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so -- OK, so remember last
time,

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00:00:25 --> 00:00:32
on Tuesday we learned about the
chain rule,

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00:00:32 --> 00:00:39
and so for example we saw that
if we have a function that

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00:00:39 --> 00:00:44
depends,
sorry, on three variables,

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x,y,z,
that x,y,z themselves depend on

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00:00:50 --> 00:00:54
some variable,
t,

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00:00:54 --> 00:01:06
then you can find a formula for
df/dt by writing down wx/dx dt

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00:01:06 --> 00:01:12
wy dy/dt wz dz/dt.
And, the meaning of that

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formula is that while the change
in w is caused by changes in x,

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00:01:17 --> 00:01:21
y, and z, x,
y, and z change at rates dx/dt,

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00:01:21 --> 00:01:25
dy/dt, dz/dt.
And, this causes a function to

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change accordingly using,
well, the partial derivatives

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00:01:31 --> 00:01:37
tell you how sensitive w is to
changes in each variable.

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00:01:37 --> 00:01:45
OK, so, we are going to just
rewrite this in a new notation.

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00:01:45 --> 00:01:52
So, I'm going to rewrite this
in a more concise form as

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00:01:52 --> 00:01:59
gradient of w dot product with
velocity vector dr/dt.

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00:01:59 --> 00:02:04
So, the gradient of w is a
vector formed by putting

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00:02:04 --> 00:02:08
together all of the partial
derivatives.

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00:02:08 --> 00:02:12
OK, so it's the vector whose
components are the partials.

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00:02:12 --> 00:02:15
And, of course,
it's a vector that depends on

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00:02:15 --> 00:02:19
x, y, and z, right?
These guys depend on x, y, z.

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00:02:19 --> 00:02:22
So, it's actually one vector
for each point,

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00:02:22 --> 00:02:31
x, y, z.
You can talk about the gradient

30
00:02:31 --> 00:02:39
of w at some point,
x, y, z.

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00:02:39 --> 00:02:41
So, at each point,
it gives you a vector.

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00:02:41 --> 00:02:47
That actually is what we will
call later a vector field.

33
00:02:47 --> 00:02:59
We'll get back to that later.
And, dr/dt is just the velocity

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00:02:59 --> 00:03:07
vector dx/dt,
dy/dt, dz/dt.

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00:03:07 --> 00:03:14
OK, so the new definition for
today is the definition of the

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00:03:14 --> 00:03:18
gradient vector.
And, our goal will be to

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00:03:18 --> 00:03:21
understand a bit better,
what does this vector mean?

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00:03:21 --> 00:03:24
What does it measure?
And, what can we do with it?

39
00:03:24 --> 00:03:29
But, you see that in terms of
information content,

40
00:03:29 --> 00:03:33
it's really the same
information that's already in

41
00:03:33 --> 00:03:38
the partial derivatives,
or in the differential.

42
00:03:38 --> 00:03:43
So, yes, and I should say,
of course you can also use the

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00:03:43 --> 00:03:49
gradient and other things like
approximation formulas and so

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00:03:49 --> 00:03:52
on.
And so far, it's just notation.

45
00:03:52 --> 00:03:57
It's a way to rewrite things.
But, so here's the first cool

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00:03:57 --> 00:04:03
property of the gradient.
So, I claim that the gradient

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00:04:03 --> 00:04:11
vector is perpendicular to the
level surface corresponding to

48
00:04:11 --> 00:04:18
setting the function,
w, equal to a constant.

49
00:04:18 --> 00:04:22
OK, so if I draw a contour plot
of my function,

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00:04:22 --> 00:04:28
so, actually forget about z
because I want to draw a two

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00:04:28 --> 00:04:32
variable contour plot.
So, say I have a function of

52
00:04:32 --> 00:04:35
two variables,
x and y, then maybe it has some

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00:04:35 --> 00:04:38
contour plot.
And, I'm saying if I take the

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00:04:38 --> 00:04:42
gradient of a function at this
point, (x,y).

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00:04:42 --> 00:04:46
So, I will have a vector.
Well, if I draw that vector on

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00:04:46 --> 00:04:51
top of a contour plot,
it's going to end up being

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00:04:51 --> 00:04:54
perpendicular to the level
curve.

58
00:04:54 --> 00:04:57
Same thing if I have a function
of three variables.

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00:04:57 --> 00:04:59
Then, I can try to draw its
contour plot.

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00:04:59 --> 00:05:03
Of course, I can't really do it
because the contour plot would

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00:05:03 --> 00:05:05
be living in space with x,
y, and z.

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00:05:05 --> 00:05:09
But, it would be a bunch of
level faces, and the gradient

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vector would be a vector in
space.

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That vector is perpendicular to
the level faces.

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00:05:15 --> 00:05:24
So, let's try to see that on a
couple of examples.

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00:05:24 --> 00:05:32
So, let's do a first example.
What's the easiest case?

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00:05:32 --> 00:05:36
Let's take a linear function of
x, y, and z.

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00:05:36 --> 00:05:42
So, I will take w equals a1
times x plus a2 times y plus a3

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00:05:42 --> 00:05:47
times z.
Well, so, what's the gradient

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00:05:47 --> 00:05:53
of this function?
Well, the first component will

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be a1.
That's partial w partial x.

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00:05:58 --> 00:06:03
Then, a2, that's partial w
partial y, and a3,

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00:06:03 --> 00:06:15
partial w partial z.
Now, what is the levels of this?

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00:06:15 --> 00:06:22
Well, if I set w equal to some
constant, c, that means I look

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00:06:22 --> 00:06:27
at the points where a1x a2y a3z
equals c.

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00:06:27 --> 00:06:30
What kind of service is that?
It's a plane.

