Powers of a Matrix and Eigenvalues proof

In summary, to prove that v is an eigenvector for Ak if A is an nxn matrix with eigenvector v, you need to examine A(Av) = A(λv) and simplify both the left and right sides. This will show that v is an eigenvector of A-squared with the associated eigenvalue. This will give you a hint about the link between A^k, v, and the corresponding eigenvalue, ultimately leading to the proof.
  • #1
muzziMsyed21
8
0

Homework Statement



Prove that if A is an nxn matrix with eigenvector v, then v is an eigenvector for Ak where kε(all positive integers)


Homework Equations



Av=λv

The Attempt at a Solution



Av=λv
A(Av)=A(λv)
Akv=λ(Av)

i know i may not be doing it right but this is what i can think of so far
 
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  • #2
muzziMsyed21 said:
Av=λv
A(Av)=A(λv)

What if I rewrote that as
A(Av) = λ(Av)
 
  • #3
If you want to show that v is an eigenvector of a power of A (given that v is an eigenvector of A itself), you need to know what happens when you multiply v by some power of A. Consider the second power to begin with - the pattern you see continues for higher powers. So,

if Av = λv, what do you get when you examine

A(Av) = A(λv)

* and simplify the left side?
* and simplify the right side (remember that A(λv) = λ(Av)) when you simplify the right?

If you correctly simplify these two pieces you should be able to show that v IS an eigenvector of A-squared, AND you will know the associated eigenvalue. The latter is important, because it will give you a major hint about the link between A^k, v, and the corresponding eigenvalue. Once you see that link, you will know how to answer your question.
 

Related to Powers of a Matrix and Eigenvalues proof

1. What is a matrix?

A matrix is a rectangular array of numbers, symbols, or expressions arranged in rows and columns. It is often used in mathematics and science to represent data or perform operations.

2. What are the powers of a matrix?

The powers of a matrix refer to its repeated multiplication with itself. For example, the second power of a matrix A is A*A, the third power is A*A*A, and so on.

3. What is an eigenvalue?

An eigenvalue of a square matrix is a number that, when multiplied by a certain vector, results in a new vector that is in the same direction as the original vector. In other words, it is a special scalar value associated with a matrix.

4. Why is calculating eigenvalues important?

Calculating eigenvalues can provide useful information about a matrix, such as determining whether it is invertible or singular. It is also used in various applications, such as solving systems of differential equations and finding the principal components in data analysis.

5. How do you prove properties of powers of a matrix and eigenvalues?

The proof of properties of powers of a matrix and eigenvalues involves using mathematical concepts and equations to show that the properties hold true for all possible matrices and eigenvalues. This typically involves using concepts from linear algebra, such as diagonalization and eigendecomposition, to simplify the equations and arrive at a solution.

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