tw

95
Advanced calculus II Differentiation and integration Author: Teh, Jyh-Haur Version: 2021 Website: http://www.math.nthu.edu.tw/jyhhaur The great thinkers labor with patience and persistence, meticulously fashioning a quantum view of space-time. Filling in a picture that melds the large and small, a view that conjoins the infinite to the infinitesimal. ——Shing-Tung Yau

Upload: others

Post on 19-Jan-2022

21 views

Category:

Documents


0 download

TRANSCRIPT

Advanced calculus IIDifferentiation and integration

Author: Teh, Jyh-Haur

Version: 2021

Website: http://www.math.nthu.edu.tw/∼jyhhaur

The great thinkers labor with patience and persistence, meticulously fashioning aquantum view of space-time. Filling in a picture that melds the large and small, a

view that conjoins the infinite to the infinitesimal. ——Shing-Tung Yau

Contents of Advanced Calculus I-2

1 Applications of uniform convergence 1

2 Stone-Weierstrass theorem 2

3 Derivatives of functions of several variables 3

4 The inverse and implicit function theorem 4

5 Riemann integrals in higher dimensional spaces 55.1 Riemann integrals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6Exercise 5.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105.2 Riemann-Lebsegue theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Exercise 5.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205.3 Fubini Theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Exercise 5.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285.4 Drawbacks of Riemann integrals . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29Exercise 5.4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

6 Differential forms 336.1 k-chains and differential forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

6.1.1 k-chains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346.1.2 Differential forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Exercise 6.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436.2 Wedge product and the exterior derivative . . . . . . . . . . . . . . . . . . . . . . . 45

6.2.1 Wedge product . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 456.2.2 The exterior derivative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Exercise 6.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 576.3 Pushforward and pullback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58Exercise 6.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 656.4 Stokes’ theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66Exercise 6.4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 726.5 Applications of the Stokes theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

6.5.1 Reduction to some theorems in calculus . . . . . . . . . . . . . . . . . . . . 736.6 De Rham cohomology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82Appendix 6.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

ii

Preface

This book stems from lecture notes for the advanced calculus courses that I taught in NationalTsing Hua University of Taiwan. Main references are

1. Real mathematical analysis by Pugh;2. Elementary classical analysis by Marsden and Hoffman.

Chapter 1 Applications of uniform convergence

Chapter 2 Stone-Weierstrass theorem

Chapter 3 Derivatives of functions of severalvariables

Chapter 4 The inverse and implicit functiontheorems

Chapter 5 Riemann integrals in higher dimensionalspaces

5.1 Riemann integrals

Definition 5.1. Lower sum and upper sumA rectangle R ⊂ Rn is a set of the form

R = [a1, b1]× [a2, b2]× · · · × [an, bn]

for some a1, a2, ..., an, b1, b2, ..., bn ∈ R. A partition P of R is a set of points

P = P1 × P2 × · · · × Pn

wherePi = ai = ti,0 < ti,1 < · · · < ti,ki = bi

is a partition of [ai, bi] where i = 1, 2, ..., n and ki ∈ N. The volume of the rectangle R isdefined to be

vol(R) := (b1 − a1)(b2 − a2) · · · (bn − an)

Let f : R→ R be a function. Define the lower sum of f with respect to the partition P to be

L(f, P ) :=kn∑in=1

· · ·k1∑i1=1

mi1,i2,...,invol(Ri1,i2...,in)

whereRi1,i2,...,in := [t1,i1−1, t1,i1 ]× [t2,i2−1, t2,i2 ]× · · · × [tn,in−1, tn,in ]

andmi1,...,in = inf

x∈Ri1,...,in

f(x)

for 1 ≤ ij ≤ kj, j = 1, ..., n.

6

The upper sum of f with respect to P is

U(f, P ) :=kn∑in=1

· · ·k1∑i1=1

Mi1,i2,...,invol(Ri1,i2,...,in)

whereMi1,...,in = sup

x∈Ri1,...,in

f(x)

for 1 ≤ ij ≤ kj where j = 1, ..., n.

Definition 5.2

♣A refinement of a partition P of a rectangle R is a partition P ′ of R such that P ⊆ P ′.

Proposition 5.1

If R ⊂ Rn is a rectangle and f : R→ R is a bounded function, then

L(f, P ) ≤ L(f, P ′) ≤ U(f, P ′) ≤ U(f, P )

for any partitions P ⊆ P ′ of R.

Definition 5.3. Lower integral and upper integral

Let R ⊂ Rn be a rectangle and f : R→ R be a function. The lower integral of f over R is

I(f) := suppL(f, P )

The upper integral of f over R is

I(f) := infpU(f, P )

If I(f) = I(f), we say that f is Riemann integrable on R and denote∫R

fdV := I(f) = I(f)

7

Definition 5.4

Suppose that A ⊂ Rn is a bounded set and f : A → R is a function. Let R be a rectangle inRn such that A ⊆ R. Define the extension f : R→ R by

f(x) =

f(x) if x ∈ A0 if x ∈ R− A

We say that f is Riemann integrable on A if f is Riemann integrable on R. If f is Riemannintegrable on A, we define ∫

A

fdV :=

∫R

fdV

The proof of the following result is similar to the dimension one case.

Theorem 5.1. Riemann’s integrability criterion

Let R ⊂ Rn be a rectangle and f : R → R be a bounded function. Then f is Riemannintegrable on R if and only if for each ε > 0, there exists a partition P such that

U(f, P )− L(f, P ) < ε

Similar to the proof for the case of dimension one, by using uniformly continuity, we knowthat all continuous functions on R are Riemann integrable. In the following, we give some basicproperties that are similar to the dimension one case.

Proposition 5.2Let A ⊂ Rn, f, g : A→ R be Riemann integrable functions.

1. For a, b ∈ R, af + bg is Riemann integrable on A and∫A

af + bgdV = a

∫A

fdV + b

∫A

gdV

2. |f | is Riemann integrable on A and

|∫A

fdV | ≤∫A

|f |dV

8

3. If A is compact, hn : A → R is Riemann integrable for n ∈ N and hn convergesuniformly to a function h : A→ R, then h is Riemann integrable and

limn→∞

∫A

hndV =

∫A

hdV

9

K Exercise 5.1 k

1. Prove the Riemann’s integrability criterion: Let R ⊂ Rn be a rectangle and f : R → R bea bounded function. Then f is Riemann integrable on R if and only if for each ε > 0, thereexists a partition P such that

U(f, P )− L(f, P ) < ε

2. Let A ⊂ Rn, f, g : A→ R be Riemann integrable functions. Prove the following results:(a). For a, b ∈ R, af + bg is Riemann integrable on A and∫

A

af + bgdV = a

∫A

fdV + b

∫A

gdV

(b). |f | is Riemann integrable on A and

|∫A

fdV | ≤∫A

|f |dV

(c). If A is compact, hn : A → R is Riemann integrable for n ∈ N and hn convergesuniformly to a function h : A→ R, then h is Riemann integrable and

limn→∞

∫A

hndV =

∫A

hdV

3. Let f : [0, 1]× [2, 3]→ R be defined by

f(x, y) =

x, if 0 ≤ x ≤ y ≤ 1

y, otherwiseUse the definition of Riemann integral to find∫

[0,1]×[2,3]

fdV

10

5.2 Riemann-Lebsegue theorem

Definition 5.5. Null set

A set A ⊂ Rn is said to have measure zero if for every ε > 0, there exists countable number ofrectangles R1, R2, ... in Rn such that

A ⊂∞⋃i=1

Ri

and∞∑i=1

vol(Ri) < ε

Example 5.11. The sets

Z ⊂ R,Z2 ⊂ R2, S1 ⊂ R2

have measure zero.2. R× 0 is a measure zero subset of R2, but R is not a measure zero subset of R1.3. A countable set has measure zero.4. A countable union of sets of measure zero is a set of measure zero.5. Let R ⊂ Rn be a rectangle. Then its boundary ∂R in Rn has measure zero.6. Let R ⊂ Rn be a rectangle. We call the interior

R an open rectangle. It is clear that a set has

measure zero if it can be covered by countably many open rectangles with total volume smallerthan an arbitrarily given positive number.

Recall that the diameter of a set A is

diam(A) := supx,y∈A||x− y||

11

Definition 5.6. Oscillation

Let R ⊂ Rn be a rectangle and f : R→ R be a bounded function. The oscillation of f at x is

oscx(f) := limr→0+

diamf(Br(x) ∩R)

Remark(i) f is continuous at x if and only if oscx(f) = 0.(ii) If x ∈ R, M = supx∈Rf(x), m = infx∈Rf(x), then

M −m ≥ oscx(f)

Definition 5.7. Set of discontinuities

Let R ⊂ Rn be a rectangle and f : R→ R be a function. The set

Disc(f) := x ∈ R|f is discontinuous at x

is called the set of discontinuities of f .

The following result gives a complete characterization of Riemann integrable functions.

Theorem 5.2. Riemann-Lebesgue theorem

Let R ⊂ Rn be a rectangle. Then f is Riemann integrable if and only if f : R → R is abounded function and the set Disc(f) has measure zero.

Proof LetDk = x ∈ R|oscx(f) ≥

1

k

Then

Disc(f) =∞⋃k=1

Dk

Suppose that f is Riemann integrable. By Proposition, f is bounded. Fix k ∈ N. We are going toshow that Dk has measure zero. Given ε > 0. By the Riemann integrability criterion, there exists a

12

partitionP = (t1,i1 , t2,i2 , ..., tn,in)|0 ≤ ij ≤ kj for j = 1, 2, ..., n

of R such that

U(f, P )− L(f, P ) =kn∑in=1

· · ·k1∑i1=1

(Mi1,..,in −m(i1,...,in))vol(Ri1,...,in) <ε

k

whereRi1,...,in = [t1,i1−1, t1,i1 ]× [t2,i2−1, t2,i2 ]× · · · × [tn,in−1, tn,in ]

Mi1,....,in = supx∈Ri1,...,in

f(x), mi1,...,in = infx∈Ri1,...,in

f(x)

LetA := (i1, ..., in) ∈ P |Ri1,...,in ∩Dk = ∅

If (i1, ..., in) ∈ A , thenMi1,...,in −mi1,...,in ≥

1

k

SinceDk ⊂

⋃(i1,...,in)∈A

Ri1,...,in

we have ∑(i1,...,in)∈A

1

kvol(Ri1,...,in) ≤

∑(i1,...,in)∈A

(Mi1,..,in −mi1,...,in)vol(Ri1,...,in) <ε

k

Therefore ∑(i1,...,in)∈A

vol(Ri1,...,in) < ε

This implies that Dk has measure zero, so is

Disc(f) =∞⋃k=1

Dk

13

Conversely, suppose that f is bounded by M > 0 and Disc(f) has measure zero. Given ε > 0.Take k ∈ N such that

1

k<

ε

2vol(R)

Since Disc(f) has measure zero, Dk is a set of measure zero. Therefore, there exist open rectanglesR1,

R2, ....

such that

Dk ⊂∞⋃i=1

Ri

and∞∑i=1

vol(Ri) <

ε

4M

For x ∈ R \Dk,oscx(f) <

1

k

thus there exists rx > 0 such that

diamf(Brx(x) ∩R) <1

k

LetB =

Ri|i ∈ N ∪ Brx(x)|x ∈ R \Dk

Then B is an open cover of R. Since R is compact, B has a Lebesgue number λ > 0. Let

P = (t1,i1 , t2,i2 , ..., tn,in)|0 ≤ ij ≤ kj for j = 1, 2, ..., n

be a partition of R withvol(Ri1,...,in) < λ

We show thatU(f, P )− L(f, P ) < ε

14

By the definition of Lebesgue number,Ri1,...,in ⊂

Rj or Brx(x)

for some j ∈ N or x ∈ R \Dk. Let

Γ := (i1, ..., in)|Ri1,...,in ⊂

Rj for some j ∈ N

Then

U(f, P )− L(f, P ) =∑

(i1,...,in)∈P

(Mi1,..,in −m(i1,...,in))vol(Ri1,...,in)

=∑

(i1,...,in)∈Γ

(Mi1,..,in −m(i1,...,in))vol(Ri1,...,in) +∑

(i1,...,in)/∈Γ

(Mi1,..,in −m(i1,...,in))vol(Ri1,...,in)

≤∑

(i1,...,in)∈Γ

2Mvol(Ri1,...,in) +∑

(i1,...,in)/∈Γ

1

kvol(Ri1,...,in)

≤ 2M(ε

4M) +

ε

2vol(R)vol(R) = ε

Definition 5.8. Piecewise continuous function

A function f : [a, b] → R is piecewise continuous if it is continuous except at a finite numberof points.