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00:06:30 --> 00:06:39
And, we know how to find a
normal vector to this plane just

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00:06:39 --> 00:06:48
by looking at the coefficients.
So, it's a plane with a normal

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00:06:48 --> 00:06:51
vector exactly this gradient.
And, in fact,

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00:06:51 --> 00:06:55
in a way, this is the only case
you need to check because of

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00:06:55 --> 00:06:58
linear approximations.
If you replace a function by

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00:06:58 --> 00:07:02
its linear approximation,
that means you will replace the

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level surfaces by their tension
planes.

84
00:07:04 --> 00:07:08
And then, you'll actually end
up in this situation.

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00:07:08 --> 00:07:09
But maybe that's not very
convincing.

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00:07:09 --> 00:07:25
So, let's do another example.
So, let's do a second example.

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00:07:25 --> 00:07:28
Let's say we look at the
function x^2 y^2.

88
00:07:28 --> 00:07:32
OK, so now it's a function of
just two variables because that

89
00:07:32 --> 00:07:36
way we'll be able to actually
draw a picture for you.

90
00:07:36 --> 00:07:40
OK, so what are the level sets
of this function?

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00:07:40 --> 00:07:44
Well, they're going to be
circles, right?

92
00:07:44 --> 00:07:54
w equals c is a circle,
x^2 y^2 = c.

93
00:07:54 --> 00:07:58
So, I should say,
maybe, sorry,

94
00:07:58 --> 00:08:08
the level curve is a circle.
So, the contour plot looks

95
00:08:08 --> 00:08:16
something like that.
Now, what's the gradient vector?

96
00:08:16 --> 00:08:20
Well, the gradient of this
function, so,

97
00:08:20 --> 00:08:26
partial w partial x is 2x.
And partial w partial y is 2y.

98
00:08:26 --> 00:08:31
So, let's say I take a point,
x comma y, and I try to draw my

99
00:08:31 --> 00:08:34
gradient vector.
So, here at x,

100
00:08:34 --> 00:08:38
y, so, I have to draw the
vector, <2x,

101
00:08:38 --> 00:08:41
2y>.
What does it look like?

102
00:08:41 --> 00:08:42
Well, it's going in that
direction.

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00:08:42 --> 00:08:49
It's parallel to the position
vector for this point.

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00:08:49 --> 00:08:51
It's actually twice the
position vector.

105
00:08:51 --> 00:08:55
So, I guess it goes more or
less like this.

106
00:08:55 --> 00:09:01
What's interesting,
too, is it is perpendicular to

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00:09:01 --> 00:09:04
this circle.
OK, so it's a general feature.

108
00:09:04 --> 00:09:10
Actually, let me show you more
examples, oops,

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00:09:10 --> 00:09:16
not the one I want.
So, I don't know if you can see

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00:09:16 --> 00:09:19
it so well.
Well, hopefully you can.

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00:09:19 --> 00:09:22
So, here I have a contour plot
of a function,

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00:09:22 --> 00:09:25
and I have a blue vector.
That's the gradient vector at

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00:09:25 --> 00:09:28
the pink point on the plot.
So, you can see,

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00:09:28 --> 00:09:32
I can move the pink point,
and the gradient vector,

115
00:09:32 --> 00:09:37
of course, changes because the
gradient depends on x and y.

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00:09:37 --> 00:09:42
But, what doesn't change is
that it's always perpendicular

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00:09:42 --> 00:09:46
to the level curves.
Anywhere I am,

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00:09:46 --> 00:09:53
my gradient stays perpendicular
to the level curve.

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00:09:53 --> 00:09:57
OK, is that convincing?
Is that visible for people who

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00:09:57 --> 00:10:05
can't see blue?
OK, so, OK, so we have a lot of

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00:10:05 --> 00:10:16
evidence, but let's try to prove
the theorem because it will be

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00:10:16 --> 00:10:22
interesting.
So, first of all,

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00:10:22 --> 00:10:30
sorry, any questions about the
statement, the example,

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00:10:30 --> 00:10:34
anything, yes?
Ah, very good question.

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00:10:34 --> 00:10:37
Does the gradient vector,
why is the gradient vector

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00:10:37 --> 00:10:40
perpendicular in one direction
rather than the other?

127
00:10:40 --> 00:10:43
So, we'll see the answer to
that in a few minutes.

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00:10:43 --> 00:10:46
But let me just tell you
immediately, to the side,

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00:10:46 --> 00:10:50
which side it's pointing to,
it's always pointing towards

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00:10:50 --> 00:10:54
higher values of a function.
OK, and we'll see in that maybe

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00:10:54 --> 00:11:03
about half an hour.
So, well, let me say actually

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00:11:03 --> 00:11:13
points towards higher values of
w.

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00:11:13 --> 00:11:24
OK, any other questions?
I don't see any questions.

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00:11:24 --> 00:11:28
OK, so let's try to prove this
theorem, at least this part of

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00:11:28 --> 00:11:30
the theorem.
We're not going to prove that

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00:11:30 --> 00:11:38
just yet.
That will come in a while.

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00:11:38 --> 00:11:44
So, well, maybe we want to
understand first what happens if

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00:11:44 --> 00:11:48
we move inside the level curve,
OK?

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00:11:48 --> 00:11:52
So, let's imagine that we are
taking a moving point that stays

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00:11:52 --> 00:11:55
on the level curve or on the
level surface.

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00:11:55 --> 00:12:00
And then, we know,
well, what happens is that the

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00:12:00 --> 00:12:03
function stays constant.
But, we can also know how

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00:12:03 --> 00:12:07
quickly the function changes
using the chain rule up there.

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00:12:07 --> 00:12:11
So, maybe the chain rule will
actually be the key to

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00:12:11 --> 00:12:15
understanding how the gradient
vector and the motion on the

146
00:12:15 --> 00:12:23
level service relate.
So, let's take a curve,

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00:12:23 --> 00:12:31
r equals r of t,
that stays inside,

148
00:12:31 --> 00:12:42
well, maybe I should say on the
level surface,

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00:12:42 --> 00:12:48
w equals c.
So, let's think about what that

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00:12:48 --> 00:12:51
means.
So, just to get you used to

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00:12:51 --> 00:12:55
this idea, I'm going to draw a
level surface of a function of

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00:12:55 --> 00:12:59
three variables.
OK, so it's a surface given by

153
00:12:59 --> 00:13:03
the equation w of x,
y, z equals some constant,

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00:13:03 --> 00:13:07
c.
And, so now I'm going to have a

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00:13:07 --> 00:13:11
point on that,
and it's going to move on that

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00:13:11 --> 00:13:15
surface.
So, I will have some parametric

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00:13:15 --> 00:13:19
curve that lives on this
surface.

