Matrices and eigen value problems

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Homework Help Overview

The problem involves two nxn matrices, A and B, and requires showing that the matrix I - BA is invertible if I - AB is invertible. It also asks to deduce that AB and BA have the same eigenvalues. The discussion centers around properties of determinants and matrix invertibility.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the implications of the determinant being non-zero for invertibility and explore the relationship between the matrices AB and BA. Some suggest examining specific matrix forms and properties, while others propose verifying hints provided in earlier posts.

Discussion Status

There is ongoing exploration of the problem with participants attempting to clarify their understanding of the determinant and its properties. Hints have been provided regarding potential approaches to demonstrate the invertibility of the matrices in question, but no consensus or resolution has been reached yet.

Contextual Notes

Some participants express confusion regarding the hints and the steps needed to show the required properties of the matrices. There is also mention of the need for additional resources or references for further study on matrices and linear algebra.

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Homework Statement



Let A and B be nxn matrices over reals. Show that I - BA is invertible if I - AB is invertible. Deduce that AB and BA have the same eigen values

Homework Equations



det(AB) = det(A).det(B)

The Attempt at a Solution



given: (I-AB) is invertible

-> det(I-AB) is not equal to 0

i.e. (-1)^n times det(AB-I) is not equal to 0
i.e. (-1)^n times det(AB)-det(I) is not equal to 0
i.e. (-1)^n times det(A).det(B)-det(I) is not equal to 0
i.e. (-1)^n times det(B).det(A)-det(I) is not equal to 0
i.e. (-1)^n times det(BA)-det(I) is not equal to 0
i.e. (-1)^n times det(BA-I) is not equal to 0

-> det(I-BA) is not equal to 0

and hence (I - BA) is invertible, if (I - AB) is invertible

as regards to the second part i have not got it yet...
 
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While the determinant may be linear in the rows and columns of a matrix, it is in general NOT linear with respect to entire matrices. That is, [itex]\det (A+B) \neq \det A + \det B[/itex].

Hint: take a look at the matrix [itex]B(I-AB)^{-1}A+I[/itex].
 
Also, for the eigenvalues, try multiplying the eigenvalue/vector equation [itex]ABx = \lambda x[/itex] by a certain matrix to transform it into an equation involving BA.
 
stringy said:
While the determinant may be linear in the rows and columns of a matrix, it is in general NOT linear with respect to entire matrices. That is, [itex]\det (A+B) \neq \det A + \det B[/itex].

Hint: take a look at the matrix [itex]B(I-AB)^{-1}A+I[/itex].

i am just a little confused here.. see..
 

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Make up two 2x2 matrices. Odds are they they will provide a counterexample to

[tex]\det (A+B) = \det A +\det B.[/tex]

Or, for a more general argument with 2x2's, suppose

[tex]A= \begin{bmatrix} \leftarrow & a_1 &\rightarrow \\ \leftarrow & a_2 & \rightarrow\end{bmatrix}, \quad B= \begin{bmatrix} \leftarrow & b_1 &\rightarrow \\ \leftarrow & b_2 & \rightarrow\end{bmatrix}[/tex]

where [itex]a_1,a_2[/itex] and [itex]b_1,b_2[/itex] are the rows of A and B, respectively. Then

[tex]\det (A+B) = \det \begin{bmatrix} a_1+b_1 \\ a_2+b_2\end{bmatrix} = \det \begin{bmatrix}a_1 \\a_2+b_2\end{bmatrix}+\det\begin{bmatrix}b_1 \\a_2+b_2\end{bmatrix}=\det\begin{bmatrix}a_1 \\a_2\end{bmatrix}+\det\begin{bmatrix}a_1 \\b_2\end{bmatrix}+\det\begin{bmatrix}b_1 \\a_2\end{bmatrix}+\det\begin{bmatrix}b_1 \\b_2\end{bmatrix} = \det A + \det B +\det\begin{bmatrix}a_1 \\b_2\end{bmatrix}+\det\begin{bmatrix}b_1 \\a_2\end{bmatrix}.[/tex]

If those extra terms vanish, then [itex]\det (A+B) =\det A +\det B[/itex]. But in general, it's not true. It would be nice if it were though. :smile: Remember it's ONLY linear in the rows and columns, not the entire matrix itself. This is also the reason that if A is nxn, then

[tex]\det (cA) = c^n \det A.[/tex]
 
stringy said:
Make up two 2x2 matrices. Odds are they they will provide a counterexample to

[tex]\det (A+B) = \det A +\det B.[/tex]

Or, for a more general argument with 2x2's, suppose

[tex]A= \begin{bmatrix} \leftarrow & a_1 &\rightarrow \\ \leftarrow & a_2 & \rightarrow\end{bmatrix}, \quad B= \begin{bmatrix} \leftarrow & b_1 &\rightarrow \\ \leftarrow & b_2 & \rightarrow\end{bmatrix}[/tex]

where [itex]a_1,a_2[/itex] and [itex]b_1,b_2[/itex] are the rows of A and B, respectively. Then

