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Before I actually show you the
mechanics of what the curl of a
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vector field really is, let's
try to get a little
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bit of intuition.
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So here I've drawn, I'm going
to just draw a two-dimensional
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vector field.
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You can extrapolate to 3,
but when we're getting
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the intuition, it's
good to do it in 2.
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And so, let's see.
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I didn't even label
the x and y axis.
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This is x, this is y.
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So when y is relatively low,
our magnitude vector goes in
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the x direction, when it
increases a little bit, it
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gets a little bit longer.
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So as we can see, as our change
in the y-direction, as we go
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in the y-direction, the
x-component of our vectors
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get larger and larger.
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And maybe in the x-direction
they're constant, regardless
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of your level of x,
the magnitude stays.
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So for given y, the magnitude
of your x-component vector
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might stay the same.
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So I mean, this vector field
might look something like this.
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I'm just making up numbers.
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Maybe it's just, I don't
know, y squared i.
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So the magnitude of the
x-direction is just a
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function of your y-value.
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And as your y-values get bigger
and bigger, the magnitude in
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your x-direction will get
bigger and bigger, proportional
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to the square of the magnitude
of the y direction.
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But for any given x, it's
always going to be the same.
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It's only dependent on y.
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So here, even if we make
x larger, we still get
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the same magnitude.
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And remember, these are
just sample points
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on our vector field.
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But anyway.
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That's enough of just getting
the intuition behind
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that vector field.
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But let me ask you a question.
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If I were to, let's say that
this vector field shows the
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velocity of a fluid
at various points.
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And so you can view this, we're
looking down on a river, maybe.
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If I were to take a little twig
or something, and I were to
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place it in this fluid, so let
me place the twig right here.
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Let me draw my twig.
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So let's say I place a twig,
it's a funny-looking twig,
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but that's good enough.
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Let's say I place a
twig right there.
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What's going to
happen to the twig?
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Well, at this point on the
twig, the water's moving to the
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right, so it'll push this part
of the twig to the right.
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At the top of the twig, the
water is also moving to the
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right, maybe with a faster
velocity, but it's also going
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to push the top of the
twig to the right.
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But the top of the twig is
going to be being pushed to
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the right faster than the
bottom of the twig, right?
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So what's going to happen?
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The twig's going
to rotate, right?
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After, I don't know, some
period of time, the
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twig's going to look
something like this.
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The bottom will move a little
bit to the right, but the
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top will move a lot
more to the right.
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Right?
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And the whole thing would have
been shifted to the right.
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But it's going to
rotate a little bit.
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And maybe after a little bit
further, maybe it looks
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something like this.
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So you can see that because the
vectors increasing in a
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direction that is perpendicular
to our direction
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of motion, right?
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This fairly simple example,
all of the vectors point
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in the x-direction.
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But the magnitude of the
vectors increase, they increase
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perpendicular, they increase
in the y-dimension, right?
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And when this happens, when the
flow is going in the same
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direction, but it's going at a
different magnitude, you see
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that any object in it
will rotate, right?
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So let's think about that.
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So if the derivative, the
partial derivative, of this
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vector field with respect to y
is increasing or decreasing, if
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it's just changing, that means
as we increase in y, or as we
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decrease in y, the magnitude of
the x-component of our vectors,
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right, the x-direction
of our vectors changes.
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And so if you have a different
speed for different levels of
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y, as something moves in the
x-direction, it's going
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to be rotated, right?
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You could almost view it as if
there's a net torque on an
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object that sits in
the water here.
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And the ultimate would be, let
me draw another vector field,
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the ultimate would be if
I had this situation.
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Let me draw another
vector field.
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If I had this situation, where
maybe down here it's like this,
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then maybe it's like this, and
then maybe it gets really
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small, then maybe it switches
directions, up here, and then
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the vector field
goes like this.
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So you could imagine up here
that's going to the left, with
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a fairly large magnitude.
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So if you put a twig here, you
would definitely hopefully see
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that the twig, not only will it
not be shifted to the right,
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this side is going to be moved
to the left, this side is going
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to be the right, it's
going to be rotated.
