Finding the Inverse of a Sum of Matrices

In summary, the conversation discusses finding A given the equation (I+2A)^{-1}= \begin{bmatrix} -1 & 2 \\ 4 & 5 \end{bmatrix}. It is determined that the inverse on the LHS was being distributed incorrectly and the correct method is to take the inverse of both sides. The inverse of the RHS is found to be \begin{bmatrix}\frac{-5}{13} & \frac{2}{13} \\ \frac{4}{13} & \frac{1}{13} \end{bmatrix}, which is then used to solve for A. The final solution for A is \begin{bmatrix} \frac{-9}{13
  • #1
CentreShifter
24
0
Inverse of a sum of matrices [solved]

The problem is relatively simple. Given the equation:

[tex](I+2A)^{-1}= \begin{bmatrix}
-1 & 2 \\
4 & 5 \end{bmatrix}[/tex]

Find A.

My problem seems to be that I'm distributing the inverse on the LHS incorrectly. My real question then is, is the following correct?

[tex](I+2A)^{-1}=I^{-1}+\frac{1}{2}A^{-1}[/tex]
 
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  • #2
CentreShifter said:
The problem is relatively simple. Given the equation:

[tex](I+2A)^{-1}= \begin{bmatrix}
-1 & 2 \\
4 & 5 \end{bmatrix}[/tex]

Find A.

My problem seems to be that I'm distributing the inverse on the LHS incorrectly. My real question then is, is the following correct?

[tex](I+2A)^{-1}=I^{-1}+\frac{1}{2}A^{-1}[/tex]
No. There is no distributive property for exponents, which is what you seem to be doing.

Since
[tex](I+2A)^{-1}= \begin{bmatrix}
-1 & 2 \\
4 & 5 \end{bmatrix}[/tex]

The matrix on the right is clearly invertible, so why don't you take the inverse of both sides?
 
  • #3
Well, exponents do distribute over products in some fashion, and there is the binomial theorem and its generalizations. But the first is not relevant and the second a long and torturous path for this problem.
 
  • #4
I should have been more clear - that exponents don't distribute over a sum; in other words, that (A + B)n [itex]\neq[/itex] An + Bn.
 
  • #5
Beautiful.

Inverting both sides did the trick.

Inverse of the RHS is [tex]\begin{bmatrix}\frac{-5}{13} & \frac{2}{13} \\ \frac{4}{13} & \frac{1}{13} \end{bmatrix}[/tex]. I'll call this [tex]B^{-1}[/tex]

So then I'm left with
[tex]\begin{align}I+2A&=B^{-1} \\

2A&=B^{-1}-I \\

A&=\frac{B^{-1}-I}{2}=\begin{bmatrix} \frac{-9}{13} & \frac{1}{13} \\ \frac{2}{13} & \frac{-6}{13}\end{bmatrix} \end{align}[/tex]

Plugging this into the original LHS yields the correct result. Thanks.
 

FAQ: Finding the Inverse of a Sum of Matrices

What is the inverse of a sum of matrices?

The inverse of a sum of matrices is the matrix that, when added to the original matrix, results in the identity matrix. In other words, it is the matrix that "undoes" the effects of the original matrix.

Can the inverse of a sum of matrices always be found?

No, the inverse of a sum of matrices can only be found if both matrices in the sum are invertible. If one or both matrices are not invertible, then the inverse of the sum does not exist.

How do you calculate the inverse of a sum of matrices?

The inverse of a sum of matrices can be calculated by first finding the inverse of each individual matrix, then adding the two inverses together, and finally taking the inverse of the resulting matrix. This can be represented algebraically as (A + B)^-1 = A^-1 + B^-1.

Is the inverse of a sum of matrices commutative?

No, the inverse of a sum of matrices is not commutative. In other words, the order in which the matrices are added matters. This can be seen in the algebraic representation (A + B)^-1 does not equal B^-1 + A^-1.

What is the significance of the inverse of a sum of matrices?

The inverse of a sum of matrices is important in solving systems of linear equations. It allows us to "undo" the effects of the original matrices and find the solution to the system. It is also useful in other areas of mathematics, such as finding the inverse of a function or solving optimization problems.

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