Linear Algebra: Find a formula for a matrix M to any power

In summary, to find the matrix power ##M^n## for a given ##2 \times 2## matrix ##M##, you can use the Jordan canonical form and the fact that ##M^n = E_1 8^n + E_2\, n 8^{n-1}##, where ##E_1, E_2## are matrices that can be obtained from two known values of ##M^n##.
  • #1
Neutrinogun
9
0

Homework Statement


sCWkyXV.png



Homework Equations


A = SDS-1

Under some specific conditions,

An=SDnS-1


The Attempt at a Solution


det(A-λI) = 0
(16-λ)(-λ) - (-64)(1) = 0
λ2 - 16λ + 64 = 0

λ = 8 Multiplicity 2.

This is as far as I got because you need 2 eigenvalues to get 2 eigenvectors to create the S/D matrices. Is there another way to solve this, because this is the only way I learned. Also there has to be an answer for this because it is on webwork with fill in the blank answers.
 
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  • #2
Neutrinogun said:

Homework Statement


sCWkyXV.png



Homework Equations


A = SDS-1

Under some specific conditions,

An=SDnS-1


The Attempt at a Solution


det(A-λI) = 0
(16-λ)(-λ) - (-64)(1) = 0
λ2 - 16λ + 64 = 0

λ = 8 Multiplicity 2.

This is as far as I got because you need 2 eigenvalues to get 2 eigenvectors to create the S/D matrices. Is there another way to solve this, because this is the only way I learned. Also there has to be an answer for this because it is on webwork with fill in the blank answers.

For an ##n \times n## matrix ##A##, if ##r_1, r_2, \ldots, r_p## are the distinct eigenvalues of multiplicities ##m_1, m_2, \ldots, m_p##, it follows from the Jordan canonical form that there are matrices ##E_{i,k_i}, i = 1, \ldots, p, k_i = 1, \ldots, m_i## such that
[tex] P(A) = \sum_{i=1}^p [E_{i1} P(r_i) + E_{i2} P'(r_i) + \cdots + E_{i,m_i} P^{(m_i-1)}(r_i) ] [/tex]
The matrices ##E_{ik}## are fixed, and are the same for all functions ##P##.

In your case, ##P(M) = E_1 P(8) + E_2 P'(8)##, where the matrices ##E_1, E_2## are the same for any polynomial ##P## (and, in fact, for any analytic function ##f(M)##). You can get them from two known values ##P(M)##, such as for ##P(x) = 1 \Longrightarrow P(M) = I## (the identity matrix) and ##P(x) = x \Longrightarrow P(M) = M##. For ##P(x) = 1, P'(x) = 0## we get ##I = E_1 + 0 E_2## and for ##P(x) = x, P'(x) = 1## we get ##M = 8 E_1 + 1 E_2##. You can solve for ##E_1, E_2##, then get ##M^n = E_1 8^n + E_2\, n 8^{n-1}##.
 
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Related to Linear Algebra: Find a formula for a matrix M to any power

1. How do I find the formula for a matrix M to any power?

To find the formula for a matrix M to any power, you can use the concept of diagonalization. This involves finding the eigenvalues and eigenvectors of the matrix, and using them to create a diagonal matrix D. Then, you can raise D to the desired power and use the eigenvectors to transform it back into the original matrix form. This will give you the formula for M to any power.

2. Can I use the formula for a matrix M to any power for non-square matrices?

No, the formula for a matrix M to any power only applies to square matrices. This is because non-square matrices do not have eigenvalues and eigenvectors, which are essential for finding the diagonal form of the matrix.

3. Is there a simpler way to find the formula for a matrix M to any power?

Yes, there are other methods for finding the formula for a matrix M to any power, such as using the Cayley-Hamilton theorem or the Jordan canonical form. However, these methods may be more advanced and require a deeper understanding of linear algebra.

4. Can I use the formula for a matrix M to any power for any type of matrix?

Yes, the formula for a matrix M to any power can be used for any type of matrix, including square, symmetric, and skew-symmetric matrices. However, the method for finding the formula may differ depending on the type of matrix.

5. Are there any applications of the formula for a matrix M to any power?

Yes, the formula for a matrix M to any power is used in many areas of mathematics and science, including physics, engineering, and computer science. It is particularly useful in solving systems of differential equations and in analyzing the behavior of dynamical systems.

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