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And you'll see that there's
a net torque on the twig.
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So what's the intuition there?
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All of a sudden, we care about
how much is the magnitude of a
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vector changing, not in its
direction of motion, like in
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the divergence example, but we
care how much is the magnitude
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of a vector changing as we go
perpendicular to its
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direction of motion.
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So when we learned about
dot and cross product,
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what did we learn?
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We learned that the dot product
of 2 vectors tells you how much
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2 vectors move together, and
the cross product tells you how
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much the perpendicular, it's
kind of the multiplication
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of the perpendicular
components of a vector.
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So this might give you a little
intuition of what is the curl.
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Because the curl essentially
measures what is the rotational
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effect, or I guess you could
say, what is the curl of a
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vector field at a given point?
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And you can you
can visualize it.
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You put a twig there, what
would happen to the twig?
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If the twig rotates and there's
some curl, if the magnitude
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of the rotation is larger,
then the curl is larger.
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If it rotates in the other
direction, you'll have the
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negative direction of curl.
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And so just like what we did
with torque, we now care
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about the direction.
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Because we care whether it's
going counterclockwise or
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clockwise, so we're going to
end up with a vector
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quantity, right?
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So, and all of this should
hopefully start fitting
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together at this point.
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We've been dealing
with this Dell
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vector or this, you know, we
could call this abusive
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notation, but it kind of is
intuitive, although it really
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doesn't have any meaning when
I describe it like this.
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You can kind of write it as a
vector operator, and then it
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has a little bit more meeting.
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But this Dell
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operator, we use it
a bunch of times.
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You know, if the partial
derivative of something in the
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i-direction, plus the partial
derivative, something with
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respect to y in the
j-direction, plus the partial
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derivative, well, this is if we
do it in three dimensions
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with respect to z
in the k-direction.
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When we applied it to just a
scalar or vector field, you
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know, like a three-dimensional
function, we just multiplied
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this times that scalar
function, we got the gradient.
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When we took the dot product of
this with a vector field, we
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got the divergence of
the vector field.
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And this should be a
little bit intuitive
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to you, at this point.
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Because when we, you might want
to review our original videos
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where we compared the dot
product to the cross product.
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Because the dot product
was, how much do two
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vectors move together?
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So when you're taking this Dell
operator and dotting it with a
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vector field, you're saying,
how much is the vector
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field changing, right?
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All a derivative is, a partial
derivative or a normal
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derivative, it's just
a rate of change.
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Partial derivative with respect
to x is rate of change
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in the x-direction.
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So all you're saying is, when
you're taking a dot product,
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how much is my rate of
change increasing in my
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direction of movement?
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How much is my rate of change
in the y-direction increasing
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in the y-direction?
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And so it makes sense that it
helps us with divergence.
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Because remember, if this is a
vector, and then as we increase
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this in the x-direction, the
vectors increase, we took a
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little point, and we said, oh,
at this point we're going to
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have more leaving than
entering, so we have a
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positive divergence.
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But that makes sense, also,
because as you go in the
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x-direction, the magnitudes
of the vectors increase.
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Anyway, I don't want to
confuse you too much.
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So now, the intuition, because
now we don't care about the
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rate of change along with the
direction of the vector.
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We care about the rate of
change of the magnitudes of
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the vectors perpendicular
the direction of the vector.
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So the curl, you might guess,
is equal to the cross product
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of our Dell operator
and the vector field.
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And if that was where your
intuition led you, and that
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is what your guess is,
you would be correct.
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That is the curl of
the vector field.
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And it is a measure of how much
is that field rotating, or
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maybe if you imagine an object
in the field, how much is the
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field causing something
to rotate because it's
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exerting a net torque?
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Because at different points
in the object, you have a
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different magnitude of a
field in the same direction.
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Anyway, I don't want to
confuse you too much.
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Hopefully that example I
just showed you will make
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a little bit of sense.
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Anyway, I realize I've
already pushed 9 minutes.
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In the next video, I'll
actually compute curl, and
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maybe we'll try to draw
a couple more to hit
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the intuition home.
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See you in the next video.
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