The document defines the operators curl and divergence for vector fields. Curl is defined as the cross product of del (the gradient operator) with the vector field and results in another vector. Divergence is defined as the dot product of del with the vector field and results in a scalar. Several examples of computing curl and divergence are worked out. Green's theorem, which relates line integrals of vector fields to surface integrals of curl and divergence, is also discussed.
In this presentation we will learn Del operator, Gradient of scalar function , Directional Derivative, Divergence of vector function, Curl of a vector function and after that solved some example related to above.
Gradient in math
Directional derivative in math
Divergence in math
Curl in math
Gradient , Directional Derivative , Divergence , Curl in mathematics
Gradient , Directional Derivative , Divergence , Curl in math
Gradient , Directional Derivative , Divergence , Curl
In this presentation we will learn Del operator, Gradient of scalar function , Directional Derivative, Divergence of vector function, Curl of a vector function and after that solved some example related to above.
Gradient in math
Directional derivative in math
Divergence in math
Curl in math
Gradient , Directional Derivative , Divergence , Curl in mathematics
Gradient , Directional Derivative , Divergence , Curl in math
Gradient , Directional Derivative , Divergence , Curl
The cross product is an important operation, taking two three-dimensional vectors and producing a three-dimensional vector. It's not a product in the commutative, associative, sense, but it does produce a vector which is perpendicular to the two crossed vectors and whose length is the area of the parallelogram spanned by the them. The direction is chosen again to follow the right-hand rule.
The cross product is an important operation, taking two three-dimensional vectors and producing a three-dimensional vector. It's not a product in the commutative, associative, sense, but it does produce a vector which is perpendicular to the two crossed vectors and whose length is the area of the parallelogram spanned by the them. The direction is chosen again to follow the right-hand rule.
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13 05-curl-and-divergence
1. Math 21a Curl and Divergence Spring, 2009
1 Define the operator (pronounced “del”) by
= i
∂
∂x
+ j
∂
∂y
+ k
∂
∂z
.
Notice that the gradient f (or also grad f) is just applied to f.
(a) We define the divergence of a vector field F, written div F or · F, as the dot product of
del with F. So if F = P, Q, R , then
div F = · F =
∂
∂x
,
∂
∂y
,
∂
∂z
· P, Q, R =
∂P
∂x
+
∂Q
∂y
+
∂R
∂z
.
Notice that div F is a scalar.
Find div F for each of the following vector fields:
(i) F = xy, yz, xz (ii) F = yz, xz, xy
(iii) F = x
r
, y
r
, z
r
where r = x2 + y2 + z2
(iv) F = grad f, where f is a function with
continuous second derivatives
(b) We define the curl of a vector field F, written curl F or × F, as the cross product of del
with F. So if F = P, Q, R , then
curl F = × F =
∂
∂x
,
∂
∂y
,
∂
∂z
× P, Q, R =
i j k
∂
∂x
∂
∂y
∂
∂z
P Q R
=
∂R
∂y
−
∂Q
∂z
i +
∂P
∂z
−
∂R
∂x
j +
∂Q
∂x
−
∂P
∂y
k.
Notice that curl F is a vector.
Find curl F for each of the following vector fields:
(i) F = xy, yz, xz (ii) F = yz, xz, xy
(iii) F = x
r
, y
r
, z
r
where r = x2 + y2 + z2
(iv) F = grad f, where f is a function with
continuous second derivatives
2. 2 Check the appropriate box (“Vector”, “Scalar”, or “Nonsense”) for each quantity.
Quantity Vector Scalar Nonsense
curl( f)
· ( × F)
div(curl f)
curl(curl F)
( · F)
Quantity Vector Scalar Nonsense
curl(curl f)
grad(div f)
div(grad F)
· ( f)
div(div F)
3 (a) Suppose we have a vector P, Q that we extend to a vector in space: F = P(x, y), Q(x, y), 0 .
Find curl F.
(b) When is the vector field F in part (a) conservative? Use the curl in your answer.
(c) If F = f = fx, fy, fz is conservative, then is curl F = 0? (See Problem 1(b)(iv).)
In fact, we can identify conservative vector fields with the curl:
Theorem: Let F be a vector field defined on all of R3
. If the component
functions of F all have continuous derivatives and curl F = 0, then F is a
conservative vector field.
4 Show that, if F is a vector field on R3
with components that have continuous second-order
derivatives, then div curl F = 0. (This is less useful for us right now than curl grad f = 0, but
it’s not a difficult computation.)