Example 5.2 The function

f(x) =

1, if x ≤ 0

2, if x ∈ [0, 1]

ex, if x ≥ 1

is piecewise continuous.

Corollary 5.1

Every piecewise continuous bounded function f : [a, b]→ R is Riemann integrable.

15

Corollary 5.2

Every monotone function f : [a, b]→ R is Riemann integrable.

Proof We first show that Disc(f) is countable. We may assume that f is monotone increasingsince similar proof works for monotone decreasing functions. For p ∈ Disc(f), since f is monotoneincreasing

limx→p−

f(x) < limx→p+

f(x)

and for p, q ∈ Disc(f), p = q,

( limx→p−

f(x), limx→p+

f(x)) ∩ ( limx→q−

f(x), limx→q+

f(x)) = ∅

This establishes a one-to-one correspondence

Disc(f)←→ ( limx→p−

f(x), limx→p+

f(x))|p ∈ Disc(f)

Note that for each p ∈ Disc(f), the open interval (limx→p− f(x), limx→p+ f(x)) contains a rationalnumber, thus the collection (limx→p− f(x), limx→p+ f(x))|p ∈ Disc(f) and hence the setDisc(f)is countable. By Proposition, a countable set is a null set, hence Disc(f) is a null set. By theRiemann-Lebesgue Theorem, f is Riemann integrable.

Corollary 5.3

Let R ⊂ Rn be a rectangle. If f, g : R → R are Riemann integrable, then the productf · g : R→ R is Riemann integrable.

Proof Since f, g are Riemann integrable, f, g are bounded. If f is bounded byM1 and g is boundedby M2 where M1,M2 > 0, then

|f(x)g(x)| ≤M1M2

for x ∈ R. Therefore f · g is bounded. Since

Disc(f · g) ⊆ Disc(f) ∪Disc(g)

16

and Disc(f)∪Disc(g) has measure zero, Disc(f · g) has measure zero. By the Riemann-LebesgueTheorem, f · g is Riemann integrable.

Corollary 5.4

Let R ⊂ Rn be a rectangle. If f : R → [a, b] is Riemann integrable, ψ : [a, b] → R iscontinuous, then ψ f is Riemann integrable.

Proof Since ψ is bounded, ψ f is bounded. Note that if f is continuous at x0, then ψ f iscontinuous at x0. Therefore

Disc(ψ f) ⊂ Disc(f)

By the Riemann-Lebesgue theorem, Disc(f) has measure zero, so isDisc(ψ f). By the Riemann-Lebesgue theorem again, ψ f is Riemann integrable.

Corollary 5.5

Let R1, R2 ⊂ Rn be rectangles such that

R1 ∩R2 ⊂ ∂R1 ∪ ∂R2

If f : R1 ∪R2 → R is Riemann integrable, then f |R1 and f |R2 are Riemann integrable and∫R1∪R2

fdV =

∫R1

f |R1dV +

∫R2

f |R2dV

Proof Since f is bounded, f |R1 and f |R2 are bounded. By the Riemann-Lebesgue theorem,Disc(f)has measure zero. Since

Disc(f |R1) ∪Disc(f |R2) = Disc(f)

so both of them have measure zero. By the Riemann-Lebesgue theorem again, f |R1 and f |R2 areRiemann integrable. Note that

f = χR1 · f + χR2 · f − χR1∩R2 · f

17

Since R1 ∩R2 has measure zero, ∫R1∩R2

fdV = 0

we have ∫R1∪R2

fdV =

∫R1∪R2

χR1fdV +

∫R1∪R2

χR2fdV −∫R1∪R2

χR1∩R2fdV

=

∫R1

fdV +

∫R2

fdV −∫R1∩R2

fdV

=

∫R1

fdV +

∫R2

fdV

Definition 5.9. Almost everywhere

If a function f has property P except on a set of measure zero, we say that f has property Palmost everywhere.

Corollary 5.6

Let R ⊂ Rn be a rectangle. Suppose that f : R→ R is Riemann integrable and f(x) ≥ 0 foralmost every x ∈ R. If ∫

R

fdV = 0

then f(x) = 0 at every continuous point x of f . In particular, f(x) = 0 almost everywhere.

Proof Suppose that f(x) ≥ 0 for all x ∈ R − Z where Z is a set of measure zero. Assume thatthere exists x0 ∈ int(R) ∩ (R − Z) such that f is continuous at x0 but f(x0) > 0. Then there existsδ > 0 such that if ||x− x0|| < δ, x ∈ R and

|f(x)− f(x0)| <f(x0)

2

Then−f(x0)

2< f(x)− f(x0) <

f(x0)

2

18

Sof(x0)

2< f(x) < 3

f(x0)

2

Let x0 = (x0,1, ..., x0,n) and

S := x = (x1, ..., xn) ∈ Rn||xi − x0,i| <1

2nδ for i = 1, ..., n

Note that for x ∈ S,

||x− x0|| ≤

√√√√ n∑i=1

(1

2nδ)2 =

√n(

1

2nδ)2 =

1

2√nδ < δ

Let

g(x) =

12f(x0), if x ∈ S

0, otherwise

Then0 ≤ g(x) ≤ f(x)

for all x ∈ S. Thus

vol(S)(1

2)f(x0) =

∫S

gdV ≤∫S

fdV ≤∫R

fdV = 0

This implies f(x0) ≤ 0 which is a contradiction. Therefore for x ∈ int(R) ∩ (R − Z) ∩ Cont(f),f(x) = 0 where

Cont(f) := x ∈ R|f is continuous at x = R−Disc(f)

This implies thatx ∈ R|f(x) = 0 ⊂ (∂R ∪ Z ∪Disc(f))

where ∂R is the boundary of R. Since (∂R ∪ Z ∪ Disc(f)) has measure zero, by the definition,f = 0 almost everywhere.

19

K Exercise 5.2 k

1. Let R ⊂ Rn be a rectangle. Show that the boundary ∂R of R has measure zero.2. Show that [0, 1]× 0 has measure zero in R2 but [0, 1] in R is not a set of measure zero.3. Show that if A,B ⊂ Rn have measure zero, then A ∪B has measure zero.4. Show that the union of countably many sets of measure zero is a set of measure zero.5. Let R ⊂ Rn be a rectangle and f : R→ R be a bounded function. For ε > 0, let

Aε := x ∈ R|oscx(f) ≥ ε

Show that Aε is a compact set.6. Let R ⊂ Rn be a rectangle and f, g : R→ R be Riemann integrable functions.

(a). Show that if f = 0 almost everywhere, then∫R

fdV = 0

(b). Show that if f = g almost everywhere, then∫R

fdV =

∫R

gdV

20

5.3 Fubini Theorem

Theorem 5.3. Fubini theorem

Let R ⊂ Rn, S ⊂ Rm be rectangles and F : R × S → R be a Riemann integrable function.Define f : S → R by

f(y) :=

∫R

F (x, y)dVn

and g : R→ R byg(x) :=

∫S

F (x, y)dVm

1. If f : S → R is a Riemann integrable function, then∫R×S

F (x, y)dV =

∫S

f(y)dVm =

∫S

∫R

F (x, y)dVndVm

2. If g : R→ R is a Riemann integrable function, then∫R×S

F (x, y)dV =

∫R

g(x)dVn =

∫R

∫S

F (x, y)dVmdVn

Proof Let P = P1 × · · · × Pn be a partition of

R = [a1, b1]× · · · × [an, bn]

wherePi = ai = ti,0 < ti,1 < · · · < ti,ki = bi

andQ = Q1 × · · · ×Qm

be a partition ofS = [c1, d1]× · · · × [cm, dm]

21

whereQj = cj = sj,0 < sj,1 < · · · < sj,ℓj = dj

DenoteA = (u1, ..., un)|0 ≤ ui < ki, i = 1, 2, ..., n

andB = (v1, ..., vm)|0 ≤ vj < `j, j = 1, 2, ...,m

For I = (u1, ..., un) ∈ A , J = (v1, ..., vm) ∈ B, let RIbe the subrectangle

RI := [t1,u1 , t1,u1+1]× · · · × [tn,un , tn,un+1]

and SJbe the subrectangle

SJ := [s1,v1 , s1,v1+1]× · · · × [sm,vm , sm,vm+1]

Furthermore, denotemIJ := inf

RI×SJ

F (x, y), MIJ := supRI×SJ

F (x, y)

Then for all (x, y) ∈ RI × SJ ,mIJ ≤ F (x, y) ≤MIJ

andmIJvol(RI) ≤

∫RI

F (x, y)dVn ≤MIJvol(RI)

For each y ∈ S, ∑I∈A

mIJvol(RI) ≤∫R

F (x, y)dVn = f(y) ≤∑I∈A

MIJvol(RI)

Then for J ∈ B,∑I∈A

mIJvol(RI)vol(SJ) ≤∫S

∫R

F (x, y)dVndVm ≤∑I∈A

MIJvol(RI)vol(SJ)

22

and hence sum over all I ∈ A , J ∈ B, we have

L(F, P ×Q) =∑I,J

mIJvol(RI)vol(SJ)

≤∫S

∫R

F (x, y)dVndVm

≤∑I,J

MIJvol(RI)vol(SJ)

= U(F, P ×Q)

Then

I(F ) = supP×S

L(F, P × S) ≤∫S

∫R

FdVndVm ≤ infP×S

U(F, P × S) = I(F )

Since F is Riemann integrable, we have∫R×S

FdV = I(F ) = I(F ) =

∫S

∫R

FdVndVm

Example 5.3 LetA := (x, y) ∈ R2 : 0 ≤ y ≤ 1, y ≤ x ≤ 1

Suppose that f : A→ R is defined by

f(x, y) := cos(1

2πx2)

Find∫AfdV .

Solution Let

f =

cos(1

2πx2), if (x, y) ∈ A

0, otherwise

23

By the Fubini theorem, we have ∫A

fdV =

∫[0,1]×[0,1]

fdV

=

∫ 1

0

∫ 1

0

f(x, y)dxdy

=

∫ 1

0

∫ 1

y

cos(1

2πx2)dxdy

but we do not know how to integrate this function with respect to x. Instead, we write

A = (x, y) ∈ R2|0 ≤ x ≤ 1, 0 ≤ y ≤ x

Then ∫A

dV =

∫ 1

0

∫ x

0

cos(1

2πx2)dydx

=

∫ 1

0

x cos(1

2πx2)dx =

1

πsin(

1

2πx2)|10

=1

π

Proposition 5.3

Let R ⊂ Rn, S ⊂ Rm be rectangles and h : R × S → R be a continuous function. Definef : R→ R and g : S → R by

f(x) :=

∫S

h(x, y)dVm

andg(y) :=

∫R

h(x, y)dVn

Then f and g are uniformly continuous on R and S respectively.

