Inverse function theorem over matrices

In summary, the conversation discusses the use of functions over matrices and the validity of the inverse function theorem for the identity matrix. The idea of interpreting matrices as vectors and redefining the function with a new dot product is proposed. However, the statement that there exists only one X such that X^2 = Y for a matrix Y near the identity is proven to be false.
  • #1
brunob
15
0
Hi there!
I'm back again with functions over matrices.
I have a function [itex]f : M_{n\times n} \to M_{n\times n} / f(X) = X^2[/itex].

Is valid the inverse function theorem for the [itex]Id[/itex] matrix? It talks about the Jacobian at the [itex]Id[/itex], but I have no idea how get a Jacobian of that function. Can I see that matrices as vectors and redefine the function as [itex]f : R^{n^2} \to R^{n^2} / f(x) = x^2[/itex] using a new dot product?
Also, how can I prove that if a matrix [itex]Y[/itex] is near to [itex]Id[/itex] then [itex]\exists ! X / X^2 = Y[/itex] ?

Thanks!
 
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  • #2
Yes, you can interpret the matrices as vectors. I'm not sure what you mean by "a new dot product". The square of a matrix would not be given by the dot product of the corresponding vector with itself; instead each component of resultant vector would be given by the formula for matrix multiplication.

brunob said:
Also, how can I prove that if a matrix [itex]Y[/itex] is near to [itex]Id[/itex] then [itex]\exists ! X / X^2 = Y[/itex] ?
Thanks!

Is this to be interpreted as "if [itex]Y[/itex] is near the identity, then there exists only one [itex]X[/itex] such that [itex]X^2 = Y[/itex]" ? If so this is false.
 
  • #3
Thanks for your response MisterX.
What I mean with "a new dot product" is defining a product between vectors that represents the matrix multiplication.

Uhmm, yes that's it, it's an extra exercice they give me in my calculus II course. Why you say it's false?
 
  • #4
brunob said:
Thanks for your response MisterX.
What I mean with "a new dot product" is defining a product between vectors that represents the matrix multiplication.

Uhmm, yes that's it, it's an extra exercice they give me in my calculus II course. Why you say it's false?

Then it belongs in the homework forums. Please post there.
 

FAQ: Inverse function theorem over matrices

What is the Inverse Function Theorem over Matrices?

The Inverse Function Theorem over Matrices is a fundamental theorem in linear algebra that relates the invertibility of a matrix to the invertibility of its inverse matrix. It states that if a matrix A is invertible, then its inverse matrix, denoted as A^(-1), is also invertible.

How is the Inverse Function Theorem over Matrices used?

The Inverse Function Theorem over Matrices is used to solve systems of equations, find the inverse of a matrix, and understand the relationship between a matrix and its inverse. It is also used in many other areas of mathematics, such as differential calculus, optimization, and statistics.

What is the significance of the Inverse Function Theorem over Matrices?

The Inverse Function Theorem over Matrices is significant because it provides a powerful tool for solving problems in linear algebra and other areas of mathematics. It allows us to easily determine if a matrix is invertible and to find its inverse, which is essential for many applications in science and engineering.

Can the Inverse Function Theorem over Matrices be extended to higher dimensions?

Yes, the Inverse Function Theorem over Matrices can be extended to higher dimensions. In fact, it is a generalization of the Inverse Function Theorem in single-variable calculus. The theorem holds for matrices of any size, as long as they are square and invertible.

Are there any limitations to the Inverse Function Theorem over Matrices?

One limitation of the Inverse Function Theorem over Matrices is that it only applies to square matrices. Additionally, it assumes that the matrix is invertible, so it cannot be used to find the inverse of a singular matrix. It also does not provide a method for finding the inverse matrix, but only states its existence.

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