3. 5 We can re-write Green’s theorem in vector form (we get the formula on the left, below). The
formula on the right can be thought of as a version of Green’s theorem that uses the normal
component rather than the tangential component:
C
F · dr =
D
(curl F) · k dA and
C
F · n ds =
D
div F(x, y) dA.
(If r = x(t), y(t) , then n = y (t),−x (t)
| y (t),−x (t) |
is the outward unit normal.) For each of the following
vector fields F and paths C, compute the integrals above using these vector forms of Green’s
theorem:
(a) F = −y, x and C is the unit circle, positively oriented.
(b) F = 2x, 2y and C is the unit square (with corners at (0, 0), (1, 0), (1, 1) and (0, 1)),
positively oriented.
(While we’ll never really look at the normal version of Green’s theorem again, one of our
big integral theorems next week can be thought of as a higher-dimensional version of it.)
6 Here are sketches of a few vector fields F = P(x, y), Q(x, y), 0 (they’re drawn in the plane, but
they’re defined in all of space). Can you tell which one has zero curl? Zero divergence?
−4 4
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F = −y, x, 0
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F = y, x, 0
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F = 2x, 2y, 0
4. Curl and Divergence – Answers and Solutions
1 (a) (i) div F = x + y + z
(ii) div F = 0
(iii) div F = y2+z2
r3 + x2+z2
r3 + x2+y2
r3 = 2(x2+y2+z2)
r3 = 2
r
(iv) div F = div(grad f) = fxx + fyy + fzz. This is the Laplace operator applied to f.
(b) (i) curl F = −y, −z, −x
(ii) curl F = 0
(iii) curl F = 0
(iv) curl F = curl(grad f) = 0.
Two quick comments:
• Notice that the vector from part (ii) is actually an example of this, since F =
grad(xyz) = yz, xz, xy . The vector for part (iii) is F = grad( x2 + y2 + z2), so
it is another example as well.
• We’ll see later on in this worksheet that curl F = 0 precisely when F = grad f (when
we make some continuity assumptions about the derivatives of the components of
F.
2 Here are some answers, although half are blank as they match questions from the homework:
Quantity Vector Scalar Nonsense
curl( f) x
· ( × F) x
div(curl f) x
curl(curl F)
( · F)
Quantity Vector Scalar Nonsense
curl(curl f) x
grad(div f)
div(grad F) x
· ( f)
div(div F)
3 (a) curl F = 0, 0, ∂Q
∂x
− ∂P
∂y
= 0, 0, Qx − Py
(b) A planar vector field F = P, Q is conservative when Qx − Py = 0. This means there’s a
function f(x, y) with P = fx and Q = fy. We also get fz = 0 since f is a function of only
x and y, so F = P(x, y), Q(x, y), 0 is conservative under this same condition. From part
(a), this means that F is conservative when curl F = 0.
(c) Yep, we’ve already seen that curl grad f = 0.
4 Here’s a quick detailed computation:
div curl F = div ( × P, Q, R )
= ·
∂R
∂y
−
∂Q
∂z
i +
∂P
∂z
−
∂R
∂x
j +
∂Q
∂x
−
∂P
∂y
k
=
∂
∂x
∂R
∂y
−
∂Q
∂z
+
∂
∂y
∂P
∂z
−
∂R
∂x
+
∂
∂z
∂Q
∂x
−
∂P
∂y
=
∂2
R
∂x ∂y
−
∂2
Q
∂x ∂z
+
∂2
P
∂y ∂z
−
∂2
R
∂y ∂x
+
∂2
Q
∂z ∂x
−
∂2
P
∂z ∂y
= (Ryx − Qzx) + (Pzy − Rxy) + (Qxz − Pyz) .
5. 5 (a) We do this both ways, of course. First let’s parameterize C by r(t) = x, y = cos(t), sin(t) ,
so dx = − sin(t) dt and dy = cos(t) dt. Thus
C
F · dr =
2π
0
− sin(t), cos(t) · − sin(t), cos(t) dt =
2π
0
1 dt = 2π.
The double integral is also straightforward: writing F = −y, x, 0 as a vector field in space,
we get curl F = 0, 0, 2 . Thus, since k = 0, 0, 1 , we get
D
(curl F) · k dA =
D
2 dA = 2 · Area(D) = 2π.