Proof We prove the result for f . The proof for g is similar. Since R × S is compact and h iscontinuous, h is uniformly continuous on R × S. Thus for ε > 0, there exists δ > 0 such that if

24

||(x1, y1)− (x2, y2)|| < δ,|h(x1, y1)− h(x2, y2)| <

1

vol(S)ε

For |x1 − x2| < δ,

|f(x1)−f(x2)| = |∫S

h(x1, y)−h(x2, y)dVm| ≤∫S

|h(x1, y)−h(x2, y)|dVm <1

vol(S)εvol(S) = ε

This shows that f is uniformly continuous on R.

Theorem 5.4

Suppose that f : [a, b]× [c, d]→ R is a function such that ∂f∂x

can be extended to a continuousfunction on [a, b]× [c, d]. For x ∈ [a, b], define

F (x) :=

∫ d

c

f(x, y)dy

Then dFdx

is continuous on [a, b] and

d

dx

∫ d

c

f(p, y)dy =

∫ d

c

∂f

∂x(p, y)dy

for p ∈ [a, b].

Proof For x ∈ [a, b], define

G(x) :=

∫ d

c

∂f

∂x(x, y)dy

and for y ∈ [c, d], define

H(y) :=

∫ b

a

∂f

∂x(x, y)dx

By Proposition 5.3, G and H are continuous functions. By the Fubini theorem and the Funda-

25

mental Theorem of Calculus, we have∫ x

a

G(t)dt =

∫ x

a

∫ d

c

∂f

∂x(x, y)dydx =

∫ d

c

∫ x

a

∂f

∂x(x, y)dxdy

=

∫ d

c

f(x, y)− f(a, y)dy

= F (x)− F (a)

ThusF ′(x) = G(x)

for all x ∈ (a, b). This proves our claim.Example 5.4 Evaluate ∫

R

sin(xy)

ydV

where R = [0, 1]× [0, 1].Solution Let

f(x, y) :=

sin(xy)y

, if (x, y) ∈ R, y = 0

1, if (x, y) ∈ R, y = 0

Note thatlimy→0

sin(xy)

y= x

ThereforeDisc(f) = [0, 1)× 0

which has measure zero in R2. By the Riemann-Lebesgue theorem, f is Riemann integrable. Notethat

∂f

∂x= cos(xy)

is continuous on R. LetF (x) :=

∫ 1

0

f(x, y)dy =

∫ 1

0

sin(xy)

ydy

26

By Theorem 5.4,

F ′(x) =

∫ 1

0

cos(xy)dy =sin(xy)

x|10 =

sin x

x

By the Fubini theorem and integration by parts,∫R

sin(xy)

ydV =

∫ 1

0

(

∫ 1

0

sin(xy)

ydy)dx

= x(

∫ 1

0

sin(xy)

ydy)|10 −

∫ 1

0

x(sin x

x)dx

=

∫ 1

0

sin y

ydy −

∫ 1

0

sin xdx

=

∫ 1

0

∞∑k=0

(−1)k y2k

(2k + 1)!dy + cos 1− 1

=∞∑k=0

(−1)k

(2k + 1)(2k + 1)!+ cos 1− 1

Note that by the Weierstrass M-test, the series∞∑k=0

(−1)k y2k

(2k + 1)!

converges uniformly on [0, 1], hence we may interchange the sum and the integral.

27

K Exercise 5.3 k

1. Let R = [a, b]× [c, d] ⊂ R2 and f : R→ R be a continuous function. Define F : R→ R by

F (x, y) :=

∫ x

a

∫ y

c

f(u, v)dvdu

Show that∂2F

∂y∂x=

∂2F

∂x∂y= f(x, y)

2. Let R ⊂ Rn, S ⊂ Rm be rectangles and f : R× S → R be a bounded function. Suppose thatf is Riemann integrable on R× S. For x ∈ R, define

F (x) :=

∫S

f(x, y)dVm

Show that F (x) exists for almost all x ∈ R.

28

5.4 Drawbacks of Riemann integrals

Definition 5.10. Rational ruler function

The rational ruler function is the function f : [0, 1]→ R defined by

f(x) :=

1q, if x = p

q∈ (0, 1], p, q ∈ N, p, q are relatively prime

1, if x = 0

0, if x ∈ [0, 1] ∩Qc

Proposition 5.4

♠The rational ruler function f is Riemann integrable.

Proof We prove thatDisc(f) = [0, 1] ∩Q

For r ∈ Q ∩ [0, 1], since [0, 1] ∩ Qc is dense in [0, 1], there exists an∞n=1 ⊂ [0, 1] ∩ Qc such thatan → r. But

limn→∞

f(an) = 0 = f(r)

Thus f is not continuous at r. This shows that [0, 1] ∩Q ⊂ Disc(f).In the following, we show that f is continuous on [0, 1] ∩ Qc. Let x0 ∈ [0, 1] ∩ Qc and ε > 0.

Take N ∈ N such that1

N< minε, x0

Letδ = min| i

j− x0||i, j = 1, 2, · · ·, N

Suppose that x ∈ [0, 1] and |x− x0| < δ. Note that

|0− x0| = x0 >1

N≥ δ

29

therefore x = 0.Case 1: If x ∈ [0, 1] ∩Qc, then

|f(x)− f(x0)| = 0 < ε

Case 2: If x ∈ (0, 1] ∩Q, then x = pq

for some p, q ∈ N. Note that since

|x− x0| < δ

we must have q > N . Therefore,

|f(x)− f(x0)| = f(x) =1

q<

1

N< ε

So f is continuous at x0. Hence

Disc(f) = Q ∩ [0, 1]

which has measure zero. By the Riemann-Lebesgue theorem, f is Riemann integrable.Remark If f, g : [0, 1]→ R are Riemann integrable, g f may NOT be Riemann integrable.Example 5.5 Let f be the rational ruler function. Let

g(x) :=

0, if x = 0

1, if x ∈ (0, 1]

Then

g f(x) =

0, if x ∈ Qc ∩ [0, 1]

1, if x ∈ Q ∩ [0, 1]

Thusg f = χQ∩[0,1]

which is not Riemann integrable.

30

K Exercise 5.4 k

1. Let

f(x) :=

x2 cos π

x2, if 0 < x ≤ 1;

0, if x = 0.

Show that f is continuous on [0, 1], differentiable on (0, 1), but its derivative f ′ is not Riemannintegrable on [0, 1]. In particular,∫ 1

0

f ′(x)dx = f(1)− f(0)

2. LetR[0, 1] := f |f : [0, 1]→ R is Riemann integrable/ ∼

where f ∼ g if and only if f = g almost everywhere on [0, 1]. For [f ], [g] ∈ R[0, 1], define

d([f ], [g]) :=

∫ 1

0

|f(x)− g(x)|dx

(a). Show that d is a metric onR[0, 1].(b). Show thatR[0, 1] under d is not a complete metric space.

31

32

Chapter 6 Differential forms

6.1 k-chains and differential forms

6.1.1 k-chains

Definition 6.1

We say that φ : [0, 1]k → V is smooth if there exists an open setW in Rk such that [0, 1]k ⊂ W

and a smooth function φ : W → V such that

φ|[0,1]k = φ

Definition 6.2. k-cell

Let V be an open subset of Rn. A k-cell in V is a smooth map

φ : [0, 1]k → V

A finite formal linear combinationl∑

i=1

aiϕi

where ai ∈ R, and all ϕi : [0, 1]k → V are k-cells in V is called a k-chain in V . Denote byCk(V ) the collection of all k-chains in V .

Remark In general, a k-chain∑l

i=1 aiϕi is NOT a function. It is a ‘formal’ linear combination ofk-cells. For example, if ϕ1, ϕ2 : [0, 1]→ B2(0) ⊂ R2 are defined by

ϕ1(t) = (1, t), ϕ2(t) = (t2, t3)

Then 3ϕ1 + 5ϕ2 ∈ C1(B2(0)) but the function

ψ(t) = 3(1, t) + 5(t2, t3) = (3 + 5t2, 3t+ 5t3)

is not even an 1-cell in B2(0) since its image is not contained in B2(0). So 3ϕ1 + 5ϕ2 and ψ are twovery different objects.

34

6.1.2 Differential forms

Definition 6.3

We say thatI = (i1, i2, ..., ik)

is a k-tuple in 1, 2, ...,m if i1, i2, ..., ik ∈ 1, 2, ...,m, and I is in ascending order if

i1 < i2 < · · · < ik

Definition 6.4

Let I = (i1, i2, ..., ik) be a k-tuple in 1, 2, ...,m and J = (j1, j2, ..., jk) be a k-tuple in1, 2, ..., n. Suppose that V is an open subset of Rn and F : V → Rm is a smooth map.Define

∂FI∂XJ

:=

∂Fi1

∂Xj1· · · ∂Fi1

∂Xjk... . . . ...∂Fik

∂Xj1· · · ∂Fik

∂Xjk

k×k

Example 6.1 Let F : R3 → R2 be defined by

F (x, y, z) = (x2y + xz, yz2)

1. If I = (1, 2), J = (1, 3), then

∂FI∂XJ

=

(2xy + z x

0 2yz

)2. If I = (1), J = (2),

∂FI∂XJ

=(x2)

Let us give a geometric interpretation of the determinant of a matrix.Remark Let X = (u1, u2),Y = (v1, v2) ∈ R2. Suppose that X,Y are not collinear. Let P be the

35

parallelogram determined by X and Y. We know that

area of P = ||X||||Y|| sin θ

where θ is the angle between X and Y determined by the formula

cos θ =X · Y||X||||Y||

Note that

sin θ =√1− cos2 θ =

√1− (

X · Y||X||||Y||

)2 =1

||X||||Y||√(||X||||Y||)2 − (X · Y)2

The area of P is

||X||||Y|| sin θ =√(u21 + u22)(v

21 + v22)− (u1v1 + u2v2)2

=√u21v

22 + u22v

21 − 2u1v1u2v2

=√

(u1v2 − u2v1)2

= | det

(u1 u2

v1 v2

)|

If there exists a linear transformation LA : R2 → R2 where A ∈ GL(2,R) with det(A) > 0 suchthat

LA(X) = e1, LA(Y) = e2

where e1, e2 is the standard ordered basis of R2, then

det

(u1 u2

v1 v2

)is positive. In this case, we say that the ordered basis X,Y and e1, e2 have the same orientation.

Let us look at integration from another viewpoint.Example 6.2

1. Let ϕ : [a, b]→ [a, b] be the identity function

ϕ(x) := x

36

and f : [a, b] → R be a smooth function. We consider fdx as a tool that can measure howlong is the length of ϕ. Write

(fdx)(ϕ) :=

∫[a,b]

f(ϕ(x))dϕ

dxdx =

∫ b

a

f(x)dx

2. Let ψ : [a, b]× [c, d]→ [a, b]× [c, d] be the identity map

ψ(x1, x2) := (x1, x2) = (ψ1(x1, x2), ψ2(x1, x2))

For any smooth function g : [a, b]× [c, d]→ R, we consider gdxdy as a tool that can measurehow large is the area of ψ. Write

(gdxdy)(ψ) =

∫[a,b]×[c,d]

g(ψ(x1, x2)) det∂ψ1,2

∂x1,2dV

=

∫[a,b]×[c,d]

g(x1, x2) det

(1 0

0 1

)dV

=

∫[a,b]×[c,d]

gdV

Definition 6.5

Let V ⊂ Rn be an open set and k ∈ N. A simple k-form on V is a linear functionfdXI : Ck(V )→ R defined by

(fdXI)(φ) :=

∫[0,1]k

f(φ(u)) det∂φI

∂u1,...,kdV

=

∫ 1

0

· · ·∫ 1

0

f(φ(u)) det(∂φI

∂u1,...,k)du1...duk

where I is a k-tuple in 1, ..., n, f : V → R is a smooth function and φ is a k-cell in V . IfI = (i1, i2, ..., ik), we also write

dXI = dxi1dxi2 · · · dxik

Example 6.3 Let φ : [0, 1]2 → R3 be defined by

φ(u1, u2) = (2u1 + 3u2, u1, u2)

37

Then φ is 2-cell for R3. Let I = (1, 2). Then

∂φI∂u1,2

=

(2 3

1 0

)and

(dXI)(φ) =

∫[0,1]2

det∂φI∂u1,2

dV =

∫ 1

0

∫ 1

0

(−3)du1du2 = −3

Proposition 6.1

Let I = (i1, i2, ..., ik) where k ∈ N. If π : 1, 2, ..., k → 1, 2, ..., k is a permutation and

πI = (iπ(1), iπ(2), ..., iπ(k))

thendXπI = sgn(π)dXI

Proof Let φ be a k-cell. Then

(dXπI)(φ) =

∫[0,1]k

det∂φπI∂u1,...,,k

dV =

∫[0,1]k

sgn(π) det∂φI

∂u1,...,kdV = sgn(π)(dXI)(φ)

HencedXπI = sgn(π)dXI

Example 6.4 On R4, we have1.

dxdy = −dydx

2.dxdydzdw = −dxdwdzdy

in which we may consider I = (1, 2, 3, 4) and πI = (1, 4, 3, 2).

