Inverse of the difference of two matrices A and B

In summary, the conversation discusses how to show that 1/(A-B) can be expressed as a sum of terms involving A and B, with the inverse of A being a crucial factor. An initial attempt at solving the problem is provided, but it is noted that A and B are not commutative, making it difficult to derive the expression in the RHS. A suggestion is made to use the formula for the sum of a geometric series, but it is mentioned that some conditions on the norms of the matrices may be necessary. Finally, it is suggested to follow a similar proof, being careful not to assume commutativity.
  • #1
yukawa
13
0

Homework Statement


Show that
1/(A-B) = (1/A) + (1/A)B(1/A) + (1/A)B(1/A)B(1/A) + (1/A)B(1/A)B(1/A)B(1/A)+...

where A and B are matrices whose inverse exist.


The Attempt at a Solution


I tried to start from the LHS by pulling out (1/A):
LHS = (1/A)[1 + B(1/A) + B(1/A)B(1/A) + B(1/A)B(1/A)B(1/A)+...]
= (1/A)*{1/[1-B(1/A)]} where I have used equation of GP sum to infinity
= 1/(A - AB(1/A))
However, i can't get the expression in RHS since A and B are not commute.

Are there any other possible approach to this problem?

Any help would be great~thanks~
 
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  • #2


yukawa said:

Homework Statement


Show that
1/(A-B) = (1/A) + (1/A)B(1/A) + (1/A)B(1/A)B(1/A) + (1/A)B(1/A)B(1/A)B(1/A)+...
So, more simply, (1/A)(1/1-(B/A))= (1/A)[(B/A)+ (B/A)2+ (B/A)3+ ...)

Do you know the proof of the sum of a geometric series?>

where A and B are matrices whose inverse exist.


The Attempt at a Solution


I tried to start from the LHS by pulling out (1/A):
LHS = (1/A)[1 + B(1/A) + B(1/A)B(1/A) + B(1/A)B(1/A)B(1/A)+...]
= (1/A)*{1/[1-B(1/A)]} where I have used equation of GP sum to infinity
= 1/(A - AB(1/A))
However, i can't get the expression in RHS since A and B are not commute.

Are there any other possible approach to this problem?

Any help would be great~thanks~
 
  • #3


The geometric series approach came to mind as well, but since these are matrices some care needs to be taken.
If this is simply a formal problem the suggestion makes sense: usually, however, it is not enough to go through the mechanics - some conditions on the norms of the matrices are required.
This seems to be a rather poorly worded problem
(BUT, I agree with the suggestion of HallsofIvy - that seems to be the intent here)
 
  • #4


You cannot assume that the formula for the sum of a geometric series of real numbers, but you can copy the proof- being careful that you don't assume commutativity.
 

What is the inverse of the difference of two matrices A and B?

The inverse of the difference of two matrices A and B is the matrix that, when multiplied by the difference of A and B, results in the identity matrix. In other words, it is the matrix that "undoes" the effect of the difference of A and B.

Is the inverse of the difference of two matrices always defined?

No, the inverse of the difference of two matrices is only defined if the difference of A and B is an invertible matrix. Invertible matrices are those that have a non-zero determinant, which means they have a unique solution to the equation Ax = b for any given b.

How do you calculate the inverse of the difference of two matrices?

To calculate the inverse of the difference of two matrices A and B, you can use the formula (A-B)^-1 = A^-1 - B^-1. This means taking the inverse of each matrix separately and then subtracting them from each other.

What is the role of the inverse of the difference of two matrices in solving systems of linear equations?

The inverse of the difference of two matrices can be used to solve systems of linear equations by multiplying it with the right-hand side of the equation. This allows us to "undo" the matrix operations and find the values of the variables in the system.

Can the inverse of the difference of two matrices be used for any type of matrix operation?

No, the inverse of the difference of two matrices can only be used for subtraction. It cannot be used for addition, multiplication, or division of matrices. Additionally, it can only be used for square matrices, meaning that the number of rows must be equal to the number of columns.

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