Continously differentiable f: R^n -> R^m not 1-1?

In summary, a continuously differentiable function F: Rn → Rm is not 1-1 when n>m. My course is over with now, but I never could figure out this question. It's pretty much been haunting me ever since, and the internet has not given me a proof that convinces me. My problem is determining why: the function is not constant. Anyone who is familiar with the subject, I would appreciate any feedback.
  • #1
ryou00730
29
0
Continously differentiable f: R^n --> R^m not 1-1?

My course is over with now, but I never could figure out this question. It's pretty much been haunting me ever since, and the internet has not given me a proof that convinces me. My problem is determining why:
A continuously di fferentiable function F: Rn → Rm is not 1-1 when n>m. I can understand why it would be true, I just can't seem to convincingly prove it. Anyone who is familiar with the subject, I would appreciate any feedback.
 
Physics news on Phys.org
  • #2


Look at the critical values of the map and use Sard's theorem to see what the image is like.

Re a continuous bijection alone, look at the issue of invariance of domain.
 
  • #3


ryou00730 said:
A continuously di fferentiable function F: Rn → Rm is not 1-1 when n>m. I can understand why it would be true, I just can't seem to convincingly prove it. .

Here are some ideas:

- Take the case of a map from the plane into the real line. At each point of the plane the Jacobian of the map,F, must have a non-trivial kernel. This is because the Jacobian is a linear map from R2 to R1,

F must be constant on any curve whose tangent lies if the kernel of the Jacoboan. If the Jacobian of F is not identically zero at a point - then it is not identically zero in a neighborhood of that point because it is continuous. Also,there is a well defined continuous field of directions(why?) in that neighborhood where the Jacobian of F is zero. Integrate this vector field of zero directions to get curves along which F is constant at every point in the neighborhood.
 
  • #4


In the case of n=2, m=1, the image has measure zero in R^1, and, by continuity+connectedness of R^n+Sard's, the image f(R^n) is a connected subset of R^1 of measure-zero, which is... Then generalize for other n>m.

For invariance of domain, use the fact that the inclusion map from R^m to R^n is a continuous injection, then compose.
 
  • #5


Bacle, I think you're confused. We're discussing the case where n>m, not n<m. Sard's theorem doesn't tell us anything useful about the image. Indeed, the image can even be all of R^m (consider the natural projection from R^2 to R^1).

We can use invariance of domain to prove the theorem. Indeed, suppose [itex]f:\mathbb{R}^n \rightarrow \mathbb{R}^m[/itex] is a continuous injection. Look at the restriction of f to some precompact open set [itex]U[/itex]. Since [itex]\overline{U}[/itex] is compact and [itex]\mathbb{R}^m[/itex] is Hausdorff, [itex]f|_{\overline{U}}[/itex] is a homeomorphism onto its image, and thus so is [itex]f|_{U}[/itex]. This contradicts invariance of domain.
 
  • #6


Ouch, yes. Next time I'll try to read the actual question. I intended the opposite direction.
 
  • #7


I realized I used the wrong theorem for this direction; it is Sard's in one direction and the inverse-value theorem+ Invariance of domain, in the opposite direction.

So, your function can clearly not be constant, so that df_x is not identically zero, so that there exists a local homeomorphism between an open set W in R^n, with an open set f(W) in R^m.
 
  • #8


Inverse function theorem does it.
 
  • #9


i may be confused too but isn't bacle correct? i.e. if there exists a regular value, as guaranteed by sard, the locally the function is a projection by the implicit function theorem, hence not one to one.
 
  • #10


mathwonk said:
i may be confused too but isn't bacle correct? i.e. if there exists a regular value, as guaranteed by sard, the locally the function is a projection by the implicit function theorem, hence not one to one.

I don't think so. Sard's theorem guarantees the existence of a regular value, but not necessarily one in the image of the function.
 
  • #11


This topic may be getting old, but I just realized that there is a way of doing this that is close to your suggestion mathwonk. According to the constant rank theorem, the function will be locally a projection at any point where the rank of the derivative is constant in some neighborhood of the point. While there might not be a point where the derivative is surjective, there will be a point where the rank of the derivative attains a maximum, and at that point the rank will be constant in a neighborhood of the point, so your idea goes through.
 

Related to Continously differentiable f: R^n -> R^m not 1-1?

1. What does it mean for a function to be continuously differentiable?

A continuously differentiable function is a function that has a derivative at every point in its domain and the derivative is itself a continuous function. This means that the function is smooth and has no sudden changes or breaks.

2. What is the significance of a function being not 1-1?

A function that is not 1-1 means that there are multiple inputs that can result in the same output. In other words, the function is not injective. This can result in a loss of information and can make it difficult to find an inverse function.

3. How is the differentiability of a function related to its continuity?

A continuously differentiable function is also continuous, but the opposite is not always true. A function can be continuous but not continuously differentiable if it has a sharp corner or point of discontinuity. However, if a function is continuously differentiable, it is automatically continuous.

4. Can a continuously differentiable function be both injective and surjective?

Yes, a continuously differentiable function can be both injective and surjective, meaning it is bijective. This means that each input has a unique output and each output has at least one corresponding input.

5. How does the differentiability of a function affect its rate of change?

A continuously differentiable function has a well-defined derivative at every point, which can be interpreted as the instantaneous rate of change at that point. This means that the function has a consistent and predictable rate of change, making it easier to analyze and understand.

Similar threads

  • Topology and Analysis
Replies
6
Views
945
Replies
4
Views
403
Replies
2
Views
170
  • Topology and Analysis
2
Replies
38
Views
3K
  • Topology and Analysis
Replies
24
Views
2K
Replies
2
Views
1K
Replies
14
Views
3K
  • Calculus and Beyond Homework Help
Replies
20
Views
1K
Replies
2
Views
1K
  • Topology and Analysis
Replies
14
Views
3K
Back
Top