38

Example 6.5 Let φ : [0, 1]5 → R6 be defined by

φ(u1, u2, u3, u4, u5) = (2u1, 3u2, 4u3, 5u4 + 6u5, u1 + u2, u1 + u3)

Let I = (1, 2, 3, 4, 5) and

π =

(1 2 3 4 5

4 3 1 5 2

)=(

1 4 5 2 3)= (13)(12)(15)(14)

Then πI = (4, 3, 1, 5, 2), sgn(π) = 1, and

φπI(u1, u2, u3, u4, u5) = (5u4 + 6u5, 4u3, 2u1, u1 + u2, 3u2, u1 + u3)

∂φπI∂u1,..,5

=

0 0 0 5 6

0 0 4 0 0

2 0 0 0 0

1 1 0 0 0

0 3 0 0 0

and

∂φI∂u1,..,5

=

2 0 0 0 0

0 3 0 0 0

0 0 4 0 0

0 0 0 5 6

1 1 0 0 0

Therefore ∂ϕπI

∂u1,...,5is obtained from ∂ϕI

∂u1,...,5by exchanging rows 4 times. Hence

det∂φπI∂u1,...,5

= det∂φI

∂u1,...,5

39

Corollary 6.1

If I = (i1, ..., ik) and ij1 = ij2 for some j1 = j2, then

dXI = 0

Proof Let π be the k-permutation that interchanges j1 and j2 only. Since sgn(π) = −1,

dXπI = −dXI

From ij1 = ij2 , we havedXπI = dXI

This implies dXI = −dXI and 2dXI = 0 which gives us

dXI = 0

Example 6.6 In any open set V ⊂ Rn, we always have1.

dxdx = 0

2.dxdydzdy = 0

Definition 6.6

Let V be an open subset of Rn. A 0-form on V is a smooth function f : V → R. For k ∈ N, ak-form on V is a finite sum of simple k-forms on V . More explicitly, a k-form on V is a linearfunction

∑I

fIdXI : Ck(V )→ R defined by

(∑I

fIdXI)(ϕ) :=∑I

(fIdXI)(ϕ)

where ϕ is a k-chain on V and the sum is a finite sum. We denote by Ωk(V ) the set of allk-forms on V .

40

Example 6.71. For f, g : R2 → R smooth functions,

f(x, y)dx+ g(x, y)dy

is an 1-form on R2.2. For h : R2 → R,

h(x, y)dxdy

is a 2-form on R2.Remark Note that I0 := 1. If φ : I0 → V is a 0-cell and f : V → R is a 0-form, then

(f)(φ) := f(φ(1))

If∑m

i=1 aiφi is a 0-chain in V , then

(f)(m∑i=1

aiφi) =m∑i=1

aif(φi(1))

Corollary 6.2

If V is open in Rn and k > n, thenΩk(V ) = 0

Proof Let I = (i1, i2, ..., ik) be a k-tuple in 1, 2, ..., n. Since k > n, ij1 = ij2 for some j1 = j2.Then by Corollary 6.1, dXI = 0. Hence

Ωk(V ) = 0

Example 6.8Ω4(R3) = 0

41

Remark LetI +k = I|I is an ascending k-tuple in 1, 2, ..., n

Note thatdXI |I ∈ I +

k

is a basis forΩk(V ) over C ∞(V ). In the language of algebra, Ωk(V ) is the C ∞(V )-module generatedby

dXI |I ∈ I +k

42

K Exercise 6.1 k

1. For i = 1, 2, 3, let ϕi : [0, 1]2 → R be defined by

ϕi(x1, x2) := 3x1 + 4ix2 + i

and ϕ, ψ : [0, 1]2 → R3 be the smooth functions defined by

ϕ(x1, x2) := (ϕ1(x1, x2), ϕ2(x1, x2), ϕ3(x1, x2))

ψ(x1, x2) := (2, ϕ1(x1, x2) + ϕ2(x1, x2), ϕ3(x1, x2) + x21)

Finddx1dx3(2ϕ+ 3ψ)

where 2ϕ+ 3ψ is a 2-chain, not a function.2. Let ϕ : In → Rn be defined by

ϕ(u1, ..., un) = (u1, ..., un)

and ω = dx1dx2 · · · dxn. Find ω(ϕ).3. (a). Suppose that

Xi :=3∑j=1

aijej

where i = 1, 2, 3 are 3 linearly independent vectors in R3. Let

P := aX1 + bX2 + cX3|0 ≤ a, b, c ≤ 1

be the parallelogram spanned by X1,X2,X3. Find the volume

V ol(P ) :=

∫P

χPdV

of P .(b). Let ϕ : [0, 1]3 → R3 be defined by

ϕ(u1, u2, u3) := u1X1 + u2X2 + u3X3

43

Finddx1dx2dx3(ϕ)

(c). Generalize above results to vectors in Rn.

44

6.2 Wedge product and the exterior derivative

6.2.1 Wedge product

Definition 6.7. Wedge product

Suppose that V ⊂ Rn is an open subset. Let

α =∑I

aIdXI

be a k-form andβ =

∑J

bJdXJ

be an `-form on V , their wedge product is the (k + l)-form

α ∧ β =∑I,J

aIbJdXIJ

where I = (i1, i2, ..., ik), J = (j1, j2, ..., jl), IJ = (i1, i2, ..., ik, j1, j2, ..., jl).

Example 6.9 Letα = fdx+ gdy ∈ Ω1(R3)

β = pdxdz + qdydz = −pdzdx− qdzdy ∈ Ω2(R3)

Then

(fdx+ gdy) ∧ (pdxdz + qdydz) = fpdxdxdz + fqdxdydz + gpdydxdz + gqdydydz

= (fq − gp)dxdydz

and

(fdx+ gdy) ∧ (−pdzdx− qdzdy) = −fpdxdzdx− fqdxdzdy − gpdydzdx− gqdydzdy

= (fq − gp)dxdydz

45

Definition 6.8

A k-permutation π : 1, ..., k → 1, ..., k and an `-permutation σ : 1, ..., ` → 1, ..., `induce a (k + `)-permutation

(π, σ) =

(1 · · · k k + 1 · · · k + `

π(1) · · · π(k) k + σ(1) · · · k + σ(`)

)

Remarksgn(π, σ) = sgn(π)sgn(σ)

Lemma 6.1

Suppose that I is a k-tuple, J is an `-tuple in 1, ..., n, and π, σ are k-permutation and`-permutation respectively. If I ′ = π(I), J ′ = σ(J), then

dXI′J ′ = sgn(π)sgn(σ)dXIJ

Proof Let I = (i1, ..., ik) and J = (j1, ..., jℓ). Write

J = (ik+1, ..., ik+ℓ)

Then

(π, σ)(IJ) = (iπ(1), ..., iπ(k), ik+σ(1), ..., ik+σ(ℓ))

= (iπ(1), ..., iπ(k), jσ(1), ..., jσ(ℓ))

= π(I)σ(J)

We have

dXI′J ′ = dXπ(I)σ(J) = dX(π,σ)(IJ) = sgn(π, σ)dXIJ = sgn(π)sgn(σ)dXIJ

Proposition 6.2

♠The wedge product is well-defined.

46

Proof Let V ⊂ Rn be an open subset. Suppose that

α =∑I

fIdXI =∑I′

f ′I′dXI′ ∈ Ωk(V )

β =∑J

gJdXJ =∑J ′

g′J ′dXJ ′ ∈ Ωℓ(V )

where all I ′, J ′ are in ascending order. We need to show that∑I,J

fIgJdXIJ =∑I′,J ′

f ′I′g

′J ′dXI′J ′

LetΓ(I ′) := I|π(I) = I ′ for some k-permutation π

Γ(J ′) := J |σ(J) = J ′ for some `-permuation σ

andπ(I, I ′) := the k-permuation that maps I to I ′

σ(J, J ′) := the `-permuation that maps J to J ′

Thenf ′I′ =

∑I∈Γ(I′)

fIsgn(π(I, I ′))

g′J ′ =∑

J∈Γ(J ′)

gIsgn(σ(J, J ′))

47

Then ∑I′,J ′

f ′I′g

′J ′dXI′J ′ =

∑I′,J ′

∑I∈Γ(I′)

fIsgn(π(I, I ′))∑

J∈Γ(J ′)

gJsgn(σ(J, J ′))dXI′J ′

=∑I′,J ′

∑I∈Γ(I′)

∑J∈Γ(J ′)

fIgJsgn(π(I, I ′))sgn(σ(J, J ′))dXI′J ′

=∑I′,J ′

∑I∈Γ(I′)

∑J∈Γ(J ′)

fIgJdXIJ

=∑I,J

fIgJdXIJ

Proposition 6.3

Let V be an open subset of Rn and Ω•(V ) :=⊕∞

k=0 Ωk(V ). The wedge product

∧ : Ω•(V )× Ω•(V )→ Ω•(V )

satisfies:(i) distributivity:

(α + β) ∧ γ = α ∧ γ + β ∧ γ

(ii) associativity:(α ∧ β) ∧ γ = α ∧ (β ∧ γ)

(iii) graded-commutativity: For α ∈ Ωk(V ), β ∈ Ωl(V )

α ∧ β = (−1)klβ ∧ α

Proof(i) For α, β, γ ∈ Ω•(V ), by setting some coefficients to be 0, we may use same indexes to write

α =∑I

aIdXI , β =∑I

bIdXI

48

Let γ =∑

J cJdXJ . Then

(α + β) ∧ γ = (∑I

(aI + bI)dXI) ∧ (∑J

cJdXJ)

=∑I,J

(aI + bI)cJdXIJ

=∑I,J

aIcJdXIJ +∑I,J

bIcJdXIJ

= α ∧ γ + β ∧ γ

(ii) Let α =∑

I aIdXI , β =∑

J bJdXJ and γ =∑

L cLdXL be some differential forms on V .Then

(α ∧ β) ∧ γ = (∑I,J

aIbJdXIJ) ∧∑L

cLdXL

=∑I,J,L

(aIbJ)cLdX(IJ)L

=∑I,J,L

aI(bJcL)dXI(JL)

= (∑I

aIdXI)(∑J,L

bJcLdXJL)

= α ∧ (β ∧ γ)

(iii) Let α =∑

I aIdXI ∈ Ωk(V ) and β =∑

J bJdXJ ∈ Ωl(V ). For

I = (i1, · · · , ik), J = (j1, · · · , jl)

IJ = (i1, · · · , ik, j1, · · · , jl), JI = (j1, · · · , jl, i1, · · · , ik)

To get dXJdXis from dXisdXJ , each is needs to exchange its position with j1, · · · , jl, henceproduces a (−1)l. The total number of exchanges needed to get dXJI from dXIJ is kl, hence

