Diagonalization and Matrix similarity

In summary: For 1a, it's more useful to write A = PDP^-1, then it's clear what A^-1 has to be. b is the same idea.For 2, write B = PAP^-1, C = QBQ^-1 (you can't use the same P for both), then the rest is pretty obvious.
  • #1
Bertrandkis
25
0
Question1 :
a) Show that if A is nonsingular and diagonalizable then A^-1 is diagonalizable
b) Show that if A is diagonalizable then A^T is diagonalizable

Question 2
Show that if A is similar to B and B similar to C, then A is similar to C.
 
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  • #2
What have you tried so far? This is a straightforward application of the definitions.
 
  • #3
Why are you doing a problem like this? If it is schoolwork (and it is certainly worded as such) then it should be in the "Homework and Schoolwork" section.

Also, you can't simply post a problem like this and expect someone else to give you the solution. Show what work you have done. Start, at the least, by quoting the definitions of "nonsingular", "diagonalizable", and "similar".
 
  • #4
THIS IS WHAT I TRIED
Question1 :
a) Show that if A is nonsingular and diagonalizable then A[tex]^{-1}[/tex] is diagonalizable

MY SOLUTION
If A is non singular then AA[tex]^{-1}[/tex]=I
If A is diagonalizable if it's similar to a diagonal matrix => P[tex]^{-1}[/tex]AP=D
which implies that AP=PD (1)
We need to show that A[tex]^{-1}[/tex]P=PD [tex]^{-1}[/tex]

so multiply both sides of (1) by A[tex]^{-1}[/tex] we have PA=PD (2)

then multiply both sides of (2) by D[tex]^{-1}[/tex] we have D[tex]^{-1}[/tex]P=A[tex]^{-1}[/tex]P

Therefore A[tex]^{-1}[/tex] is diagonalizable


Question 2
Show that if A is similar to B and B similar to C, then A is similar to C

MY SOLUTION
if A is similar to B then P[tex]^{-1}[/tex]AP=B we can show that AP=PB(1)
if B is similar to C then P[tex]^{-1}[/tex]BP=C (2)
now replace BP in equation (2)by (1) then P[tex]^{-1}[/tex]AP=C
Therefore A is similar to C
 
Last edited:
  • #5
For 1a, it's more useful to write A = PDP^-1, then it's clear what A^-1 has to be. b is the same idea.

For 2, write B = PAP^-1, C = QBQ^-1 (you can't use the same P for both), then the rest is pretty obvious.
 
  • #6
Bertrandkis said:
THIS IS WHAT I TRIED
Question1 :
a) Show that if A is nonsingular and diagonalizable then A[tex]^{-1}[/tex] is diagonalizable

MY SOLUTION
If A is non singular then AA[tex]^{-1}[/tex]=I
If A is diagonalizable if it's similar to a diagonal matrix => P[tex]^{-1}[/tex]AP=D
which implies that AP=PD (1)
We need to show that A[tex]^{-1}[/tex]P=PD [tex]^{-1}[/tex]

so multiply both sides of (1) by A[tex]^{-1}[/tex] we have PA=PD (2)

then multiply both sides of (2) by D[tex]^{-1}[/tex] we have D[tex]^{-1}[/tex]P=A[tex]^{-1}[/tex]P
No. If you multiply PA= PD on the LEFT by D-1 you get D-1PA= D-1PD. If you multiply PA= PD on the RIGHT by D-1 you get PAD-1= P. Neither of those is, directly, D-1P= A-1. By the way, have you already proved that, if A is invertible and diagonlizable, the D is also invertible?

Therefore A[tex]^{-1}[/tex] is diagonalizable


Question 2
Show that if A is similar to B and B similar to C, then A is similar to C

MY SOLUTION
if A is similar to B then P[tex]^{-1}[/tex]AP=B we can show that AP=PB(1)
if B is similar to C then P[tex]^{-1}[/tex]BP=C (2)
now replace BP in equation (2)by (1) then P[tex]^{-1}[/tex]AP=C
You can't replace "BP" in (2) by (1)- (1) doesn't say anything about BP- it says that PB=AP. Also, of course, the "P" in your first two equationsis not necessairily the same!
Therefore A is similar to C
 

Related to Diagonalization and Matrix similarity

1. What is diagonalization?

Diagonalization is a process in linear algebra where a square matrix is transformed into a diagonal matrix by finding a similarity transformation. This means that the diagonal matrix has all zeros except on the main diagonal, which contains the eigenvalues of the original matrix.

2. What is the purpose of diagonalization?

The main purpose of diagonalization is to simplify calculations involving matrices, such as finding powers and inverses. It also helps to reveal important properties of the original matrix, such as its eigenvalues and eigenvectors.

3. What conditions must be met for a matrix to be diagonalizable?

A matrix must be square and have n linearly independent eigenvectors to be diagonalizable, where n is the size of the matrix. Additionally, the matrix must have a complete set of eigenvalues, meaning that all of its eigenvalues must be distinct.

4. Can a non-square matrix be diagonalized?

No, only square matrices can be diagonalized. However, a rectangular matrix can be reduced to a diagonal matrix through a similar process called singular value decomposition (SVD).

5. How is matrix similarity related to diagonalization?

Two matrices are considered similar if they represent the same linear transformation with respect to different bases. Diagonalization is one method of finding a similarity transformation for a matrix, so that it can be transformed into a diagonal matrix.

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