The normal component version requires us to have a unit outward-pointing normal n. For
the unit circle, the unit normal at the point (x, y) is simply n = x, y . (One way to see
this is to parameterize the circle as r(t) = x(t), y(t) = cos(t), sin(t) , so by our formula n
is the unit vector in the direction y (t), −x (t) = cos(t), sin(t) . But this is a unit vector
already, and in fact it is the vector x, y .) Thus F · n = −y, x · x, y = 0, so the line
integral is zero. Note also that div F = ∂
∂x
(−y) + ∂
∂y
(x) = 0, so the double integral is also
zero.
(b) Again we do this both ways. We’ll parameterize C in four parts (all with 0 ≤ t ≤ 1):
C1 : r(t) = x, y = t, 0 C2 : r(t) = x, y = 1, t
C3 : r(t) = x, y = 1 − t, 1 C4 : r(t) = x, y = 0, 1 − t
From this we get four integrals:
C1
F · dr =
C1
2x, 2y · dx, dy =
1
0
2t, 0 · dt, 0 =
1
0
2t dt = 1
C2
F · dr =
C2
2x, 2y · dx, dy =
1
0
2, 2t · 0, dt =
1
0
2t dt = 1
C3
F · dr =
C3
2x, 2y · dx, dy =
1
0
2(1 − t), 2 · −dt, 0 =
1
0
2(t − 1) dt = −1
C4
F · dr =
C4
2x, 2y · dx, dy =
1
0
0, 2(1 − t) · 0, −dt =
1
0
2(t − 1) dt = −1.
Thus
C
F · dr =
C1
+
C2
+
C3
+
C4
= 1 + 1 − 1 − 1 = 0.
The double integral is considerably easier: writing F = 2x, 2y, 0 as a vector field in space,
we compute curl F = 0, so the integrand in the double integral is zero. Thus the double
integral is zero as well.
The normal component version requires us to have a unit outward-pointing normal n. These
are simple to find for each component (using the above parameterization):
C1 : n = −j = 0, −1 C2 : n = i = 1, 0 ,
C3 : n = j = 0, 1 , C4 : n = −i = −1, 0 .
6. Thus the integrals are all (note that ds = dt in each case)
C1
F · n ds =
1
0
2t, 0 · 0, −1 dt = 0
C2
F · n ds =
1
0
2, 2t · 1, 0 dt =
1
0
2 dt = 2
C3
F · n ds =
1
0
2(1 − t), 2 · 0, 1 dt =
1
0
2 dt = 2
C4
F · n ds =
1
0
0, 2(1 − t) · −1, 0 = 0.
Thus
C
F · n ds =
C1
+
C2
+
C3
+
C4
= 0 + 2 + 2 + 0 = 4.
The double integral is again much simpler: we compute div F = 2 + 2 = 4, so the double
integral is just 4 times the area of the square. Thus the double integral has value 4 as well.
6 The idea here is that we can do this two ways: first, we can compute the curl and divergence of
the given vector fields:
(a) div F = 0
curl F = 0, 0, 2
(b) div F = 0
curl F = 0
(c) div F = 4
curl F = 0
Thus we see that the first vector field is the only one with a non-zero curl, and that the last
vector field is similarly the only one with a non-zero divergence.
Here’s a way to see this from the graph. We’ll use the two Green’s theorems from the previous
problem:
C
F · T ds =
D
(curl F) · k dA
C
F · n ds =
D
div F dA.
(Here we’ve written the first one slightly differently, but it’s the same. Since dr = r (t) dt and
T = r (t)
|r (t)|
and ds = |r (t)| dt, we get dr = T ds.)
Let’s start with the curl and the first of Green’s theorems. Let’s integrate around a small circle
C centered at the origin. We’ll choose it so small that curl F is essentially constant on the tiny
little disk D bounded by C. By this argument, the double integral is roughly
D
(curl F) · k dA ≈
D
(curl F(0, 0, 0)) · k dA = (curl F(0, 0, 0)) · k · Area(D).
On the other hand, the line integral is the integral of F · T. This is the tangential component of
F, and in particular
F · T 0 means F and T are mostly in the same direction,
F · T 0 means F and T are mostly in opposing directions, and
7. In the case of the first sketch, it’s clear that F is mostly parallel to the tangent vector to the
small circle C, so F · T 0. Thus C
F · T ds 0, so by Green’s theorem,
(curl F(0, 0, 0)) · k 0.
The moral: the curl of F is non-zero means that there is some kind of rotation in the vector
field. We’ll see much more of this later.
We could do something similar with the divergence. Let’s cut straight to the chase: the (outward-
pointing) normal n produces a positive divergence at the origin. This gives us what we call a
source (when div F 0) at the origin; if the vector fields were pointing in we’d get a sink (and
div F 0).