α ∧ β =∑I,J

aIbJdXIJ = (−1)kl∑J,I

bJaIdXJI = (−1)klβ ∧ α

49

Example 6.10 Letα = dx1dx2 + dx3dx4 ∈ Ω2(R5)

β = dx1dx3dx5 + dx3dx4dx5 ∈ Ω3(R5)

Then

α ∧ β = (dx1dx2) ∧ (dx3dx4dx5) = −(dx1dx3dx2dx4dx5)

= (−1)3(dx1dx3dx4dx5dx2) = (−1)6(dx3dx4dx5dx1dx2)

= β ∧ α

50

6.2.2 The exterior derivative

Definition 6.9. The exterior derivative

Let V be an open subset of Rn. The exterior derivative is the operator d : Ωk(V )→ Ωk+1(V )

defined as follows:1. for k = 0 and f ∈ Ω0(V ),

df :=n∑i=1

∂f

∂xidxi ∈ Ω1(V )

2. for k ∈ N and α =∑

|I|=k aIdXI ∈ Ωk(V ),

dα :=∑|I|=k

daI ∧ dXI =∑|I|=k

n∑i=1

∂aI∂xi

dxidXI ∈ Ωk+1(V )

Example 6.11 Let α = sin(xy)dx+ cos(xy)dy ∈ Ω1(R2). Then

dα = cos(xy)(y)dxdx+ cos(xy)(x)dydx+ (−sin(xy)y)dxdy + (−sin(xy)x)dydy

= (−ysin(xy)− xcos(xy))dxdy

Example 6.12 Let α = fdx+ gdy ∈ Ω1(R2). Then

dα = (∂f

∂xdx+

∂f

∂ydy)dx+ (

∂g

∂xdx+

∂g

∂ydy)dy

=∂f

∂ydydx+

∂g

∂xdxdy = (

∂g

∂x− ∂f

∂y)dxdy

We show that the exterior derivative is well-defined.

Proposition 6.4Let V ⊂ Rn be an open subset. If

α =∑|I|=k

fIdXI =∑|J |=k

gJdXJ ∈ Ωk(V )

51

thend(∑|I|=k

fIdXI) = d(∑|J |=k

gJdXJ)

Proof Since the differential of a smooth function is unique, there is nothing to prove for k = 0. Letk ∈ N. Write

α =∑I′

f ′I′dXI′

where every I ′ is a k-tuple in ascending order. We use notations as in the proof of Proposition 6.2.Note that

f ′I′ =

∑I∈Γ(I′)

fIsgn(π(I, I ′))

anddf ′I′ =

∑I∈Γ(I′)

dfIsgn(π(I, I ′))

Then

d(∑I′

f ′I′dXI′) =

∑I′

df ′I′ ∧ dXI′

=∑I′

∑I∈Γ(I′)

dfIsgn(π(I, I ′)) ∧ dXI′

=∑I′

∑I∈Γ(I′)

dfI ∧ dXI

=∑I

dfI ∧ dXI

= d(∑I

fIdXI)

This proves that d is well-defined.

52

Proposition 6.5

Let V be an open subset ofRn and k ∈ N∪0. The exterior derivative d : Ωk(V )→ Ωk+1(V )

satisfies:

(i)d(aα + bβ) = adα + bdβ

for all a, b ∈ R, α, β ∈ Ωk(V ).(ii) If α ∈ Ωk(V ), β ∈ Ωl(V ), then

d(α ∧ β) = dα ∧ β + (−1)kα ∧ dβ

(iii)d2 = 0

That meansd(dα) = 0

for all α ∈ Ωk(V )

Proof(i) For f, g ∈ Ω0(V ),

d(af + bg) =n∑i=1

∂(af + bg)

∂xidxi =

n∑i=1

(a∂f

∂xi+ b

∂g

∂xi)dxi

= a

n∑i=1

∂f

∂xidxi + b

n∑i=1

∂g

∂xidxi

= adf + bdg

53

For α =∑

I aIdXI , β =∑

I bIdXI ,

d(aα + bβ) = d((∑I

aaI + bbI)dXI) =∑I

d(aaI + bbI) ∧ dXI

=∑I

(adaI + bdbI) ∧ dXI

= a∑I

daI ∧ dXI + b∑I

dbI ∧ dXI

= adα + bdβ

(ii) For f, g ∈ Ω0(V ),

d(f · g) =n∑i=1

∂(fg)

∂xidXi

=n∑i=1

(∂f

∂xig + f

∂g

∂xi)dXi

= (n∑i=1

∂f

∂xidXi)g + f(

n∑i=1

∂g

∂xidXi)

= (df)g + f(dg)

54

For α =∑

I aIdXI , β =∑

J bJdXJ ,

d(α ∧ β) = d(∑I,J

aIbJdXIJ) =∑I,J

d(aIbJ) ∧ dXIJ

=∑I,J

((daI)bJ + aI(dbJ)) ∧ dXIJ

=∑I,J

(daI)bJ ∧ dXI ∧ dXJ +∑I,J

aI(dbJ) ∧ dXI ∧ dXJ

= (∑I

daIdXI) ∧ (∑J

bJdXJ) +∑I,J

aI(dbJ) ∧ dXI ∧ dXJ

= dα ∧ β +∑I,J

aI

n∑i=1

∂bJ∂xi

dxi ∧ dXI ∧ dXJ

= dα ∧ β +∑I

aI(−1)kdXI ∧∑J

(n∑i=1

∂bJ∂xi

dxi) ∧ dXJ

= dα ∧ β + (−1)kα ∧ dβ

(iii) For f ∈ Ω0(V ), df =∑n

i=1∂f∂xidxi

d2f =n∑i=1

n∑j=1

∂2f

∂xj∂xidxjdxi

Note that∂2f

∂xj∂xidxjdxi = −

∂2f

∂xi∂xjdxidxj

55

Hence,

d2f =∑i<j

∂2f

∂xj∂xidxjdxi +

∑i=j

∂2f

∂xj∂xidxjdxi +

∑i>j

∂2f

∂xj∂xidxjdxi

=∑i<j

∂2f

∂xj∂xidxjdxi +

∑i>j

∂2f

∂xj∂xidxjdxi

=∑i<j

∂2f

∂xj∂xidxjdxi −

∑i>j

∂2f

∂xi∂xjdxidxj

=∑i<j

∂2f

∂xj∂xidxjdxi −

∑i<j

∂2f

∂xj∂xidxjdxi

= 0

Note thatd2XI = d(1dXI) = 0

For α =∑

|I|=k aIdXI ∈ Ωk(V ),

d2α = d(dα) = d(∑|I|=k

daI ∧ dXI) =∑|I|=k

(d2aI ∧ dXI − daI ∧ d2XI) = 0

Example 6.13 Let ω = sin(xy)dx+ zcosydy + xdz ∈ Ω1(R3). Then

dω = cos(xy)xdydx+ cosydzdy + dxdz

andd2ω = 0 + 0 + 0 = 0

56

K Exercise 6.2 k

1. Suppose that V is an open set of Rn. Let ϕ ∈ Ωk(V ) where k is an odd integer. Show thatϕ ∧ ϕ = 0.

2. Let

ϕ = xdx− ydy

ψ = zdxdy + xdydz

θ = zdy

Compute ϕ ∧ ψ, θ ∧ ϕ ∧ ψ, dϕ, dψ, dθ.3. Let

ω = dx1dx2 + dx3dx4 + · · ·+ dx2n−1dx2n ∈ Ω2(R2n)

Compute ωn the wedge product of n copies of ω.4. A function f : R3 → R is said to be homogeneous of degree k if

f(tx, ty, tz) = tkf(x, y, z)

for t > 0, (x, y, z) ∈ R3. Show that(a). If f is smooth and homogeneous of degree k, then

x∂f

∂x+ y

∂f

∂y+ z

∂f

∂z= kf

(b). If ω = adx+ bdy+ cdz ∈ Ω1(R3), a, b, c are homogeneous of degree k and dω = 0, finda smooth function g such that ω = dg.

(c). If α = adydz + bdzdx+ cdxdy where a, b, c are homogeneous of degree k and dα = 0,find β ∈ Ω1(R3) such that α = dβ.

57

6.3 Pushforward and pullback

Definition 6.10. Pushforward and pullback

Let V be an open subset of Rn, W be an open subset of Rm, and F : V → W be a smoothmap. If ϕ is a k-cell in V , define

F∗ϕ = F ϕ

Then F∗ϕ is a k-cell in W . Extending by linearity, we get a map F∗ : Ck(V )→ Ck(W ) by

F∗(l∑

i=1

aiϕi) :=l∑

i=1

aiF∗ϕi

The map F∗ is called the pushforward induced by F . Furthermore, F also induces a linearmap F ∗ : Ωk(W )→ Ωk(V ) by

(F ∗ω)(ϕ) := ω(F∗ϕ)

where ϕ ∈ Ck(V ) and ω ∈ Ωk(W ). The map F ∗ is called the pullback induced by F .

Example 6.14 Let V = BR2

1 (0) ⊂ R2, W = BR3

1 (0) ⊂ R3,

F (x, y) = (x2, y4,√2xy2)

Note that if (x, y) ∈ V , then

(x2)2 + (y4)2 + (√2xy2)2 = x4 + y8 + 2x2y4 = (x2 + y4)2 ≤ (x2 + y2)2 < 1

hence F is a function from V to W . Given ϕ : [0, 1]→ V where

ϕ(t) = (1

2t,1

3t)

Then(F∗ϕ)(t) = F (ϕ(t)) = F (

1

2t,1

3t) = (

1

4t2,

1

81t4,

√2

18t3)

Letω = xyzdx+ x2dy + ydz ∈ Ω1(W )

58

Then

(F ∗ω)(ϕ) = ω(F∗ϕ) = ω(F ϕ)

=

∫ 1

0

(1

4t2)(

1

81t4)(

√2

18t3)(

1

2t) + (

1

4t2)2(

4

81t3) + (

1

81t4)(

√2

6t2)dt

=

√2

8 · 81 · 181

11+

1

4 · 811

8+

√2

6 · 811

7

Definition 6.11

Let k ∈ N and k ≤ n. Suppose that A is a k × n matrix and B is an n × k matrix. ForJ = (j1 < j2 < · · · < jk) an ascending k-tuple in 1, ..., n, denote by

AJ :=

| | · · · |cj1 cj2 · · · cjk

| | · · · |

the k × k-matrix formed by the j1-th, j2-th,..., jk-th columns of A, and denote by

BJ :=

− rj1 −− rj2 −...

......

− rjk −

the k × k-matrix formed by the j1-th, j2-th,...,jk-th rows of B.

The following result from linear algebra will be needed in the proof of the next theorem.