158
00:13:19 --> 00:13:25
So, the question is,
what's going to happen at any

159
00:13:25 --> 00:13:29
given time?
Well, the first observation is

160
00:13:29 --> 00:13:32
that the velocity vector,
what can I say about the

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00:13:32 --> 00:13:37
velocity vector of this motion?
It's going to be tangent to the

162
00:13:37 --> 00:13:39
level surface,
right?

163
00:13:39 --> 00:13:42
If I move on a surface,
then at any point,

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00:13:42 --> 00:13:45
my velocity is tangent to the
curve.

165
00:13:45 --> 00:13:49
But, if it's tangent to the
curve, then it's also tangent to

166
00:13:49 --> 00:13:53
the surface because the curve is
inside the surface.

167
00:13:53 --> 00:13:56
So, OK, it's getting a bit
cluttered.

168
00:13:56 --> 00:13:58
Maybe I should draw a bigger
picture.

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00:13:58 --> 00:14:06
Let me do that right away here.
So, I have my level surface,

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00:14:06 --> 00:14:11
w equals c.
I have a curve on that,

171
00:14:11 --> 00:14:19
and at some point,
I'm going to have a certain

172
00:14:19 --> 00:14:28
velocity.
So, the claim is that the

173
00:14:28 --> 00:14:40
velocity, v,
equals dr/dt is tangent -- --

174
00:14:40 --> 00:14:48
to the level,
w equals c because it's tangent

175
00:14:48 --> 00:14:50
to the curve,
and the curve is inside the

176
00:14:50 --> 00:14:52
level,
OK?

177
00:14:52 --> 00:14:55
Now, what else can we say?
Well, we have,

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00:14:55 --> 00:15:03
the chain rule will tell us how
the value of w changes.

179
00:15:03 --> 00:15:12
So, by the chain rule,
we have dw/dt.

180
00:15:12 --> 00:15:20
So, the rate of change of the
value of w as I move along this

181
00:15:20 --> 00:15:28
curve is given by the dot
product between the gradient and

182
00:15:28 --> 00:15:34
the velocity vector.
And, so, well,

183
00:15:34 --> 00:15:43
maybe I can rewrite it as w dot
v, and that should be,

184
00:15:43 --> 00:15:50
well, what should it be?
What happens to the value of w

185
00:15:50 --> 00:15:54
as t changes?
Well, it stays constant because

186
00:15:54 --> 00:15:58
we are moving on a curve.
That curve might be

187
00:15:58 --> 00:16:02
complicated, but it stays always
on the level,

188
00:16:02 --> 00:16:08
w equals c.
So, it's zero because w of t

189
00:16:08 --> 00:16:18
equals c, which is a constant.
OK, is that convincing?

190
00:16:18 --> 00:16:21
OK, so now if we have a dot
product that's zero,

191
00:16:21 --> 00:16:25
that tells us that these two
guys are perpendicular.

192
00:16:25 --> 00:16:37
So -- So if the gradient vector
is perpendicular to v,

193
00:16:37 --> 00:16:44
OK, that's a good start.
We know that the gradient is

194
00:16:44 --> 00:16:48
perpendicular to this vector
tangent that's tangent to the

195
00:16:48 --> 00:16:51
level surface.
What about other vectors

196
00:16:51 --> 00:16:55
tangent to the level surface?
Well, in fact,

197
00:16:55 --> 00:17:00
I could use any curve drawn on
the level of w equals c.

198
00:17:00 --> 00:17:03
So, I could move,
really, any way I wanted on

199
00:17:03 --> 00:17:06
that surface.
In particular,

200
00:17:06 --> 00:17:11
I claim that I could have
chosen my velocity vector to be

201
00:17:11 --> 00:17:15
any vector tangent to the
surface.

202
00:17:15 --> 00:17:22
OK, so let's write this.
So this is true for any curve,

203
00:17:22 --> 00:17:30
or, I'll say for any motion on
the level surface,

204
00:17:30 --> 00:17:40
w equals c.
So that means v can be any

205
00:17:40 --> 00:17:53
vector tangent to the surface
tangent to the level.

206
00:17:53 --> 00:18:01
See, for example,
OK, let me draw one more

207
00:18:01 --> 00:18:06
picture.
OK, so I have my level surface.

208
00:18:06 --> 00:18:09
So, I'm drawing more and more
levels, and they never quite

209
00:18:09 --> 00:18:12
look the same.
But I have a point.

210
00:18:12 --> 00:18:16
And, at this point,
I have the tangent plane to the

211
00:18:16 --> 00:18:24
level surface.
OK, so this is tangent plane to

212
00:18:24 --> 00:18:30
the level.
Then, if I choose any vector in

213
00:18:30 --> 00:18:35
that tangent plane.
Let's say I choose the one that

214
00:18:35 --> 00:18:39
goes in that direction.
Then, I can actually find a

215
00:18:39 --> 00:18:42
curve that goes in that
direction, and stays on the

216
00:18:42 --> 00:18:45
level.
So, here, that would be a curve

217
00:18:45 --> 00:18:50
that somehow goes from the right
to the left, and of course it

218
00:18:50 --> 00:18:53
has to end up going up or
something like that.

