Linear Algebra, Matrix Inverse Proof

In summary, the conversation discusses the problem of showing that (A^-1 + 2B^-1) is invertible when A, B, and 2A + B are invertible n x n matrices. The solution involves using the distributive law for matrices and expressing (A^-1 + 2B^-1)^-1 in terms of A, B, and (2A+B)^-1. The student also mentions using the Binomial Inverse Theorem, but is unsure of how to apply it.
  • #1
patata
10
0

Homework Statement


Let A,B and and 2A + B be invertible n x n matrices. Show that (A^-1 + 2B^-1) is also invertible and express (A^-1 + 2B^-1)^-1 in terms of A, B and (2A+B)^-1

The Attempt at a Solution


I'm not exactly sure how to tackle this problem, i know that for a matrix to be invertible, we have to be able to multiply (both pre and post multiply it) by some other matrix so that their product gives the identity, however, in this case, I'm completely lost as to what to due to the sum of the matrices inside the brackets. Any hints on suggests? Can i let C = the sum of A+2B say to simplify matters? but even if i do that I am not sure how to proceed.

I've also been reading on this thing called 'Binomial Inverse Theorum' but again, I am not to sure if I am barking up the wrong tree or how to apply it to this case.

Thanks for any and all help
 
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  • #2
As some attempted working, If i multiply A(A^-1 +2B^-1)2B does that give me I? Essentially what I am finding most confusing is how to deal with the terms in the brackets.
 
  • #3
the distributive law holds for matrices;

C(A+B)=CA+CB

so to expand

(A+B)(C+D),

first you expand the left bracket:

A(C+D)+B(C+D)

and then you do the right brackets similarly.
 

Related to Linear Algebra, Matrix Inverse Proof

1. What is linear algebra?

Linear algebra is a branch of mathematics that deals with studying linear equations and their representations in vector spaces. It involves operations and structures such as matrices, vectors, and linear transformations.

2. What is a matrix inverse?

A matrix inverse is a matrix that, when multiplied by the original matrix, results in the identity matrix. It is denoted as A-1 and is used to solve systems of linear equations and perform other operations in linear algebra.

3. Why is proving the matrix inverse important?

Proving the matrix inverse is important because it ensures the existence and uniqueness of a solution to a system of linear equations. It also allows for efficient computation of solutions and is essential in many applications of linear algebra, such as in computer graphics, data analysis, and engineering.

4. What is the process for proving a matrix inverse?

The process for proving a matrix inverse involves using algebraic manipulations and properties of matrices to show that the product of the original matrix and its inverse results in the identity matrix. This can be done using various methods, such as Gaussian elimination, determinants, or the adjoint matrix.

5. Are there any special types of matrices that do not have an inverse?

Yes, there are special types of matrices that do not have an inverse. These include singular matrices, which have a determinant of zero, and non-square matrices, which cannot have an inverse. It is also important to note that not all square matrices have an inverse, as it is dependent on the matrix's properties and values.

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