Finding the Base Matrix A from Matrix A100

In summary, if a matrix is not diagonalizable, we can use its Jordan canonical form to compute its powers. This involves finding the eigenvectors and eigenvalues, and then using these values to construct the Jordan canonical form, which can be used to find the powers of the matrix.
  • #1
Anarza
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Homework Statement


If A100 is some 3x3 matrix, find the base matrix A.

2. Relevant information
Eigenvalues, diagonalization, etc.

The Attempt at a Solution


So far, I've been finding the eigenvalues and diagonalizing the matrix via A = P-1DP where D is the diagonal matrix and P is a matrix with A's eigenvalues. hoping to find the base matrix with powers of n. Any suggestions to guide me?

There was a similar discussion to this earlier, trying to reference that as well.
 
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  • #2
I think your method sounds good. What problem are you having with it?
If A = P-1DP, then A2 = P-1DPP-1DP = P-1D2P, right?
 
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  • #3
Anarza said:

Homework Statement


If A100 is some 3x3 matrix, find the base matrix A.

2. Relevant information
Eigenvalues, diagonalization, etc.

The Attempt at a Solution


So far, I've been finding the eigenvalues and diagonalizing the matrix via A = P-1DP where D is the diagonal matrix and P is a matrix with A's eigenvalues. hoping to find the base matrix with powers of n. Any suggestions to guide me?

There was a similar discussion to this earlier, trying to reference that as well.

Some matrices are not diagonalizable. What would you do in those cases?
 
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  • #4
RUber said:
I think your method sounds good. What problem are you having with it?
If A = P-1DP, then A2 = P-1DPP-1DP = P-1D2P, right?

After finding the diagonal, the P matrix, and the inverse of P, I'm setting them equal to An (with the numeric digits in the diagonal also set to the nth power). The cross produce of these three matrices supposedly give me the power formula of the base matrix A.

Example: A 3x3 matrix of {{1,1,1},{2,2,2},{3,3,3}} turns out to be all the same digits to the nth power. I can see how this works moving forward, but it's not giving me the root matrix.
 
  • #5
Ray Vickson said:
Some matrices are not diagonalizable. What would you do in those cases?

Hmm, I'm not quite sure. I did a check to make sure the one I'm dealing with is, but I would be interested in knowing what to do in other cases as well. The book I'm using gives examples on how to go forward from A to A100 via use of patterns, but those matricies are diagonalizable as well.
 
  • #6
Anarza said:
After finding the diagonal, the P matrix, and the inverse of P, I'm setting them equal to An (with the numeric digits in the diagonal also set to the nth power). The cross produce of these three matrices supposedly give me the power formula of the base matrix A.

Example: A 3x3 matrix of {{1,1,1},{2,2,2},{3,3,3}} turns out to be all the same digits to the nth power. I can see how this works moving forward, but it's not giving me the root matrix.

I think your example may hint at Ray's question.
With a diagonalizable matrix A=P-1DP, you have found that A100=P-1D100P. And a diagonal matrix raised to a power is the same as each term in that matrix raised to the same power.
I question whether your example is diagonalizable, since your rows are all colinear.
 
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  • #7
Anarza said:
Hmm, I'm not quite sure. I did a check to make sure the one I'm dealing with is, but I would be interested in knowing what to do in other cases as well. The book I'm using gives examples on how to go forward from A to A100 via use of patterns, but those matricies are diagonalizable as well.

Here is an example:
[tex] A = \pmatrix{11/10&19/10&21/10\\
1/10& 19/10& 11/10\\
-1/10&-9/10&-1/10} [/tex]
The eigenvalues of ##A## are ##1,1,9/10##, and there are only two eigenvectors; thus, ##A## is not diagonalizable. In fact, if
[tex] P = \pmatrix{1&0&1\\0&1&1\\-1&1&-1}, \; P^{-1} = \pmatrix{2&-1&1\\1&0&1\\-1&1&-1} [/tex]
we have
[tex] A = P^{-1} J P \;\; \text{where} \;\; J = \pmatrix{1&1&0\\0&1&0\\0&0&9/10} [/tex]
Here, ##J## is the Jordan canonical form of ##A##.

We have ##A^n = P^{-1} J^n P##, and ##J^n## is easily computed:
[tex] J^n = \pmatrix{1 & n & 0\\0 & 1 & 0\\0 & 0 & (9/10^n} [/tex]

In general, if the Jordan canonical form of a matrix is
[tex] J = \pmatrix{a & 1 & 0\\0 & a & 0 \\ 0 & 0 & b} [/tex]
then
[tex] J^n = \pmatrix{a^n & n a^{n-1} & 0 \\ 0 & a^n & 0 \\ 0 & 0 & b^n} [/tex]
 
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  • #8
Ray Vickson said:
Here is an example:
[tex] A = \pmatrix{11/10&19/10&21/10\\
1/10& 19/10& 11/10\\
-1/10&-9/10&-1/10} [/tex]
The eigenvalues of ##A## are ##1,1,9/10##, and there are only two eigenvectors; thus, ##A## is not diagonalizable. In fact, if
[tex] P = \pmatrix{1&0&1\\0&1&1\\-1&1&-1}, \; P^{-1} = \pmatrix{2&-1&1\\1&0&1\\-1&1&-1} [/tex]
we have
[tex] A = P^{-1} J P \;\; \text{where} \;\; J = \pmatrix{1&1&0\\0&1&0\\0&0&9/10} [/tex]
Here, ##J## is the Jordan canonical form of ##A##.

We have ##A^n = P^{-1} J^n P##, and ##J^n## is easily computed:
[tex] J^n = \pmatrix{1 & n & 0\\0 & 1 & 0\\0 & 0 & (9/10^n} [/tex]

In general, if the Jordan canonical form of a matrix is
[tex] J = \pmatrix{a & 1 & 0\\0 & a & 0 \\ 0 & 0 & b} [/tex]
then
[tex] J^n = \pmatrix{a^n & n a^{n-1} & 0 \\ 0 & a^n & 0 \\ 0 & 0 & b^n} [/tex]

Ah, that actually makes sense! Thank you for going through the details.
 

Related to Finding the Base Matrix A from Matrix A100

1. How can I find the base matrix A from matrix A100?

To find the base matrix A from matrix A100, you can use the process of matrix decomposition. This involves finding the eigenvalues and eigenvectors of matrix A100 and then using them to create a diagonal matrix, which will be the base matrix A.

2. Is it possible to find the base matrix A without using matrix decomposition?

No, matrix decomposition is the most efficient and accurate method for finding the base matrix A from matrix A100. Other methods, such as row reduction, can also be used but may be more time-consuming and less accurate.

3. Can the base matrix A be different for each matrix A100?

Yes, the base matrix A will be different for each matrix A100 as it is dependent on the eigenvalues and eigenvectors of the specific matrix A100. This means that even small changes in the values of matrix A100 can result in a different base matrix A.

4. What is the significance of finding the base matrix A from matrix A100?

The base matrix A is important as it allows us to easily perform operations on matrix A100, such as finding its inverse or raising it to a power. It also provides insight into the structure and behavior of matrix A100.

5. Can the base matrix A be used to recreate matrix A100?

Yes, the base matrix A can be used to recreate matrix A100 by multiplying it with a specific transformation matrix. This transformation matrix will be dependent on the specific values in matrix A100 and can be calculated using the eigenvectors and eigenvalues of matrix A100.

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