Is the Inverse Function Theorem in R^2 Limited to Certain Neighborhoods?

In summary, the theorem states that there is a neighborhood of a point (x,y) in the plane such that the function F:U\rightarrowV is one-to-one and onto. However, it seems that this may not be the case for points near the origin (r=0).
  • #1
WHOAguitarninja
20
0
Aye...title should say in R^2, sorry about that.
I'm hitting somewhat of a wall in my understanding of a theorem (or rather a special case of a theorem). The theorem as stated in the book is as follows.

The Inverse FUnction Theorem in the Plane
Let O be an open subset of the plane R^2 and suppose that the mapping F: O[tex]\rightarrow[/tex]R[tex]^{2}[/tex] is continuously differentiable. Let (x, y) be a point in O at which the derivative matrix DF(x,y) is invertible.

Then there is a neighborhood U of the point (x,y) and a neighborhood V of its image F(x,y) such that F: U[tex]\rightarrow[/tex]V is one to one and onto.

The theorem goes on to talk about the inverse functions, but that's not where I'm getting stuck. My problem is this. Consider the function F(r,[tex]\theta[/tex]) = (r*cos[tex]\theta[/tex], r*sin[tex]\theta[/tex]).

The determinant of the derivative matrix of this function is just r, so the theorem seems that it should only break down at r=0. However consider the point (r, 2*pi)It does not seem to me that it's 1-1 in a neighborhood around this point, which seems to contradict the theorem.

Where am I misunderstanding things. Is the mapping actually 1-1 here? It seems not to me as it seems to me if you just let theta go to infinity it circles the same ring in the image. I understand that if you restrict it to a ring then it invalidates the theorem as the neighborhood then isn't open due to the ring being thin. But I don't see any way to get around the looping problem.
 
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  • #2
the theorem says the function is 1-1 on SOME nbhd, not on ALL nbhds.
 
  • #3
So let me see if I understand the restriction correctly, as I don't think the book spells this out very well.

We can only state that it's 1-1 if V is some, perhaps restricted, neighborhood of the image of U. That much I see. However we also must restrict U to the neighborhood in which F:U->V is invertible? Otherwise we have that F[tex]^{-1}[/tex](1,0) can be equal to (1, 2*pi*n) for any n. Do we have to choose a range for the inverse from the outset in order to preserve 1-1? Is that correct?
 

FAQ: Is the Inverse Function Theorem in R^2 Limited to Certain Neighborhoods?

What is the Inverse Function Theorem in R?

The Inverse Function Theorem in R is a fundamental concept in calculus and real analysis that states if a function is continuously differentiable at a point, then its inverse function is also continuous at that point. In other words, it describes the relationship between a function and its inverse function.

Why is the Inverse Function Theorem important?

The Inverse Function Theorem is important because it allows us to determine when a function has an inverse and provides a method for finding the inverse function. It is also used in many other areas of mathematics, such as optimization and differential equations.

What are the conditions for the Inverse Function Theorem to hold in R?

The Inverse Function Theorem holds in R if the function is continuously differentiable and has a non-zero derivative at a point. Additionally, the inverse function must also be continuously differentiable at that point.

How is the Inverse Function Theorem used in real life applications?

The Inverse Function Theorem is used in various real-life applications such as engineering, physics, and economics. For example, it is used to solve optimization problems in engineering and to model inverse relationships in economics.

Are there any limitations to the Inverse Function Theorem in R?

One limitation of the Inverse Function Theorem in R is that it only applies to functions with a non-zero derivative. Additionally, it is limited to functions defined on a single variable and does not apply to multivariable functions. It also assumes that the functions are continuously differentiable, which may not always be the case in real-world scenarios.

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