Hi.
Welcome back to recitation.
In lecture you've been learning about vector
calculus, Stokes' theorem, all sorts of cool
stuff like that, curl.
So I have a nice problem here for you.
So let F be the following vector field.
So it's the vector field whose direction is xi hat plus yj
hat plus zk hat, but in addition I want to multiply it
by rho to the n.
So this is your usual rho from spherical coordinates.
This is the square root of x squared plus y
squared plus z squared.
And n can be any number.
So it might be positive, it might be negative, it might be
0, doesn't have to be an integer.
Some number, though, it's some constant.
So what I'd like you to do is to show that for this field,
regardless of what the value of n happens to be, that it is
a gradient field.
So it is the gradient of some function.
So why don't you pause the video, have a go at that, come
back and we can work on it together.
So recall that for something to be a gradient field, what
that means--
well, first of all, that means that there is some function
that has it as the gradient, and we know a lot of other
characterizations of it.
And one of them that we know involves the curls.
So let's talk about that one.
So in order to look at the curl of this field, I'm going
to want to take partial derivatives of its components.
And so I'm going to want to take partial
derivatives of rho.
So let's just remember or recall that partial rho
partial x equals z over rho.
And similarly, partial rho partial y is y over rho.
And partial z partial--
sorry, partial rho partial z is z over rho.
So you can just check that using the fact that you know
what rho is.
Et cetera.
I'm going to write et cetera because it's the same
for the other two.
So let's call-- for shorthand--
let's call F, Mi plus Nj plus P times k.
So M, N, and P are its components.
If F is this, then we know that curl F is equal to--
what is it?
So it's P, the y partial derivative of P, minus the z
partial derivative of N, i hat, plus--
OK, so it's the z partial derivative of M minus the x
partial derivative of P, j hat, plus--
it's going to be, what's the last one?--
the x partial derivative of N, minus the y partial derivative
of M k hat.
So if this is our formula for F, then this is our formula
for the curl of F. And OK, so now we just have to compute
these various different partial derivatives in order
to see what the curl is.
And then hopefully that'll tell us
something about this field.
So let's see.
So Py.
In our case, so M is equal to rho to the little n times x.
Big N is equal to rho to the little n times y.
And big P is equal to rho to the little n times z.
So let's look at our components here.
So P sub y--
well, z is a constant with respect to y.
So this is just rho to the n.
Well, z times the y partial of rho to the n.
So that's by the chain rule, so we got n rho to the n minus
1 times y over rho times z.
So we can rewrite this as nyz rho to the n minus 2.
And similarly, so that was P sub y, so let's
look at N sub z.
So N is rho to the n times y.
So you take the z partial
derivative, so y is a constant.
So we need to look at the z partial
derivative of P to the n.
So this is, again, it's n--
sorry, I think I said P to the n.
But of course this isn't a P, this is a rho.
So it's n rho to the n minus 1 times partial rho partial z.
So that's z over rho times y.
And again, this is equal to nyz rho to the n minus 2.
OK, so P sub y, the y partial of P is nyz rho
to the n minus 2.
And the z partial of n is nyz rho to the n minus 2.
And they're the same.
So what does that mean?
So that means the first component of curl of F is 0.
So if you do a little bit more arithmetic of exactly the same
sort, you have two more components to check.
What you're going to find is that the
other ones are 0 also.
I'm not going to do out all those partial derivatives for
you, but I trust that you can compute the similar looking
partial derivatives that appear in these other two
components--
this j should have had a hat--
the other partial derivatives that appear in these
components and show that they're all also equal to 0.
So in our case, curl of F is just equal to 0 vector.
OK, great.
So what does that mean?
Well, we want to show that something is a gradient field.
So we know that we can do that.
We know that that happens precisely when its curl is 0
if it's defined on a simply connected domain.
On a simply connected region.
So we know that a function is a gradient field if it's
defined on a simply connected domain and has curl 0.
Well, let's see.
So where is this thing defined?
Where is F defined?
Well, if n is bigger than or equal to 0--
well, I guess I want strictly bigger than 0 just to be on
the safe side.
If n is positive, this is defined
everywhere and we're great.
If n is negative, then we have a problem at 0.
Because then we have division by rho.
So we don't want to divide by 0.
So if n is negative, there's a problem at the origin.
So in the worst case, F is defined
everywhere except the origin.
But that's simply connected.
Because we're in space.
If we were in the plane, this would be a different story.
But in space, just removing a point doesn't destroy simply
connectedness.
So this field F is defined everywhere, except the origin
perhaps, so we're in a simply connected region.
So when you have curl F in a simply connected region, your
field is, in fact, a gradient field.
Now I leave it as an exercise to you to come up with the
actual function, or one of the actual functions, of which
this is a gradient.
But we've just shown that because its curl is 0, and
because it's defined in a simply connected region of
space, that this field really is the gradient
field of some function.
So I'll stop there.