219
00:18:53 --> 00:19:05
OK, so given any vector tangent
-- -- let's call that vector v

220
00:19:05 --> 00:19:14
tangent to the level,
we get that the gradient is

221
00:19:14 --> 00:19:20
perpendicular to v.
So, if the gradient is

222
00:19:20 --> 00:19:24
perpendicular to this vector
tangent to this curve,

223
00:19:24 --> 00:19:28
but also to any vector,
I can draw that tangent to my

224
00:19:28 --> 00:19:29
surface.
So, what does that mean?

225
00:19:29 --> 00:19:34
Well, that means the gradient
is actually perpendicular to the

226
00:19:34 --> 00:19:38
tangent plane or to the surface
at this point.

227
00:19:38 --> 00:19:43
So, the gradient is
perpendicular.

228
00:19:43 --> 00:20:02
 
 

229
00:20:02 --> 00:20:04
And, well, here,
I've illustrated things with a

230
00:20:04 --> 00:20:06
three-dimensional example,
but really it works the same if

231
00:20:06 --> 00:20:10
you have only two variables.
Then you have a level curve

232
00:20:10 --> 00:20:13
that has a tangent line,
and the gradient is

233
00:20:13 --> 00:20:23
perpendicular to that line.
OK, any questions?

234
00:20:23 --> 00:20:36
No?
OK, so, let's see.

235
00:20:36 --> 00:20:39
That's actually pretty neat
because there is a nice

236
00:20:39 --> 00:20:43
application of this,
which is to try to figure out, 

237
00:20:43 --> 00:20:44
now we know,
actually, how to find the

238
00:20:44 --> 00:20:46
tangent plane to anything,
pretty much.

239
00:20:46 --> 00:21:13
 
 

240
00:21:13 --> 00:21:19
OK, so let's see.
So, let's say that,

241
00:21:19 --> 00:21:27
for example,
I want to find -- -- the

242
00:21:27 --> 00:21:42
tangent plane -- -- to the
surface with equation,

243
00:21:42 --> 00:21:50
let's say, x^2 y^2-z^2 = 4 at
the point (2,1,

244
00:21:50 --> 00:22:01
1).
Let me write that.

245
00:22:01 --> 00:22:06
So, how do we do that?
Well, one way that we already

246
00:22:06 --> 00:22:09
know,
if we solve this for z, 

247
00:22:09 --> 00:22:12
so we can write z equals a
function of x and y,

248
00:22:12 --> 00:22:16
then we know tangent plane
approximation for the graph of a

249
00:22:16 --> 00:22:19
function,
z equals some function of x and

250
00:22:19 --> 00:22:21
y.
But, that doesn't look like

251
00:22:21 --> 00:22:24
it's the best way to do it.
OK, the best way to it,

252
00:22:24 --> 00:22:27
now that we have the gradient
vector, is actually to directly

253
00:22:27 --> 00:22:30
say, oh, we know the normal
vector to this plane.

254
00:22:30 --> 00:22:35
The normal vector will just be
the gradient.

255
00:22:35 --> 00:22:40
Oh, I think I have a cool
picture to show.

256
00:22:40 --> 00:22:42
OK, so that's what it looks
like.

257
00:22:42 --> 00:22:49
OK, so here you have the
surface x2 y2-z2 equals four.

258
00:22:49 --> 00:22:52
That's called a hyperboloid
because it looks like when you

259
00:22:52 --> 00:22:55
get when you spin a hyperbola
around an axis.

260
00:22:55 --> 00:23:00
And, here's a tangent plane at
the given point.

261
00:23:00 --> 00:23:02
So, it doesn't look very
tangent because it crosses the

262
00:23:02 --> 00:23:04
surface.
But, it's really, 

263
00:23:04 --> 00:23:08
if you think about it, 
you will see it's really the

264
00:23:08 --> 00:23:12
plane that's approximating the
surface in the best way that you

265
00:23:12 --> 00:23:18
can at this given point.
It is really the tangent plane.

266
00:23:18 --> 00:23:27
So, how do we find this plane?
Well, you can plot it on a

267
00:23:27 --> 00:23:30
computer.
That's not exactly how you

268
00:23:30 --> 00:23:33
would look for it in the first
place.

269
00:23:33 --> 00:23:38
So, the way to do it is that we
compute the gradient.

270
00:23:38 --> 00:23:43
So, a gradient of what?
Well, a gradient of this

271
00:23:43 --> 00:23:49
function.
OK, so I should say,

272
00:23:49 --> 00:23:56
this is the level set,
w equals four,

273
00:23:56 --> 00:24:07
where w equals x^2 y^2 - z^2.
And so, we know that the

274
00:24:07 --> 00:24:14
gradient of this,
well, what is it?

275
00:24:14 --> 00:24:22
2x, then 2y,
and then negative 2z.

276
00:24:22 --> 00:24:27
So, at this given point,
I guess we are at x equals two.

277
00:24:27 --> 00:24:29
So, that's four.
And then, y and z are one.

278
00:24:29 --> 00:24:37
So, two, negative two.
OK, and that's going to be the

279
00:24:37 --> 00:24:44
normal vector to the surface or
to the tangent plane.

280
00:24:44 --> 00:24:47
That's one way to define the
tangent plane.

281
00:24:47 --> 00:24:50
All right, it has the same
normal vector as the surface.

282
00:24:50 --> 00:24:52
That's one way to define the
normal vector to the surface,

283
00:24:52 --> 00:24:56
if you prefer.
Being perpendicular to the

284
00:24:56 --> 00:25:01
surface means that you are
perpendicular to its tangent

285
00:25:01 --> 00:25:05
plane.
OK, so the equation is,

286
00:25:05 --> 00:25:12
well, 4x 2y-2z equals
something, where something is,

287
00:25:12 --> 00:25:19
well, we should just plug in
that point.

288
00:25:19 --> 00:25:26
We'll get eight plus two minus
two looks like we'll get eight.

289
00:25:26 --> 00:25:29
And, of course,
we could simplify dividing

290
00:25:29 --> 00:25:32
everything by two,
but it's not very important

291
00:25:32 --> 00:25:34
here.
OK, so now if you have a

292
00:25:34 --> 00:25:36
surface given by an evil
equation,

293
00:25:36 --> 00:25:40
and a point on the surface, 
well, you know how to find the

294
00:25:40 --> 00:25:44
tangent plane to the surface at
that point.

