Determining Matrix Powers without Eigenvectors ? (Worked out but inelegant soln)

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Homework Help Overview

The discussion revolves around determining matrix powers without using eigenvectors, specifically focusing on a matrix defined by its elements and its characteristic equation. The original poster presents a method using the Cayley-Hamilton theorem to express higher powers of the matrix in terms of lower powers.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the use of the Cayley-Hamilton theorem and its implications for simplifying calculations of matrix powers. Questions arise regarding the elegance of the solution and the necessity of distinct eigenvalues for diagonalizability. Some participants suggest alternative perspectives on the theorem's utility.

Discussion Status

The discussion is active, with participants providing insights and questioning assumptions about diagonalizability and the application of the Cayley-Hamilton theorem. There is a recognition of the potential for simplifying calculations, though no consensus on the elegance of the original method has been reached.

Contextual Notes

Participants are exploring the implications of eigenvalues on diagonalizability and the conditions under which a matrix can be considered diagonalizable. The conversation also touches on the limitations of using the Cayley-Hamilton theorem in certain scenarios.

sid9221
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My solution:
[tex] M=\begin{bmatrix}<br /> t+15 & -12 \\ <br /> 24 & t-19<br /> \end{bmatrix}[/tex]

The eigen values are 1,3.

Hence as the matrix has real and distinct eigenvalues it is diagonalisable.

Now the characteristic equation is [tex]t^2 - 4t +3 =0[/tex]

So [tex]M^2 - 4M +3I = 0[/tex]

[tex]M^2 = 4M-3I[/tex]

Hence [tex]M^7 = (4M-3I)(4M-3I)(4M-3I)(M)[/tex]

This gives the correct answer but is a very inelegant solution. Is there a better way to determine the answer without Eingevectors ?
 
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Why do you think that is inelegant? You used the Cayley Hamilton Theorem, right? I like it.
 
I think that is exactly what you were supposed to do. The only thing left is to finish the calculation by substituting in the given matrix and doing the multiplications.
 
Mark44 said:
I think that is exactly what you were supposed to do. The only thing left is to finish the calculation by substituting in the given matrix and doing the multiplications.

Whats the point in having a theorem that just saves you 1 multiplication ?
 
If you had a much larger matrix M, and it was being raised to a higher power, this could save you some work.

For this problem, the real goal is to get you comfortable working with the characteristic equation of a matrix.
 
Mark44 said:
If you had a much larger matrix M, and it was being raised to a higher power, this could save you some work.

For this problem, the real goal is to get you comfortable working with the characteristic equation of a matrix.

I see. Thank you.
 
No, no, you're not done yet!

Work out the brackets, you'll see terms like M4 and M3. Substitute them also by using Caley-Hamilton.

The eventual goal is to write

[tex]M^7=aM^2+bM+cI[/tex]

This only needs one matrix multiplication.
 
micromass said:
No, no, you're not done yet!

Work out the brackets, you'll see terms like M4 and M3. Substitute them also by using Caley-Hamilton.

The eventual goal is to write

[tex]M^7=aM^2+bM+cI[/tex]

This only needs one matrix multiplication.

[tex]27 IM-108 M^2-144 IM^3+64 M^4[/tex]

Than sub in value for M^2 and multiply ? I don't see how I can get the answer with 1 multiplication ?
 
sid9221 said:
Hence as the matrix has real and distinct eigenvalues it is diagonalisable.

I think that's incorrect. The proper explanation should be:
Since the matrix does not have zero as one of its eigenvalues, it is invertible, hence it is diagonalisable.

micromass said:
No, no, you're not done yet!

Work out the brackets, you'll see terms like M4 and M3. Substitute them also by using Caley-Hamilton.

The eventual goal is to write

[tex]M^7=aM^2+bM+cI[/tex]

This only needs one matrix multiplication.

But, replacing M^2 again would give M^7 in terms of M and I only, right?
 
  • #10
sharks said:
I think that's incorrect. The proper explanation should be:
Since the matrix does not have zero as one of its eigenvalues, it is invertible, hence it is diagonalisable.

No, that is totally incorrect. Invertibility and diagonalisable have nothing to do with each other.

OP:

[itex]M^2=4M-3I[/itex]

So

[itex]M^3=4M^2-3M[/itex]

So you can replace all occurences of [itex]M^3[/itex] with occurences of [/itex]M^2[/itex].

Same way: you can replace [itex]M^4[/itex] with something and [itex]M^2[/itex] with something.
 
  • #11
sharks said:
But, replacing M^2 again would give M^7 in terms of M and I only, right?

Right! So this problem requires no matrix multiplications at all!
 
  • #12
sid9221 said:
Hence as the matrix has real and distinct eigenvalues it is diagonalisable.

But, do the eigenvalues need to be distinct in order for the matrix to be diagonalisable? What if the eigenvalues are real but equal?
 
  • #13
sharks said:
But, do the eigenvalues need to be distinct in order for the matrix to be diagonalisable? What if the eigenvalues are real but equal?

Then it might or might not be diagonalisable.

A matrix is diagonalisable if and only if it has a basis of eigenvectors. So if the eigenvalues are distinct, then all eigenspaces are distinct and thus a basis of eigenvectors exist.

Another equivalence is: a matrix is diagonalisable if and only if the algebraic multiplicity is the geometric multiplicity.

However, if not all the eigenvalues are distinct, then it might be harder to check diagonalisability. Typically, one has to know the eigenvectors at that point.

Yet another equivalence states that a matrix is diagonalisable iff the minimal polynomial has distinct factors. But then we have to know the minimal polynomial.
 
  • #14
Apparently works out to:

[tex]M^7 = 27 - 108[4M-3I] - 144[16M-15I] + 64[64M-63I][/tex]
 
  • #15
sid9221 said:
Apparently works out to:

[tex]M^7 = 27 - 108[4M-3I] - 144[16M-15I] + 64[64M-63I][/tex]

That first term would have to be 27I.
 
  • #16
micromass said:
Then it might or might not be diagonalisable.

A matrix is diagonalisable if and only if it has a basis of eigenvectors. So if the eigenvalues are distinct, then all eigenspaces are distinct and thus a basis of eigenvectors exist.

Another equivalence is: a matrix is diagonalisable if and only if the algebraic multiplicity is the geometric multiplicity.

However, if not all the eigenvalues are distinct, then it might be harder to check diagonalisability. Typically, one has to know the eigenvectors at that point.

Yet another equivalence states that a matrix is diagonalisable iff the minimal polynomial has distinct factors. But then we have to know the minimal polynomial.
I'll need to look into that a bit more. Thank you for the clarification, micromass.
 
  • #17
Mark44 said:
That first term would have to be 27I.

Yeah of course !

So extending this, you could potentially calculate the 27th power of a 6x6 matrix without a single multiplication(or a few) wow !

Cayley and Hamilton were pretty smart dude's eh !
 

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