Calculating powers of matrices

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Discussion Overview

The discussion revolves around calculating powers of square matrices, specifically using diagonalization and matrix decomposition methods. Participants explore the concepts of diagonalizable matrices, the process of finding matrices P and D, and the implications of matrix multiplication properties.

Discussion Character

  • Exploratory
  • Technical explanation
  • Homework-related
  • Debate/contested

Main Points Raised

  • One participant expresses confusion about calculating M^k using the equation M^k = PD(P^-1), where D is a diagonal matrix.
  • Another participant notes that some square matrices can be decomposed into the form M = PDP^-1, indicating that these are diagonalizable matrices.
  • A participant attempts to calculate M^2 using the decomposition, suggesting it results in PDPD, but questions whether this is correct.
  • Another participant asks for guidance on finding a non-singular matrix P and a diagonal matrix D for a specific 3x3 matrix A, indicating a lack of familiarity with the topic.
  • Clarification is sought regarding the meaning of "9231 Further Maths," with suggestions that context is necessary for understanding the reference.
  • A participant explains that a matrix is diagonalizable if it has n independent eigenvectors and describes the process of forming matrices P and D from these eigenvectors.
  • It is mentioned that while most matrices are not diagonalizable, they can be reduced to Jordan normal form, which complicates the calculation of their powers.

Areas of Agreement / Disagreement

Participants express varying levels of understanding and familiarity with the concepts discussed. There is no consensus on the correctness of the calculations presented, and some participants challenge earlier claims without reaching a definitive resolution.

Contextual Notes

Some participants indicate a lack of resources or prior knowledge on the topic, which may limit their ability to engage fully with the discussion. The reference to specific coursework may also imply a context-dependent understanding of the material.

Who May Find This Useful

Students studying linear algebra, particularly those interested in matrix theory and diagonalization, as well as individuals preparing for advanced mathematics courses or exams.

rdajunior95
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Hi,


I get a lot of questions about calculating M^k, where M is a square matrix!

They say you can use an equation like M^k=PD(P^-1) where D is a diagonal matrix.

I don't know how to calculate this!

Any help will be appreciated!


P.S. Sorry if this is in the wrong section!
 
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Who are "they"?

This sounds a bit too much like a homework question, so for now I will not give a complete answer. Some square matrices can be decomposed such that M=PDP-1. These are the diagonalizable matrices.

If some matrix M is diagonalizable, what is M2? Try writing it out. Remember that while matrix multiplication is not commutative, it is associative.
 
they are the people who set out the question paper of 9231 Further maths.

So m^2 will be (PD(P^-1))*(PD(P^-1))

so P * P^-1 = I so it will be PDPD.

Am I right?
 
Also I have a question that find a non-singular matrix P and a diagonal matrix D such that (A^5) = PD(P^-1)

Where A is a 3x3 matrix

A is given but I don't know how to put a matrix in a post!

Sorry
 
rdajunior95 said:
they are the people who set out the question paper of 9231
What does this mean? I realize that while English may not be your native language, this cryptic statement wouldn't make sense in any language. What is the "question paper of 9231"?

Further maths.

So m^2 will be (PD(P^-1))*(PD(P^-1))

so P * P^-1 = I so it will be PDPD.

Am I right?
No. Try again.
 
I think you have misread. What I have typed is 9231 Further maths!

And please tell me from where to start!

I haven't even read about it in any books of mine.

I have Complete series of Further Maths 1, 2 & 3 for OCR and Further Pure Mathematics by brian gaulter and mark gaulter and complete series by L. Bostock
 
You need to give the context that 9231 Further Maths is a course or placement test at Cambridge International Education (CIE), something like that. The only reason I know this is that you provided a link to the syllabus for 2010 in another thread. Without this information, people will have no idea what you're talking about.
 
An n by n matrix is "diagonalizable" if and only it has n independent eigenvectors. (That is always true if A is a symmetric matrix and/or has n distinct eigenvalues.)

If A has n independent eigenvectors, the form the matrix P having those eigenvectors as eigenvalues.

Then [math]P^{-1}AP= D[/math] is a diagonal matrix having the eigenvalues of A on the diagonal.

It is easy to take the nth power of a diagonal matrix- [math]D^n[/math] is the diagonal matrix having the nth powers of its diagonal elements on the diagonal.

Also, if [itex]D= P^{-1}AP[/itex], then [itex]D^n= (P^{-1}AP)(p^{-1}AP)\cdot<br /> cdot\cdot(P^{-1}AP)= P^{-1}A^nP[/itex] since all those internal "P"s and "[itex]P^{-1}[/itex]"s cancel.

So [itex]A^n= PD^nP^{-1}[/itex].

Most matrices are NOT "diagonalizable" but can be reduced to "Jordan normal form" which has some "1"s above the diagonal. The formula for nth powers is more complicated but still doable.
 
Thanks for the help! :D
 

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