Powers of a Matrix and Eigenvalues proof

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SUMMARY

The discussion centers on proving that if A is an nxn matrix with eigenvector v, then v is also an eigenvector for Ak, where k is any positive integer. The proof begins with the eigenvalue equation Av = λv and extends to higher powers of A by demonstrating that A(Av) = A(λv) simplifies to Akv = λ^k v. This establishes that v remains an eigenvector for any power of A, with the corresponding eigenvalue being λ^k.

PREREQUISITES
  • Understanding of eigenvalues and eigenvectors
  • Familiarity with matrix multiplication
  • Knowledge of the properties of linear transformations
  • Basic concepts of mathematical induction
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  • Study the properties of eigenvalues and eigenvectors in linear algebra
  • Learn about matrix powers and their implications in linear transformations
  • Explore mathematical induction techniques for proving properties of matrices
  • Investigate the spectral theorem and its applications in eigenvalue problems
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Students studying linear algebra, mathematicians interested in matrix theory, and educators teaching eigenvalue concepts.

muzziMsyed21
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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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muzziMsyed21 said:
Av=λv
A(Av)=A(λv)

What if I rewrote that as
A(Av) = λ(Av)
 
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.
 

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