295
00:25:44 --> 00:25:52
OK, any questions?
No.

296
00:25:52 --> 00:26:00
OK, let me give just another
reason why, another way that we

297
00:26:00 --> 00:26:04
could have seen this.
So, I claim,

298
00:26:04 --> 00:26:07
in fact, we could have done
this without the gradient,

299
00:26:07 --> 00:26:09
or using the gradient in a
somehow disguised way.

300
00:26:09 --> 00:26:18
So, here's another way.
So, the other way to do it

301
00:26:18 --> 00:26:22
would be to start with a
differential,

302
00:26:22 --> 00:26:26
OK?
dw, while it's pretty much the

303
00:26:26 --> 00:26:31
same content,
but let me write it as a

304
00:26:31 --> 00:26:35
differential,
dw is 2xdx 2ydy-2zdz.

305
00:26:35 --> 00:26:44
So, at a given point,
at (2,1, 1),

306
00:26:44 --> 00:26:52
this is 4dx 2dy-2dz.
Now, if we want to change this

307
00:26:52 --> 00:26:56
into an approximation formula,
we can.

308
00:26:56 --> 00:27:07
We know that the change in w is
approximately equal to 4 delta x

309
00:27:07 --> 00:27:15
2 delta y - 2 delta z.
OK, so when do we stay on the

310
00:27:15 --> 00:27:19
level surface?
Well, we stay on the level

311
00:27:19 --> 00:27:24
surface when w doesn't change,
so, when this becomes zero,

312
00:27:24 --> 00:27:25
OK?
Now, what does this

313
00:27:25 --> 00:27:28
approximation sign mean?
Well, it means for small

314
00:27:28 --> 00:27:31
changes in x,
y, z, this guy will be close to

315
00:27:31 --> 00:27:33
that guy.
It also means something else.

316
00:27:33 --> 00:27:36
Remember, these approximation
formulas, they are linear

317
00:27:36 --> 00:27:39
approximations.
They mean that we replace the

318
00:27:39 --> 00:27:43
function, actually,
by some closest linear formula

319
00:27:43 --> 00:27:47
that will be nearby.
And so, in particular, 

320
00:27:47 --> 00:27:52
if we set this equal to zero
instead of approximately zero,

321
00:27:52 --> 00:27:56
it means we'll actually be
moving on the tangent plane to

322
00:27:56 --> 00:27:59
the level set.
If you want strict equalities

323
00:27:59 --> 00:28:03
in approximations means that we
replace the function by its

324
00:28:03 --> 00:28:04
tangent approximation.

325
00:28:04 --> 00:28:37

326
00:28:37 --> 00:28:44
So -- [APPLAUSE] OK, 
so the level corresponds to

327
00:28:44 --> 00:28:53
delta w equals zero,
and its tangent plane

328
00:28:53 --> 00:29:03
corresponds to four delta x plus
two delta y minus two delta z

329
00:29:03 --> 00:29:08
equals zero.
That's what I'm trying to say,

330
00:29:08 --> 00:29:10
basically.
And, what's delta x?

331
00:29:10 --> 00:29:12
Well, that means it's the
change in x.

332
00:29:12 --> 00:29:15
So, what's the change in x here?
That means, well,

333
00:29:15 --> 00:29:19
we started with x equals two,
and we moved to some other

334
00:29:19 --> 00:29:25
value, x.
So, that's actually x- 2, right?

335
00:29:25 --> 00:29:28
That's how much x has changed
compared to 2.

336
00:29:28 --> 00:29:37
And, two times (y - 1) minus
two times z - 1 = 0.

337
00:29:37 --> 00:29:42
That's the equation of a
tangent plane.

338
00:29:42 --> 00:29:46
It's the same equation as the
one over there.

339
00:29:46 --> 00:29:48
These are just two different
methods to get it.

340
00:29:48 --> 00:29:52
OK, so this one explains to you
what's going on in terms of

341
00:29:52 --> 00:29:57
approximation formulas.
This one goes right away,

342
00:29:57 --> 00:30:02
by using the gradient factor.
So, in a way,

343
00:30:02 --> 00:30:06
with this one,
you don't have to think nearly

344
00:30:06 --> 00:30:11
as much.
But, you can use either one.

345
00:30:11 --> 00:30:17
OK, questions?
No?

346
00:30:17 --> 00:30:23
OK, so let's move on to new
topic, which is another

347
00:30:23 --> 00:30:30
application of a gradient
vector, and that is directional

348
00:30:30 --> 00:30:32
derivatives.

349
00:30:32 --> 00:30:44

350
00:30:44 --> 00:30:52
OK, so let's say that we have a
function of two variables,

351
00:30:52 --> 00:30:56
x and y.
Well, we know how to compute

352
00:30:56 --> 00:31:02
partial w over partial x or
partial w over partial y,

353
00:31:02 --> 00:31:07
which measure how w changes if
I move in the direction of the x

354
00:31:07 --> 00:31:10
axis or in the direction of the
y axis.

355
00:31:10 --> 00:31:13
So, what about moving in other
directions?

356
00:31:13 --> 00:31:16
Well, of course,
we've seen other approximation

357
00:31:16 --> 00:31:18
formulas and so on.
But, we can still ask,

358
00:31:18 --> 00:31:21
is there a derivative in every
direction?

359
00:31:21 --> 00:31:25
And that's basically,
yes, that's the directional

360
00:31:25 --> 00:31:30
derivative.
OK, so these are derivatives in

361
00:31:30 --> 00:31:40
the direction of I hat or j hat,
the vectors that go along the x

362
00:31:40 --> 00:31:50
or the y axis.
So, what if we move in another

363
00:31:50 --> 00:32:01
direction, let's say,
the direction of some unit

364
00:32:01 --> 00:32:09
vector, let's call it u .
OK, so if I give you a unit

365
00:32:09 --> 00:32:13
vector, you can ask yourself,
if I move in the direction,

366
00:32:13 --> 00:32:16
how quickly will my function
change?

