The Implicit Function Theorem
We can also recall the implicit function theorem. This is less directly generalizable to manifolds, since talking about a function is effectively considering a manifold with a particular product structure: the product between the function’s domain and range.
Still, we can go back and clean up not only the statement of the implicit function theorem, but its proof, as well. And we can even extend to a different, related statement, all using the inverse function theorem for manifolds.
So, take a smooth function , where
with
. Suppose further that
has maximal rank
at a point
. If we write
for the projection onto the first
components of
, then there is some coordinate patch
of
around
so that
in that patch.
This is pretty much just like the original proof. We can clearly define to agree with
in its first
components and just to copy over the
th component for
. That is,
Then , and the Jacobian of
is
After possibly rearranging the arguments of , we may assume that the matrix in the upper-left has nonzero determinant —
has rank
at
, by assumption — and so the Jacobian of
also has nonzero determinant. By the inverse function theorem,
has a neighborhood
of
on which it’s a diffeomorphism
. Thus on
we conclude
This is basically the implicit function theorem from before. But now let’s consider what happens when . Again, we assume that
has maximal rank — this time it’s
— at a point
. If we write
for the inclusion of
into the first
components of
, then I say that there is a coordinate patch
around
so that
in a neighborhood of
.
This time, we take the product and define the function
by
Then , and the Jacobian of
at
is
Just as before, by rearranging the components of we can assume that the determinant of the matrix in the upper-left is nonzero, and thus the determinant of the whole Jacobian is nonzero. And thus
is a diffeomorphism on some neighborhood
. We let
be the image of this neighborhood, and write
. Thus on some neighborhood we conclude
Either way, the conclusion is that we can always pick local coordinates on the larger-dimensional space so that is effectively just a simple inclusion or projection with respect to those coordinates.