Multivariable Calculus Flashcards

1
Q

Define Euclidean distance for x,y in Rn

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2
Q

Define the Euclidean norm

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3
Q

Define the | . |1 norm

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4
Q

Define convergence for a sequence of vectors (xj)

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5
Q

Define the scalar product

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6
Q

State and prove the Cauchy-Schwartz inequality

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7
Q

Define cos theta with regards to the cauchy schwartz inequality

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8
Q

State and prove the triangle inequality

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9
Q

State the relationship between the euclidean norm and the 1 norm

A

|x| <= |x|1 <= sqrt(n) |x|

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10
Q

Define the infinity norm

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11
Q

State and prove the relationship between the euclidean norm and the infinity norm

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12
Q

Prove the uniqueness of limits for a sequence (xj)

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13
Q
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14
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15
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16
Q
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17
Q

Give the sequential definition of continuity

A

f is continuous at p, if for every sequence (xj) which converges to p, f(xj) converges to f(p)

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18
Q
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19
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20
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21
Q
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22
Q

Prove that a Cauchy sequence (xj) is convergent

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23
Q

Define the Open Ball

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24
Q

Define continuity of a function f: U to Rn at p in terms of open balls

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25
Q

When is U, a subset of Rn, open?

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26
Q
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27
Q

Define the epsilon nieghbourhood of E

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28
Q

Proposition: If E1,……., Em are all closed then the union is closed

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29
Q

Proposition: Let U1,……,Um be open sets, then the intersection is open

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30
Q

Proposition: A set is closed if and only if it contains all its limit points

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31
Q

Define relatively open

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32
Q

Define an isolated point of U

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33
Q

Define a continuous limit

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34
Q
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35
Q

Define a path from p in Rn to q in Rn

A

A path is a continuous map r: [a,b] to U, [a,b] in R such that r(a) = p and r(b) = q

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36
Q

Define path connected for U, a subset of Rn

A

for all p,q in U, there is a path r:[a,b] to U such that r(a) = p and r(b) = q

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37
Q
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38
Q

Define sequential compactness for K, a subset of Rn

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39
Q
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40
Q

K, a subset of R2 is sequentially compact if and only if K is closed and bounded

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41
Q

State and prove the extreme value theorem a subset K in Rn

42
Q

Let V = { (x,y) : xy not equal to 0}. Prove V isn’t path connected

43
Q

What is meant by L(Rn, Rk) and M(k x n, R)

44
Q

Define || (aij) ||2

45
Q

Define the operator norm

46
Q

What is the relationship between || A || and || (aij) ||2?

47
Q

Prove that ||BA|| <= ||B|| ||A||

48
Q

Define the General Linear group

50
Q

Define differentiability for a point p, in U, a subset of Rn

52
Q

State the chain rule

53
Q

Define directional derivative

54
Q

Define the partial derivative

56
Q

Define the Jacobian matrix

57
Q

What condition must hold in the Jacobian matrix for p to be differentiable

A

it must exist at all points

58
Q

Define continuously differentiable

59
Q

What is the Jacobian form of the chain rule?

60
Q

Define grad f

61
Q

Given f: Rn to R and g:R to R whats the jth partial derivative of g(f(x)), and then define grad g(f(x))

62
Q

define d/dt f(r(t)) for f:Rn to R and r:R to Rn

64
Q

Define a change of variables

66
Q

State the Inverse function theorem

68
Q

State the Implicit function theorem

69
Q

Define a vector field

70
Q

Define the Curve Cpq

71
Q

Define the tangential line integral

74
Q

Define a gradient field

A

If a vector field v is the gradient of a function f : U → R then v is called a gradient field.

75
Q

State the fundamental theorem of calculus for a gradient vector field

77
Q

Define conservative

79
Q

Theorem: A vector field v: U to Rn is a gradient field if and only if its conservative

80
Q

When is f called a scalar potential of v

A

When v = grad f

81
Q

Define v perp, and then the normal to a curve C

82
Q

Define the flux of a vector field in R2

83
Q

Derive greens theorem for a rectangle

84
Q

Define a region in Rn

85
Q

Define curl

86
Q

Define a positively oriented regular parameterisation

87
Q

State Greens theorem for a planar region

88
Q

Give the equation for the flux of of v across the boundary of omega

89
Q

Define the divergence of a vector field

90
Q

State the divergence theorem

91
Q

Give the two equations for the flux of v across a surface S in R3

92
Q

State the divergence theorem in R3

93
Q

Define a radial function

94
Q

Define Hess f(p)

95
Q

When do second order partial derivatives commute?

A

D2f exists

the second partial derivatives are continuous

96
Q

State Taylor’s theorem, both for the 1 variable case, and otherwise

97
Q

State the conditions for when a symmetric matrix is

i) positive definite
ii) positive semidefinite
iii) negative definite
iv) negative semidefinite
v) indefinite

98
Q

State the second order derivative test

99
Q

State the definitiveness test for 2x2 symmetric matrices