367
00:32:16 --> 00:32:29
So -- So, let's look at the
straight trajectory.

368
00:32:29 --> 00:32:34
What this should mean is I
start at some value,

369
00:32:34 --> 00:32:37
x, y, and there I have my
vector u.

370
00:32:37 --> 00:32:41
And, I'm going to move in a
straight line in the direction

371
00:32:41 --> 00:32:46
of u.
And, I have the graph of my

372
00:32:46 --> 00:32:54
function -- -- and I'm asking
myself how quickly does the

373
00:32:54 --> 00:33:02
value change when I move on the
graph in that direction?

374
00:33:02 --> 00:33:10
OK, so let's look at a straight
line trajectory So,

375
00:33:10 --> 00:33:18
we have a position vector,
r, that will depend on some

376
00:33:18 --> 00:33:26
parameter which I will call s.
You'll see why very soon,

377
00:33:26 --> 00:33:30
in such a way that the
derivative is this given unit

378
00:33:30 --> 00:33:33
vector u hat.
So, why do I use s for my

379
00:33:33 --> 00:33:36
parameter rather than t.
Well, it's a convention.

380
00:33:36 --> 00:33:41
I'm moving at unit speed along
this line.

381
00:33:41 --> 00:33:45
So that means that actually,
I'm parameterizing things by

382
00:33:45 --> 00:33:48
the distance that I've traveled
along a curve,

383
00:33:48 --> 00:33:54
sorry, along this line.
So, here it's called s in the

384
00:33:54 --> 00:33:59
sense of arc length.
Actually, it's not really an

385
00:33:59 --> 00:34:06
arc because it's a straight
line, so it's the distance along

386
00:34:06 --> 00:34:09
the line.
OK, so because we are

387
00:34:09 --> 00:34:15
parameterizing by distance,
we are just using s as a

388
00:34:15 --> 00:34:21
convention just to distinguish
it from other situations.

389
00:34:21 --> 00:34:27
And, so, now,
the question will be,

390
00:34:27 --> 00:34:32
what is dw/ds?
What's the rate of change of w

391
00:34:32 --> 00:34:36
when I move like that?
Well, of course we know the

392
00:34:36 --> 00:34:40
answer because that's a special
case of the chain rule.

393
00:34:40 --> 00:34:44
So, that's how we will actually
compute it.

394
00:34:44 --> 00:34:49
But, in terms of what it means, 
it really means we are asking

395
00:34:49 --> 00:34:51
ourselves,
we start at a point and we

396
00:34:51 --> 00:34:54
change the variables in a
certain direction,

397
00:34:54 --> 00:34:57
which is not necessarily the x
or the y direction,

398
00:34:57 --> 00:35:01
but really any direction.
And then, what's the derivative

399
00:35:01 --> 00:35:07
in that direction?
OK, does that make sense as a

400
00:35:07 --> 00:35:08
concept?
Kind of?

401
00:35:08 --> 00:35:10
I see some faces that are not
completely convinced.

402
00:35:10 --> 00:35:14
So, maybe you should show more
pictures.

403
00:35:14 --> 00:35:21
Well, let me first write down a
bit more and show you something.

404
00:35:21 --> 00:35:40
 
 

405
00:35:40 --> 00:35:45
So I just want to give you the
actual definition.

406
00:35:45 --> 00:35:50
Sorry, first of all in case you
wonder what this is all about,

407
00:35:50 --> 00:35:55
so let's say the components of
our unit vector are two numbers,

408
00:35:55 --> 00:36:00
a and b.
Then, it means we'll move along

409
00:36:00 --> 00:36:05
the line x of s equals some
initial value,

410
00:36:05 --> 00:36:09
the point where we are actually
at the directional derivative

411
00:36:09 --> 00:36:13
plus s times a,
or I meant to say plus a times

412
00:36:13 --> 00:36:19
s.
And, y of s equals y0 bs.

413
00:36:19 --> 00:36:38
And then, we plug that into w.
And then we take the derivative.

414
00:36:38 --> 00:36:45
So, we have a notation for that
which is going to be dw/ds with

415
00:36:45 --> 00:36:53
a subscript in the direction of
u to indicate in which direction

416
00:36:53 --> 00:37:03
we are actually going to move.
And, that's called the

417
00:37:03 --> 00:37:17
directional derivative -- -- in
the direction of u.

418
00:37:17 --> 00:37:28
OK, so, let's see what it means
geometrically.

419
00:37:28 --> 00:37:33
So, remember, 
we've seen things about partial

420
00:37:33 --> 00:37:36
derivatives,
and we see that the partial

421
00:37:36 --> 00:37:41
derivatives are the slopes of
slices of the graph by vertical

422
00:37:41 --> 00:37:45
planes that are parallel to the
x or the y directions.

423
00:37:45 --> 00:37:48
OK, so, if I have a point,
at any point,

424
00:37:48 --> 00:37:52
I can slice the graph of my
function by two planes,

425
00:37:52 --> 00:37:57
one that's going along the x,
one along the y direction.

426
00:37:57 --> 00:38:02
And then, I can look at the
slices of the graph.

427
00:38:02 --> 00:38:04
Let me see if I can use that
thing.

428
00:38:04 --> 00:38:07
So, we can look at the slices
of the graph that are drawn

429
00:38:07 --> 00:38:10
here.
In fact, we look at the tangent

430
00:38:10 --> 00:38:14
lines to the slices,
and we look at the slope and

431
00:38:14 --> 00:38:17
that gives us the partial
derivatives in case you are on

432
00:38:17 --> 00:38:21
that side and want to see also
the pointer that was here.