Theorem 6.1. The Cauchy-Binet formula

Let k ∈ N and k ≤ n. Suppose that A is a k × n matrix and B is an n× k matrix then

det(AB) =∑

J ascending k-tuplein 1, ..., n

(detAJ)(detBJ)

59

Example 6.15 Let k = 2, n = 3, A =

(1 2 3

0 1 3

)2×3

, B =

1 1

2 0

3 1

3×2

Summing over all ascending 2-tuples J in 1, 2, 3, we get∑J⊂1,2,3,|J |=2

J ascending

(detAJ)(detBJ) = detA(1,2) detB(1,2) + detA(1,3) detB(1,3) + detA(2,3) detB(2,3)

= 1(−2) + 3(−2) + 3(2) = −2

which is same as

detAB = det

(14 4

11 3

)= −2

Theorem 6.2

Let V,W,W ′ be open subsets of Rn,Rm and Rr respectively. Suppose that F : V → W andG : W → W ′ are smooth maps. Then

1. (G F )∗ = F ∗ G∗.2. For F = (F1, ..., Fm), I = (i1, ..., ik), let

dFI := dFi1 ∧ dFi2 ∧ ... ∧ dFikand f : W → R be a smooth function. Then

F ∗(fdYI) = (F ∗f)dFI

3. If α ∈ Ωk(W ), β ∈ Ωl(W ), then

F ∗(α ∧ β) = F ∗α ∧ F ∗β

4. For α ∈ Ωk(W ),F ∗(dα) = d(F ∗α)

60

Proof In the following, let ϕ : [0, 1]k → V be a k-cell. Write

ϕ = (ϕ1, ..., ϕn)

1. Let γ ∈ Ωk(W ′) be a k-form on W ′ and ϕ be a k-cell in V . Then

((G F )∗γ)(ϕ) = γ((G F ) ϕ)

= γ(G (F ϕ)) = (G∗γ)(F ϕ)

= F ∗(G∗γ)(ϕ) = ((F ∗ G∗)γ)(ϕ)

This proves(G F )∗ = F ∗ G∗

2. Let I = (i1, ..., ik) and F = (F1, ..., Fm). Then

(F ϕ)I = (F1 ϕ, ..., Fm ϕ)I = FI ϕ.

Note that

DFI =

∂Fi1

∂x1· · · ∂Fi1

∂xn... . . . ...

∂Fik

∂x1· · · ∂Fik

∂xn

k×n

, Dϕ =

∂φ1

∂u1· · · ∂φ1

∂uk... . . . ...∂φn

∂u1· · · ∂φn

∂uk

n×k

By the Cauchy-Binet formula,

det∂(F ϕ)I∂u1,...,k

= det∂(FI ϕ)∂u1,...,k

= det[(∂FI

∂x1,...,n) ϕ](∂ϕ1,...,n

∂u1,...,k)

= det[(DFI) ϕ](Dϕ)

=∑

J⊂1,2,...,n,|J |=kJ ascending

det[(DFI) ϕ]J det(Dϕ)J

=∑

J⊂1,2,...,n,|J |=kJ ascending

det(∂FI∂XJ

ϕ) det( ∂ϕJ∂u1,...,k

)

61

Then

F ∗(fdYI)(ϕ) = (fdYI)(F ϕ)

=

∫[0,1]k

f(F ϕ) det ∂(F ϕ)I∂u1,...,k

dV

=

∫[0,1]k

f(F ϕ)∑

J⊂1,2,...,n,|J |=kJ ascending

det(∂FI∂XJ

ϕ) det( ∂ϕJ∂u1,...,k

)dV

=∑

J⊂1,2,...,n,|J |=kJ ascending

∫[0,1]k

(F ∗f)(ϕ) det(∂FI∂XJ

ϕ) det( ∂ϕJ∂u1,...,k

)dV

=∑

J⊂1,2,...,n,|J |=kJ ascending

(F ∗f det∂FI∂XJ

dXJ)(ϕ)

HenceF ∗(fdYI) =

∑J⊂1,2,...,n,|J |=k

J ascending

(F ∗f) det∂FI∂XJ

dXJ

In particular, when f ≡ 1,

F ∗(dYI) =∑

J⊂1,2,...,n,|J |=kJ ascending

det∂FI∂XJ

dXJ

We claim thatF ∗(dYI) = dFi1 ∧ dFi2 ∧ · · · ∧ dFik

Recall that if A =(aij

)k×k

,

detA =∑

π:k−permutation

sgn(π)a1π(1)a2π(2) · · · akπ(k)

62

Hence

dFI = dFi1 ∧ dFi2 ∧ · · · ∧ dFik

= (n∑

s1=1

∂Fi1∂xs1

dxs1) ∧ · · · ∧ (n∑

sk=1

∂Fi1∂xsk

dxsk)

=∑

s1,··· ,sk∈1,··· ,nall distinct

∂Fi1∂xs1

· · · ∂Fik∂xsk

dxs1 · · · dxsk

=∑

J⊂1,··· ,n,|J |=kJ ascending

(∑

π:k−permutation

sgn(π)∂Fi1∂xjπ(1)

· · · ∂Fik∂xjπ(k)

)dXJ

=∑

J⊂1,··· ,n,|J |=kJ ascending

det∂FI∂XJ

dXJ = F ∗dYI

3. For f, g ∈ Ω0(W ),

F ∗(f · g) = (f · g) F = (f F ) · (g F ) = F ∗f · F ∗g

Note that

F ∗(fdYI)(φ) = (fdYI)(F φ)

=

∫[0,1]k

(f F ) φ det ∂(F φ)I∂u1,...,k

dV = ((F ∗f)F ∗dYI)(φ)

Hence forα = fdYI ∈ Ωk(W ), β = gdYJ ∈ Ωℓ(W )

F ∗(α ∧ β) = F ∗(fgdYIJ) = F ∗(fg)F ∗(dYIJ) = (F ∗f)(F ∗g)dFIJ

= (F ∗f)(F ∗g)dFI ∧ dFJ = ((F ∗f)dFI) ∧ ((F ∗g)dFJ)

= (F ∗(fdYI)) ∧ (F ∗(gdYJ))

= F ∗α ∧ F ∗β

63

Since F ∗ is linear, the result is true for all k, `-forms on W .4. Let f ∈ Ω0(W ). We have

F ∗(df) = F ∗(m∑i=1

∂f

∂yidyi) =

m∑i=1

F ∗(∂f

∂yi)F ∗dyi

=m∑i=1

∂f

∂yi FdFi =

m∑i=1

∂f

∂yi F (

n∑j=1

∂Fi∂xj

dxj)

=n∑j=1

(m∑i=1

∂f

∂yi F )(∂Fi

∂xj))dxj =

n∑j=1

∂(f F )∂xj

dxj

= d(f F ) = d(F ∗f)

For ω = fdYI ,

F ∗(dω) = F ∗(df ∧ dYI) = F ∗(df) ∧ F ∗(dYI)

= d(F ∗f) ∧ dFI = d(F ∗f) ∧ dFI + F ∗f ∧ d(dFI)

= d((F ∗f) ∧ dFI) = d((F ∗f) ∧ (F ∗dYI))

= dF ∗(fdYI) = d(F ∗ω).

64

K Exercise 6.3 k

1.

65

6.4 Stokes’ theorem

Definition 6.12

Let V be an open subset of Rn and w ∈ Ωk(V ). If φ is a k−cell in V , denote∫ϕ

ω := ω(φ)

If Φ =∑N

j=1 ajφj ∈ Ck(V ), denote ∫Φ

ω :=N∑j=1

ai

∫ϕj

ω

Definition 6.13

Let V ⊂ Rn be an open subset. Denote

C−1(V ) := 0

For k = 0, defineτ 1,00 , τ 1,10 : [0, 1]0 := 1 → [0, 1]

byτ 1,00 (1) := 0, τ 1,10 (1) := 1

For k ∈ N and 1 ≤ j ≤ k + 1, define τ j,1k , τ j,0k : [0, 1]k → [0, 1]k+1 byτ j,0k (u1, · · · , uk) = (u1, · · · , uj−1, 0, uj, · · · , uk)τ j,1k (u1, · · · , uk) = (u1, · · · , uj−1, 1, uj, · · · , uk)

66

Definition 6.14. Boundary operator

Let V be an open subset ofRn. For k ∈ N∪0, the boundary operator ∂ : Ck(V )→ Ck−1(V )

is defined as following: Let φ be a k−cell in V . If k = 0, define

∂φ = 0

If k ∈ N and 1 ≤ j ≤ k, define

∂jφ = φ τ j,1k−1 − φ τj,0k−1

and

∂φ =k∑j=1

(−1)j+1∂jφ

Then extend ∂ by linearity.

67

Example 6.16 Let φ : [0, 1]2 → R3 be defined by

φ(s, t) = (st, 3s+ t, s2 + t3)

Then

φ τ 1,11 (t) = φ(1, t) = (t, 3 + t, 1 + t3),

φ τ 1,01 (t) = φ(0, t) = (0, 0 + t, t3),

φ τ 2,11 (t) = φ(t, 1) = (t, 3t+ 1, t2 + 1),

φ τ 2,01 (t) = φ(t, 0) = (0, t, t2),

∂φ = ∂1φ− ∂2φ = (φ τ 1,11 − φ τ1,01 )− (φ τ 2,11 − φ τ

2,01 )

Example 6.17 Note that the boundary of a cell is a chain. The boundary of an 1-cell is a 0-chain.For example, let ϕ : [0, 1]→ R2 be defined by

ϕ(t) = (t, t2)

Then∂ϕ = ϕ(1)− ϕ(0) = (1, 1)− (0, 0)

where we identify (1, 1), (0, 0) with the functions from [0, 1]0 = 1 to R2 that map 1 to (1, 1), 0 to(0, 0) respectively. Hence (1, 1)− (0, 0) is a 0-chain not equal to (1, 1).

Lemma 6.2

Let W ⊂ Rn be an open set such that [0, 1]n ⊂ W . If ω ∈ Ωn−1(W ) and η : [0, 1]n → W isthe identity-inclusion n-cell in W , i.e.,

η(u1, ..., un) := (u1, ..., un)

then ∫η

dω =

∫∂η

ω

68

Proof Let

ω =n∑i=1

fidx1 ∧ ... ∧ dxi ∧ ... ∧ dxn

wheredx1 ∧ ... ∧ dxi ∧ ... ∧ dxn = dx1 ∧ ... ∧ dxi−1 ∧ dxi+1 ∧ ... ∧ dxn

and each fi : Rn → R is a smooth function. Then

dω =n∑i=1

(n∑j=1

∂fi∂xj

dxj)dx1 ∧ ... ∧ dxi ∧ ... ∧ dxn

=n∑i=1

∂fi∂xi

dxi ∧ dx1 ∧ ... ∧ dxi ∧ ... ∧ dxn

=n∑i=1

(−1)i−1 ∂fi∂xi

dx1 ∧ ... ∧ dxn

Note that∂η

∂u1,...,n= In = the n× n identity matrix

∫η

dω = (dω)(η) =n∑i=1

(−1)i−1

∫[0,1]n

∂fi∂xi

(η(u1, ..., un))(det∂η

∂u1,...,n)dVn

=n∑i=1

(−1)i−1

∫[0,1]n

∂fi∂xi

(u1, ..., un)dVn

Let Ij = (1, ..., j, ..., n). Then |Ij| = n− 1. Note that

τ i,0n−1(u) = (u1, ..., ui−1, 0, ui, ..., un−1)

τ i,1n−1(u) = (u1, ..., ui−1, 1, ui, ..., un−1)

and

det∂(τ i,0n−1)Ij∂u1,...,n−1

= det∂(τ i,1n−1)Ij∂u1,...,n−1

=

1 if i = j

0 otherwise

69

We have∫∂iη

ω =

∫ητ i,1n−1−ητ

i,0n−1

ω =

∫τ i,1n−1−τ

i,0n−1

ω

=n∑j=1

∫[0,1]n−1

fj τ i,1n−1 det∂(τ i,1n−1)Ij∂u1,...,n−1

− fj τ i,0n−1 det∂(τ i.0n−1)Ij∂u1,...,n−1

dVn−1

=

∫[0,1]n−1

fi τ i,1n−1 − fi τi,0n−1dVn−1

=

∫[0,1]n−1

fi(u1, ..., ui−1, 1, ui, ..., un−1)− fi(u1, ..., ui−1, 0, ui, ..., ui−1)dVn−1

FTC=

∫[0,1]n−1

(

∫ 1

0

∂fi∂xi

(u1, ..., ui−1, x, ui, ..., un−1)dxi)dVn−1

=

∫[0,1]n

∂fi∂xi

dVn

Hence ∫∂η

ω =n∑i=1

(−1)i+1

∫∂iη

ω =n∑i=1

(−1)i+1

∫[0,1]n

∂fi∂xi

dVn =

∫η

Theorem 6.3. Stokes theorem

Let V be an open subset of Rn. For k ∈ N ∪ 0, if ω ∈ Ωk(V ) and ϕ ∈ Ck+1(V ), then∫φ

dω =

∫∂φ

ω

Proof Let ϕ be a (k+1)-cell in V . Since ϕ is a smooth map, by the definition of smoothness, thereis an open set W ⊂ Rk+1 and a smooth map ϕ : W → V such that