[tex]\det (A+B) = \det \begin{bmatrix} a_1+b_1 \\ a_2+b_2\end{bmatrix} = \det \begin{bmatrix}a_1 \\a_2+b_2\end{bmatrix}+\det\begin{bmatrix}b_1 \\a_2+b_2\end{bmatrix}=\det\begin{bmatrix}a_1 \\a_2\end{bmatrix}+\det\begin{bmatrix}a_1 \\b_2\end{bmatrix}+\det\begin{bmatrix}b_1 \\a_2\end{bmatrix}+\det\begin{bmatrix}b_1 \\b_2\end{bmatrix} = \det A + \det B +\det\begin{bmatrix}a_1 \\b_2\end{bmatrix}+\det\begin{bmatrix}b_1 \\a_2\end{bmatrix}.[/tex]

If those extra terms vanish, then [itex]\det (A+B) =\det A +\det B[/itex]. But in general, it's not true. It would be nice if it were though. :smile: Remember it's ONLY linear in the rows and columns, not the entire matrix itself. This is also the reason that if A is nxn, then

[tex]\det (cA) = c^n \det A.[/tex]

thanks a lot.. any idea then how to solve the first part of the problem.. i am stuck...
 
Did you take a look at the hint in my first post? Try verifying that that matrix is the inverse you're looking for.
 
stringy said:
Did you take a look at the hint in my first post? Try verifying that that matrix is the inverse you're looking for.

ya .. well i didnt understand .. i wish you could break it down for me.. and how you got the idea to solve it... is there any particular book that's good for "matrices" and "linear algebra" . . . ?
 
stringy said:
Did you take a look at the hint in my first post? Try verifying that that matrix is the inverse you're looking for.

also could you help me out with this problem too..
 

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  • #10
For future reference, start a new thread when you have a new question. You'll get a lot more traffic and lots more help. :smile:

EDIT: I wrote a big long post, but then forgot to ask the most important question first! Can you show me what you've tried so far?
 
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  • #11
stringy said:
For future reference, start a new thread when you have a new question. You'll get a lot more traffic and lots more help. :smile:

EDIT: I wrote a big long post, but then forgot to ask the most important question first! Can you show me what you've tried so far?

well what i have tried so far has been the wrong approach as you have pointed out.. thanks for that ... so to be honest ... right now i have nothing to show .. as i didn't understand how really B(I−AB)^−1.A+I is the inverse to the matrix i am looking for?
 
  • #12
There are a variety of ways to show that a matrix is invertible: show it's determinant is different from zero, show that it has full rank, show that the equation Ax=0 has only the trivial solution, etc. etc. However, we're going to construct a matrix that will send I-BA to the identity, and since inverses are unique, this must be the inverse we're after. Also note that--in the case of matrices at least--showing a matix is a left- or right-inverse is equivalent to showing that it is THE two-sided inverse.

So we need to show that

[tex](I-BA)(B(I-AB)^{-1}A+I) = I.[/tex]

That matrix, our candidate for the inverse, exists by hypothesis, i.e., it contains the inverse of I-AB which we are allowed to assume exists. So, therefore, the first step is to expand that multiplication:

[tex](I-BA)(B(I-AB)^{-1}A+I) = B(I-AB)^{-1}A+I -BA(B(I-AB)^{-1}A+I) = B(I-AB)^{-1}A+I -BAB(I-AB)^{-1}A-BA.[/tex]

Try taking over from here...
 
  • #13
stringy said:
There are a variety of ways to show that a matrix is invertible: show it's determinant is different from zero, show that it has full rank, show that the equation Ax=0 has only the trivial solution, etc. etc. However, we're going to construct a matrix that will send I-BA to the identity, and since inverses are unique, this must be the inverse we're after. Also note that--in the case of matrices at least--showing a matix is a left- or right-inverse is equivalent to showing that it is THE two-sided inverse.

So we need to show that

[tex](I-BA)(B(I-AB)^{-1}A+I) = I.[/tex]

That matrix, our candidate for the inverse, exists by hypothesis, i.e., it contains the inverse of I-AB which we are allowed to assume exists. So, therefore, the first step is to expand that multiplication:

[tex](I-BA)(B(I-AB)^{-1}A+I) = B(I-AB)^{-1}A+I -BA(B(I-AB)^{-1}A+I) = B(I-AB)^{-1}A+I -BAB(I-AB)^{-1}A-BA.[/tex]

Try taking over from here...
very interesting thanks .. a lot .. could you tell me of any good book which covers matrices thoroughly ? thanks again . .
 
  • #14
It's hard to know what exactly to recommend when I don't know your background.

There is a subforum over in Academic Guidance called Science Book Discussion where they will recommend books. Maybe you should post over there. Or, I'm sure there will probably be some results that pop up if you use the search feature. And, take a look https://www.physicsforums.com/blog.php?b=3206" .

I didn't learn my linear algebra and matrix theory all from one source, it was kind of a piecemeal education that I picked up as I went along. I hated my intro linear algebra text and course, so perhaps that's why. Now it's one of my favorite things to talk about.
 
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  • #15
stringy said:
It's hard to know what exactly to recommend when I don't know your background.

There is a subforum over in Academic Guidance called Science Book Discussion where they will recommend books. Maybe you should post over there. Or, I'm sure there will probably be some results that pop up if you use the search feature. And, take a look https://www.physicsforums.com/blog.php?b=3206" .

I didn't learn my linear algebra and matrix theory all from one source, it was kind of a piecemeal education that I picked up as I went along. I hated my intro linear algebra text and course, so perhaps that's why. Now it's one of my favorite things to talk about.

sorry for the late reply... thanks for all the help ...:smile:
 
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