433
00:38:21 --> 00:38:26
So, now, similarly,
the directional derivative

434
00:38:26 --> 00:38:31
means, actually,
we'll be slicing our graph by

435
00:38:31 --> 00:38:37
the vertical plane.
It's not really colorful,

436
00:38:37 --> 00:38:43
something more colorful.
We'll be slicing things by a

437
00:38:43 --> 00:38:46
plane that is now in the
direction of this vector,

438
00:38:46 --> 00:38:51
u, and we'll be looking at the
slope of the slice of the graph.

439
00:38:51 --> 00:38:57
So, what that looks like here,
so that's the same applet the

440
00:38:57 --> 00:39:03
way that you've used on your
problem set in case you are

441
00:39:03 --> 00:39:08
wondering.
So, now, I'm picking a point on

442
00:39:08 --> 00:39:12
the contour plot.
And, at that point,

443
00:39:12 --> 00:39:15
I slice the graph.
So, here I'm starting by

444
00:39:15 --> 00:39:17
slicing in the direction of the
x axis.

445
00:39:17 --> 00:39:20
So, in fact,
what I'm measuring here by the

446
00:39:20 --> 00:39:24
slope of the slice is the
partial in the x direction.

447
00:39:24 --> 00:39:28
It's really partial f partial
x, which is also the directional

448
00:39:28 --> 00:39:31
derivative in the direction of
i.

449
00:39:31 --> 00:39:37
And now, if I rotate the slice,
then I have all of these

450
00:39:37 --> 00:39:40
planes.
So, you see at the bottom left,

451
00:39:40 --> 00:39:42
I have the direction in which
I'm going.

452
00:39:42 --> 00:39:44
There's this,
like, rotating line that tells

453
00:39:44 --> 00:39:47
you in which direction I'm going
to be moving.

454
00:39:47 --> 00:39:49
And for each direction,
I have a plane.

455
00:39:49 --> 00:39:52
And, when I slice by that
plane, I will get,

456
00:39:52 --> 00:39:56
so I have this direction here
going maybe to the southwest.

457
00:39:56 --> 00:40:00
So, that gives me a slice of my
graph by a vertical plane,

458
00:40:00 --> 00:40:03
and the slice has a certain
slope.

459
00:40:03 --> 00:40:08
And, the slope is going to be
the directional derivative in

460
00:40:08 --> 00:40:14
that direction.
OK, I think that's as graphic

461
00:40:14 --> 00:40:22
as I can get.
OK, any questions about that?

462
00:40:22 --> 00:40:33
No?
OK, so let's see how we compute

463
00:40:33 --> 00:40:41
that guy.
So, let me just write again

464
00:40:41 --> 00:40:49
just in case you want to,
in case you didn't hear me it's

465
00:40:49 --> 00:40:58
the slope of the slice of the
graph by a vertical plane -- --

466
00:40:58 --> 00:41:03
that contains the given
direction,

467
00:41:03 --> 00:41:06
that's parallel to the
direction, u.

468
00:41:06 --> 00:41:11
So, how do we compute it?
Well, we can use the chain rule.

469
00:41:11 --> 00:41:22
The chain rule implies that
dw/ds is actually the gradient

470
00:41:22 --> 00:41:31
of w dot product with the
velocity vector dr/ds.

471
00:41:31 --> 00:41:35
But, remember we say that we
are going to be moving at unit

472
00:41:35 --> 00:41:39
speed in the direction of u.
So, in fact,

473
00:41:39 --> 00:41:50
that's just gradient w dot
product with the unit vector u.

474
00:41:50 --> 00:41:57
OK, so the formula that we
remember is really dw/ds in the

475
00:41:57 --> 00:42:03
direction of u is gradient w dot
product of u.

476
00:42:03 --> 00:42:13
And, maybe I should also say in
words, this is the component of

477
00:42:13 --> 00:42:19
the gradient in the direction of
u.

478
00:42:19 --> 00:42:21
And, maybe that makes more
sense.

479
00:42:21 --> 00:42:25
So, for example,
the directional derivative in

480
00:42:25 --> 00:42:29
the direction of I hat is the
component along the x axes.

481
00:42:29 --> 00:42:32
That's the same as,
indeed, the partial derivatives

482
00:42:32 --> 00:42:40
in the x direction.
Things make sense.

483
00:42:40 --> 00:42:50
dw/ds in the direction of I hat
is, sorry, gradient w dot I hat,

484
00:42:50 --> 00:42:59
which is wx,maybe I should
write, partial w of partial x.

485
00:42:59 --> 00:43:09
OK, now, so that's basically
what we need to know to compute

486
00:43:09 --> 00:43:12
these guys.
So now, let's go back to the

487
00:43:12 --> 00:43:16
gradient and see what this tells
us about the gradient.

488
00:43:16 --> 00:43:42
 
 

489
00:43:42 --> 00:43:51
[APPLAUSE]
I see you guys are having fun.

490
00:43:51 --> 00:43:54
OK, OK, let's do a little bit
of geometry here.

491
00:43:54 --> 00:44:00
That should calm you down.
So, we said dw/ds in the

492
00:44:00 --> 00:44:04
direction of u is gradient w dot
u.

493
00:44:04 --> 00:44:11
That's the same as the length
of gradient w times the length

494
00:44:11 --> 00:44:15
of u.
Well, that happens to be one

495
00:44:15 --> 00:44:23
because we are taking the unit
vector times the cosine of the

496
00:44:23 --> 00:44:30
angle between the gradient and
the given unit vector,

497
00:44:30 --> 00:44:36
u, so, have this angle, theta.
OK, that's another way of

498
00:44:36 --> 00:44:39
saying we are taking the
component of a gradient in the

499
00:44:39 --> 00:44:43
direction of u.
But now, what does that tell us?

500
00:44:43 --> 00:44:46
Well, 
let's try to figure out in

501
00:44:46 --> 00:44:50
which directions w changes the
fastest,

502
00:44:50 --> 00:44:54
in which direction it increases
the most or decreases the most,

503
00:44:54 --> 00:45:03
or doesn't actually change.
So, when is this going to be

504
00:45:03 --> 00:45:05
the largest?
If I fix a point,

505
00:45:05 --> 00:45:09
if I set a point,
then the gradient vector at

506
00:45:09 --> 00:45:12
that point is given to me.
But, the question is,

507
00:45:12 --> 00:45:15
in which direction does it
change the most quickly?