[0, 1]k+1 ⊂ W and ϕ|[0,1]k+1 = ϕ

Let η : [0, 1]k+1 → W be the identity-inclusion. Note that

ϕ∗(η) = ϕ η = ϕ

70

and

ϕ∗(∂η) = ϕ∗(k+1∑j=1

(−1)j+1∂jη)

=k+1∑j=1

(−1)j+1(ϕ (η τ j,1k )− ϕ (η τ j,0k ))

=k+1∑i=1

(−1)j+1(ϕ τ j,1k − ϕ τj,0k )

= ∂ϕ

Then ∫φ

dω =

∫φ∗(η)

dω = (dω)(ϕ∗η)

= (ϕ∗dω)(η) = (dϕ∗ω)(η) =

∫η

dϕ∗ω

=

∫∂η

ϕ∗ω = (ϕ∗ω)(∂η)

= ω(ϕ∗(∂η)) = ω(∂ϕ)

=

∫∂φ

ω

For a (k + 1)-chain ϕ =∑ℓ

i=1 aiϕi in V ,∫φ

dω =

∫∑ℓ

i=1 aiφi

dω =ℓ∑i=1

ai

∫φi

dω =ℓ∑i=1

ai

∫∂φi

ω =

∫∑ℓ

i=1 ai∂φi

ω =

∫∂φ

ω

This completes the proof.

71

K Exercise 6.4 k

1. In Rn, define∗(fdXI) = sgn(π)fdXJ

where |I| + |J | = n, I, J ascending, I ∪ J = 1, 2, ..., n and π is a n-permutation thatpermutes (1, 2, ..., n) to (IJ). For example in R3, ∗(dx2) = −dx1dx3. Extend by linearity weget a map

∗ : Ωk(Rn)→ Ωn−k(Rn)

which is called the Hodge star operator.(a). If ω = a12dx1 ∧ dx2 + a13dx1 ∧ dx3 + a23dx2 ∧ dx3 is a 2-form in R3, find ∗ω. If we

consider ω as a 2-form in R4, what is ∗ω? In general, if we consider ω as a 2-form in Rn,what is ∗ω?

(b). Show that ∗ ∗ ω = (−1)k(n−k)ω.(c). Find ∗d ∗ (dxI).(d). Let δ = (−1)n(k+1)+1 ∗ d∗ : Ωk(Rn) → Ωk−1(Rn) and ∆ = (dδ + δd) : Ωk(Rn) →

Ωk(Rn). Show that on 0-forms, ∆ = −∑n

j=1∂2

∂x2j.

(e). Let η : In → Rn be the inclusion map which we consider as a n-cell of Rn. Forα, β ∈ Ωk(Rn), define

< α, β >:=

∫η

α ∧ ∗β

Show that <,> is an inner product on Ωk(Rn).(f). Using Stokes’ theorem, show that δ is the adjoint of d, i.e., < dα, β >=< α, δβ > for

α or β having zero boundary values. (A form γ ∈ Ωk(V ) is said to have zero boundaryvalue if γ =

∑I aIdXI , then each aI(η τ j,i) = 0 for j = 1, ..., n, i = 0, 1.)

2. Show that ∂2c = 0 for c ∈ Ck(V ) where V is an open set of Rn.

72

6.5 Applications of the Stokes theorem

6.5.1 Reduction to some theorems in calculus

Definition 6.15

A smooth map F : R3 → R3 is called a vector field on R3. Let

V F (R3) := F |F is a vector field on R3

For f : R3 → R a smooth function, define the gradient of f to be

∇(f) := (∂f

∂x,∂f

∂y,∂f

∂z)

For F = (F1, F2, F3) ∈ V F (R3), define the curl of F to be

curl(F ) := det

i j k∂∂x

∂∂y

∂∂z

F1 F2 F3

:= (∂F3

∂y− ∂F2

∂z, −(∂F3

∂x− ∂F1

∂z),∂F2

∂x− ∂F1

∂y)

and the divergence of F to be

div(F ) :=∂F1

∂x+∂F2

∂y+∂F3

∂z

Definition 6.16

Suppose that we have homomorphisms between vector spaces

V1Ψ1 //

Φ1

V2

Φ2

W1

Ψ2 //W2

We say that the square is a commutative diagram if

Φ2 Ψ1 = Ψ2 Φ1

73

Proposition 6.6

Each square in the following diagram is commutative:

0 //

Ω0(R3) d //

Φ0

Ω1(R3) d //

Φ1

Ω2(R3) d //

Φ2

Ω3(R3) d //

Φ3

0

0 / / C ∞(R3) ∇ // V F (R3)

curl // V F (R3)div // C ∞(R3) // 0

where those functions on the vertical arrows are defined as follow:

Φ0(f) := f

Φ1(f1dx+ f2dy + f3dz) := (f1, f2, f3)

Φ2(g1dxdy + g2dxdz + g3dydz) := (g3,−g2, g1)

Φ3(fdxdydz) = f

and they are isomorphisms between vector spaces.

Proof We prove that each square is commutative as follows:1.

Prove: Φ1 d = ∇ Φ0

For f ∈ Ω0(R3),

Φ1(df) = Φ1(∂f

∂xdx+

∂f

∂ydy +

∂f

∂zdz)

= (∂f

∂x,∂f

∂y,∂f

∂z)

= ∇(f) = ∇ Φ0(f)

2.Prove: Φ2 d = curl Φ1

74

Φ2 d(f1dx+ f2dy + f3dz)

= Φ2[∂f1∂y

dydx+∂f1∂z

dzdx+∂f2∂x

dxdy +∂f2∂z

dzdy +∂f3∂x

dxdz +∂f3∂y

dydz]

= Φ2[(∂f2∂x− ∂f1

∂y)dxdy + (

∂f3∂x− ∂f1

∂z)dxdz + (

∂f3∂y− ∂f2

∂z)dydz]

= ((∂f3∂y− ∂f2

∂z), −(∂f3

∂x− ∂f1

∂z), (

∂f2∂x− ∂f1

∂y))

= curl(f1, f2, f3) = curl(Φ1(f1dx+ f2dy + f3dz))

3.Prove: Φ3 d = div Φ2

Φ3d(g1dxdy + g2dxdz + g3dydz) = Φ3(∂g1∂z

dzdxdy +∂g2∂y

dydxdz +∂g3∂x

dxdydz)

= Φ3((∂g1∂z− ∂g2

∂y+∂g3∂x

)dxdydz)

=∂g1∂z− ∂g2

∂y+∂g3∂x

= div(g3,−g2, g1)

= div(Φ2(g1dxdy + g2dxdz + g3dydz))

Corollary 6.3

1.curl ∇ = 0

2.div curl = 0

Proof Recall that we have d2 = 0. Thus

75

1.curl ∇ = Φ2 d d Φ−1

0 = 0

2.div curl = Φ3 d d Φ−1

1 = 0

We leave the proof of the following result to the appendix of this section.

Theorem 6.4. Change of variables formula

Let U,W ⊂ Rn be some open sets and Φ : U → W be a C 1-diffeomorphism. Let f : W → Rbe a Riemann integrable function and R ⊂ U be a rectangle. Then∫

R

f Φ| det(DΦ)|dV =

∫Φ(R)

fdV

Definition 6.17

♣Let ϕ : [0, 1]k → Rn be a k-cell. We say that ϕ is injective if ϕ is an injective map.

We now use the language of forms and chains to interpret several results in calculus.

Definition 6.18

Let C ∈ C1(R2). If there is an injective 2-cell ϕ : [0, 1]2 → R2 such that

∂ϕ = C and det(Dϕ) > 0

then we say that C is a positively oriented, piecewise-smooth, simple closed curve in the planeand D := image ϕ is the region bounded by C.

Remark We remark that even though we prove Stokes’ theorem for smooth forms and smooth chains,the proof goes through for C 1-forms and C 1-chains. We will use this C 1 version Stokes’ theorem inthe following paragraphs.

The following statement of the Green theorem is from Stewart’s Calculus [? ].

76

Theorem 6.5. Green’s theorem

Let C be a positively oriented, piecewise-smooth, simple closed curve in the plane and let Dbe the region bounded by C. If P andQ have continuous partial derivatives on an open regionthat contains D, then ∫

C

Pdx+Qdy =

∫∫D

(∂Q

∂x− ∂P

∂y)dA

Proof ∫C

Pdx+Qdy =

∫∂φ

Pdx+Qdy =

∫φ

d(Pdx+Qdy) =

∫φ

(∂Q

∂x− ∂P

∂y)dxdy

=

∫[0,1]2

(∂Q

∂x ϕ− ∂P

∂y ϕ) det ∂ϕ

∂u1,2dV

=

∫∫D

(∂Q

∂x− ∂P

∂y)dA

where the second equality comes from the Stokes’ theorem and the last equality comes from thechange of variables formula.

Definition 6.19

Let ϕ be an injective 2-cell in R3 and C ∈ C1(R3) be an 1-chain such that

∂ϕ = C

We say that S := image of ϕ is an oriented piecewise-smooth surface that is bounded bya simple, closed, piecewise-smooth boundary curve C with positive orientation. Let F =

(F1, F2, F3) be a vector field whose components have continuous partial derivatives on anopen region in R3 that contains S. Define∫

C

F · dr :=∫C

F1dx+ F2dy + F3dz∫∫S

F · dS :=

∫∫[0,1]2

(F ϕ) · (ϕu × ϕv)dA

The following statement of the Stokes’ theorem is from Stewart’s Calculus [? ].77

Theorem 6.6. Stokes’ theorem in Calculus

Let S be an oriented piecewise-smooth surface that is bounded by a simple, closed, piecewise-smooth boundary curve C with positive orientation. Let F = (F1, F2, F3) be a vector fieldwhose components have continuous partial derivatives on an open region in R3 that containsS. Then ∫

C

F · dr =∫∫

S

curl(F ) · dS

Proof Suppose that ϕ : [0, 1]2 → R3 is an injective 2-cell such that S is the image of ϕ and

∂ϕ = C

Then ∫C

F · dr =∫∂φ

F1dx+ F2dy + F3dz =

∫φ

d(F1dx+ F2dy + F3dz)

=

∫φ

(∂F2

∂x− ∂F1

∂y)dxdy + (

∂F3

∂x− ∂F1

∂z)dxdz + (

∂F3

∂y− ∂F2

∂z)dydz

=

∫φ

curl(F ) · (dydz,−dxdz, dxdy)

=

∫[0,1]2

curl(F ) ϕ · (det(∂ϕ2,3

∂u1,2), − det(

∂ϕ1,3

∂u1,2), det(

∂ϕ1,2

∂u1,2))dV

=

∫[0,1]2

curl(F ) ϕ · (ϕu1 × ϕu2)dV

=

∫∫S

curl(F ) · dS

where the second equality is from the Stokes’ theorem.

Definition 6.20Let φ be an injective 3-cell in R3 and S ∈ C2(R3) be a 2-chain such that

∂φ = S and det(Dφ) > 0

on [0, 1]3. We say thatE := images of φ is a simple solid region and S is the boundary surface

78

♣of E with positive orientation.

The following statement of the divergence theorem is from Stewart’s Calculus [? ].

Theorem 6.7. The divergence theorem

LetE be a simple solid region and let S be the boundary surface ofE with positive orientation.Let F = (F1, F2, F3) be a vector field whose component functions have continuous partialderivatives on an open region that contains E. Then∫∫

S

F · dS =

∫∫∫E

divFdV

Proof Let E be the image of an injective 3-cell ψ in R3 and

S =6∑i=1

aiϕi

where each ϕi is a 2-cell in R3 and ai ∈ 1,−1.Note that for a 2-cell ϕ in R3,∫[0,1]2

(F ϕ) · (ϕu1 × ϕu2)dV =

∫[0,1]2

(F ϕ) · (det(∂ϕ2,3

∂u1,2), − det(

∂ϕ1,3

∂u1,2), det(

∂ϕ1,2

∂u1,2))dV

=

∫φ

F · (dydz,−dxdz, dxdy)

79

Then∫∫S

F · dS =

∫∫∑6

i=1 aiφi

F · dS

=6∑i=1

ai

∫[0,1]2

(F ϕi) · (ϕi,u1 × ϕi,u2)dA

=6∑i=1

ai

∫φi

F · (dydz,−dxdz, dxdy)

=

∫S

F · (dydz,−dxdz, dxdy)

=

∫∂ψ

(F1, F2, F3) · (dxdy,−dxdz, dydz) =∫ψ

d(F1dxdy − F2dxdz + F3dydz)

=

∫ψ

div(F )dxdydz =

∫[0,1]3

div(F ) ψ det(∂ψ

u1,2,3)dV

=

∫∫∫E

div(F )dV

where the last equality follows from the change of variables formula.Example 6.18 Let

E := (x, y, z) ∈ R3|x2 + y2 + z2 ≤ 4

be a simple solid region and let S be the boundary surface of E with positive orientation. Let

ω = zdxdy − ydxdz + xdydz

Find∫Sω.

Solution Let ϕ : [0, 1]3 → R3 be an injective 3-cell such that the image of ϕ is E. Note that

dω = dzdxdy − dydxdz + dxdydz = 3dxdydz

80

Then by the Stokes’ theorem∫S

ω =

∫∂φ

ω =

∫φ

=

∫φ

3dxdydz = 3

∫∫∫E

dV = 3V ol(E) = 3(4

3)π(2)3 = 32π

81

6.6 De Rham cohomology

We recall some results from linear algebra.

Definition 6.21

Let E be a vector space and F ⊂ E be a vector subspace. For e ∈ E, write

[e] := e+ f |f ∈ F

The quotient space E/F is defined to be

E/F := [e]|e ∈ E

It is a standard result in linear algebra that E/F is again a vector space with linear structureinduced from E. We need the following simple result for proving some results later.

Proposition 6.7

Let E1, E2 be two vector spaces and F1 ⊂ E1, F2 ⊂ E2 are vector subspaces respectively.Let T : E1 → E2 be a linear transformation. If T (F1) ⊂ F2, then T induces a lineartransformation

T : E1/F1 → E2/F2

byT ([e]) := [T (e)]

Definition 6.22Let V be an open subset of Rn and ω ∈ Ωk(V ). We say that ω is closed if

dω = 0

We say that ω is exact ifω = dα

82

for some α ∈ Ωk−1(V ). Let

Zk(V ) := ω ∈ Ωk(V )|dω = 0, Bk(V ) := ω ∈ Ωk(V )|ω is exact.

Note since d2 = 0, exact forms are closed. Hence

Bk(V ) ⊂ Zk(V )

The vector space

Hk(V ) =Zk(V )

Bk(V )

is called the k-th de Rham cohomology group.

Proposition 6.8

Let V be an open subset of Rn,W be an open subset of Rm and F : V → W be a smooth map.Then

1. F ∗ induces a linear map F ∗ : Hk(W )→ Hk(V ) defined by

F ∗[ω] := [F ∗ω]

for k ≥ 0.2. If F is a diffeomorphism, then F ∗ : Hk(W ) → Hk(V ) is an isomorphism of vector

spaces for all k ∈ N ∪ 0.

Proof If ω ∈ Zk(W ), thend(F ∗(ω)) = F ∗(dω)

Hence, F ∗(Zk(W )) ⊂ Zk(V ). If ω ∈ Bk(W ), then ω = dα for some α ∈ Ωk−1(W ). So

F ∗(ω) = F ∗dα = d(F ∗α)

Hence F ∗(Bk(W )) ⊂ Bk(V ). Since F ∗ : Zk(W )→ Zk(V ) is linear, by Proposition 6.7 F inducesa linear transformation F ∗ : Hk(W )→ Hk(V ).

2. Suppose that F is a diffeomorphism, we have F F−1 = idW and F−1 F = idV , then83

(F−1 F )∗ = F ∗ (F−1)∗ = (idV )∗ = idHk(V )

which implies that F ∗ is onto. From

(F F−1)∗ = (F−1)∗ F ∗ = (idW )∗ = idHk(W )

we see that F ∗ is one-to-one. Therefore, F ∗ is an isomorphism.

Proposition 6.9

♠If V ⊂ Rn is a nonempty connected open subset, then H0(V ) ∼= R.

Proof Note that B0(V ) = 0. For f ∈ Z0(V ),

df =n∑i=1

∂f

∂xidxi = 0

which means ∂f∂xi≡ 0 on V , for all i = 1, · · · , n. So grad(f) = 0 on V . By theorem, f is a constant

function on V . Hence Z0(V ) = R and

H0(V ) = R/0 ∼= R

Corollary 6.4

If V ⊂ Rn is an open subset which has k connected components, then

H0(V ) ∼= Rk

The following famous result says that all closed k−forms on Rn are exact.

Theorem 6.8. Poincaré lemma

For k ∈ N,Hk(Rn) = 0

84

Corollary 6.5

R2 − (0, 0) is not diffeomorphic to R2.

Proof Letω = − y

x2 + y2dx+

x

x2 + y2dy ∈ Ω1(R2 − (0, 0))

We have

dω = −(x2 + y2)− y(2y)(x2 + y2)2

dydx+(x2 + y2)− x(2x)

(x2 + y2)2dxdy

=(x2 − y2)(x2 + y2)2

dxdy − (x2 − y2)(x2 + y2)2

dxdy = 0

Let φ : [0, 1]→ R2 − (0, 0) be defined by

φ(θ) = (cos 2πθ, sin 2πθ)

Assume that w = dα for some α ∈ Ω0(R2 − (0, 0)). Then by Stokes’ theorem,∫ϕ

ω =

∫ϕ

dα =

∫∂ϕ

α = α(φ(1))− α(φ(0)) = 0

But ∫ϕ

ω =

∫ 1

0

− sin 2πθ

cos2 2πθ + sin2 2πθ(− sin 2πθ)(2π) +

cos 2πθ

cos2 2πθ + sin2 2πθ(cos 2πθ)(2π)dθ

=

∫ 1

0

2πdθ = 2π = 0

which is a contradiction. Therefore some closed 1-forms onR2−(0, 0) are not exact which impliesthat H1(R2 − (0, 0)) = 0. But by the Poincaré lemma, H1(R2) = 0, this proves the result.

85

Appendix 6.6

Theorem 6.9. Poincaré lemma

For k ∈ N,Hk(Rn) = 0

Proof Let β ∈ Ωk(Rn+1). Write

β =∑|I|=k

fIdXI +∑

|J |=k−1

gJdt ∧ dXJ

Define N : Ωk(Rn+1)→ Ωk−1(Rn) by

N(β) :=∑

|J |=k−1

(

∫ 1

0

gJ(x, t)dt)dXJ

We claim that(dN +Nd)(β) =

∑I

(fI(x, 1)− fI(x, 0)dXI

We compute

dβ =∑|I|=k

(n∑l=1

∂fI∂xl

dxl) ∧ dXI +∑|I|=k

∂fI∂t

dt ∧ dXI +∑

|J |=k−1

(n∑l=1

∂gJ∂xl

dxl) ∧ dt ∧ dXJ

N(dβ) =∑|I|=k

(

∫ 1

0

∂fI∂t

dt)dXI −∑

|J |=k−1

n∑l=1

(

∫ 1

0

∂gJ∂xl

dxl) ∧ dt ∧ dXJ

dN(β) =∑

|J |=k−1

n∑l=1

(

∫ 1

0

∂gJ∂xl

dt)dxl ∧ dXJ

(dN +Nd)(β) =∑|I|=k

n∑l=1

(

∫ 1

0

∂fI∂t

dXI)FTC=

∑|I|=k

(fI(x, 1)− fI(x, 0))dXI

Define ρ : Rn+1 → Rn byρ(x, t) = tx

86

where x = (x1, · · · , xn). Let L = N ρ∗. Then

Ld+ dL = Nρ∗d+ dNρ∗ = Ndρ∗ + dNρ∗ = (Nd+ dN)ρ∗

Let ω = hdXI ∈ Ωk(Rn), I = (i1, · · · , ik)

ρ∗(hdXI) = (ρ∗h)(ρ∗dXI) = h(tx)dρI

Note that

dρI = dρi1 ∧ · · · ∧ dρik = d(txi1) ∧ · · · ∧ d(txik) = (tdxi1 + xi1dt) ∧ · · · ∧ (tdxik + xikdt)

= tkdXI + terms that include dt

Henceρ∗(hdXI) = h(tx)(tkdXI + terms that include dt)

Then

(Nd+ dN)ρ∗ω = (Nd+ dN)ρ∗(hdXI) = (h(1x)1k − h(0x)0k)dXI = h(x)dXI = ω

By linearity, for all ω ∈ Ω(Rn),(Nd+ dN)ρ∗ω = ω

If dω = 0, thenω = (Nd+ dN)ρ∗ω = Nρ∗dω + d(Nρ∗ω) = d(Nρ∗ω)

Hence ω is exact and therefore Hk(Rn) = 0, for all k > 0

87

88

Bibliography

[1] Marsden J. and Hoffman M.J., Elementary classical analysis, 2nd ed., Freeman, New York, 1993.[2] Pugh, C.C., Real mathematical analysis, Springer-Verlag, New York, 2002.[3] Rudin, W., Principles of mathematical analysis, 3rd edition, McGraw-Hill, New York, 1985.

Index

Absorbing barrier, 4Adjoint partial differential operator, 20A-harmonic function, 16, 182A∗-harmonic function, 182

Boundary condition, 20, 22Dirichlet, 15Neumann, 16

Boundary value problemthe first, 16the second, 16the third, 16

Bounded set, 19

Diffusioncoefficient, 1equation, 3, 23

Dirichletboundary condition, 15boundary value problem, 16

Ellipticboundary value problem, 14, 158partial differential equation, 14

partial differential operator, 19

Fick’s law, 1Flux, 1Formally adjoint partial differential operator,

20Fundamental solution

conceptional explanation, 12general definition, 23temporally homogeneous case, 64, 112

Genuine solution, 196Green function, 156Green’s formula, 21

Harnack theoremsfirst theorem, 185inequality, 186lemma, 186second theorem, 187third theorem, 187

Helmhotz decomposition, 214Hilbert-Schmidt expansion theorem, 120

Initial-boundary value problem, 22

Initial condition, 22Invariant measure (for the fundamental

solution), 167

Maximum principlefor A-harmonic functions, 183for parabolic differential equations, 65strong, 83

Neumannboundary condition, 16boundary value problem, 16function, 179

One-parameter semigroup, 113

Parabolic initial-boundary value problem, 22Partial differential equation

of elliptic type, 14of parabolic type, 22

Positive definite kernel, 121

Reflecting barrier, 4Regular (set), 19Removable isolated singularity, 191Robin problem, 16

Semigroup property (of fundamentalsolution), 64, 113

Separation of variables, 131Solenoidal (vector field), 209Strong maximum principle, 83Symmetry (of fundamental solution), 64, 112

Temporally homogeneous, 111

Vector field with potential, 209

Weak solutionof elliptic equations, 195of parabolic equation, 196associated with a boundary condition, 204

91