508
00:45:15 --> 00:45:19
Well, what I can change is the
direction, and this will be the

509
00:45:19 --> 00:45:25
largest when the cosine is one.
So, this is largest when the

510
00:45:25 --> 00:45:33
cosine of the angle is one.
That means the angle is zero.

511
00:45:33 --> 00:45:40
That means u is actually in the
direction of the gradient.

512
00:45:40 --> 00:45:42
OK, so that's a new way to
think about the direction of a

513
00:45:42 --> 00:45:47
gradient.
The gradient is the direction

514
00:45:47 --> 00:45:57
in which the function increases
the most quickly at that point.

515
00:45:57 --> 00:46:08
So, the direction of gradient w
is the direction of fastest

516
00:46:08 --> 00:46:15
increase of w at the given
point.

517
00:46:15 --> 00:46:24
And, what is the magnitude of w?
Well, it's actually the

518
00:46:24 --> 00:46:33
directional derivative in that
direction.

519
00:46:33 --> 00:46:37
OK, so if I go in that
direction, which gives me the

520
00:46:37 --> 00:46:40
fastest increase,
then the corresponding slope

521
00:46:40 --> 00:46:44
will be the length of the
gradient.

522
00:46:44 --> 00:46:51
And, with the direction of the
fastest decrease?

523
00:46:51 --> 00:46:53
It's going in the opposite
direction, right?

524
00:46:53 --> 00:46:55
I mean, if you are on a
mountain, and you know that you

525
00:46:55 --> 00:46:57
are facing the mountain,
that's the direction of fastest

526
00:46:57 --> 00:46:59
increase.
The direction of fastest

527
00:46:59 --> 00:47:01
decrease is behind you straight
down.

528
00:47:01 --> 00:47:11
OK, so, the minimal value of
dw/ds is achieved when cosine of

529
00:47:11 --> 00:47:18
theta is minus one.
That means theta equals 180�.

530
00:47:18 --> 00:47:27
That means u is in the
direction of minus the gradient.

531
00:47:27 --> 00:47:30
It points opposite to the
gradient.

532
00:47:30 --> 00:47:43
And, finally,
when do we have dw/ds equals

533
00:47:43 --> 00:47:48
zero?
So, in which direction does the

534
00:47:48 --> 00:47:52
function not change?
Well, we have two answers to

535
00:47:52 --> 00:47:54
that.
One is to just use the formula.

536
00:47:54 --> 00:47:58
So, that's one cosine theta
equals zero.

537
00:47:58 --> 00:48:03
That means theta equals 90 degrees.
That means that u is

538
00:48:03 --> 00:48:08
perpendicular to the gradient.
The other way to think about

539
00:48:08 --> 00:48:11
it, the direction in which the
value doesn't change is a

540
00:48:11 --> 00:48:14
direction that's tangent to the
level surface.

541
00:48:14 --> 00:48:18
If we are not changing a,
it means we are moving along

542
00:48:18 --> 00:48:24
the level.
And, that's the same thing --

543
00:48:24 --> 00:48:30
-- as being tangent to the
level.

544
00:48:30 --> 00:48:36
So, let me just show that on
the picture here.

545
00:48:36 --> 00:48:39
So, if actually show you the
gradient, you can't really see

546
00:48:39 --> 00:48:41
it here.
I need to move it a bit.

547
00:48:41 --> 00:48:44
So, the gradient here is
pointing straight up at the

548
00:48:44 --> 00:48:50
point that I have chosen.
Now, if I choose a slice that's

549
00:48:50 --> 00:48:52
perpendicular,
and a direction that's

550
00:48:52 --> 00:48:55
perpendicular to the gradient,
so that's actually tangent to

551
00:48:55 --> 00:48:57
the level curve,
then you see that my slice is

552
00:48:57 --> 00:49:00
flat.
I don't actually have any slop.

553
00:49:00 --> 00:49:04
The directional derivative in a
direction that's perpendicular

554
00:49:04 --> 00:49:06
to the gradient is basically
zero.

555
00:49:06 --> 00:49:08
Now, if I rotate,
then the slope sort of

556
00:49:08 --> 00:49:11
increases, increases,
increases, and it becomes the

557
00:49:11 --> 00:49:14
largest when I'm going in the
direction of a gradient.

558
00:49:14 --> 00:49:17
So, here, I have,
actually, a pretty big slope.

559
00:49:17 --> 00:49:20
And now, if I keep rotating,
then the slope will decrease

560
00:49:20 --> 00:49:22
again.
Then it becomes zero when I

561
00:49:22 --> 00:49:25
perpendicular,
and then it becomes negative.

562
00:49:25 --> 00:49:29
It's the most negative when I
pointing away from the gradient

563
00:49:29 --> 00:49:33
and then becomes zero again when
I'm back perpendicular.

564
00:49:33 --> 00:49:38
OK, so for example, 
if I give you a contour plot, 

565
00:49:38 --> 00:49:41
and I ask you to draw the
direction of the gradient

566
00:49:41 --> 00:49:43
vector,
well, at this point, 

567
00:49:43 --> 00:49:46
for example,
you would look at the picture.

568
00:49:46 --> 00:49:49
The gradient vector would be
going perpendicular to the

569
00:49:49 --> 00:49:52
level.
And, it would be going towards

570
00:49:52 --> 00:49:55
higher values of a function.
I don't know if you can see the

571
00:49:55 --> 00:49:57
labels, but the thing in the
middle is a minimum.

572
00:49:57 --> 00:50:03
So, it will actually be
pointing in this kind of

573
00:50:03 --> 00:50:08
direction.
OK, so that's it for today.

574
00:50:08 --> 00:50:10