Matrix Exponentials: A, Eigenvalues, Jordan Form, Fundamental Matrix T

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Discussion Overview

The discussion revolves around the computation of matrix exponentials, specifically for a given matrix A and its Jordan form. Participants explore the eigenvalues, eigenvectors, and the fundamental matrix T required for expressing the matrix exponential in terms of its Jordan form.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Exploratory

Main Points Raised

  • One participant presents a matrix A and calculates its eigenvalues, noting that there is only one eigenvector for the eigenvalue λ = 1, leading to a proposed Jordan form.
  • Another participant suggests using Taylor's series to compute the matrix exponential e^A, highlighting the complexity involved with Jordan forms compared to diagonal matrices.
  • A participant observes a pattern in the powers of A, noting that A raised to even powers equals the identity matrix, while odd powers return A, but expresses uncertainty about summing the series to find e^A.
  • One participant realizes that the Taylor expansion relates to hyperbolic functions, indicating progress in solving the problem.
  • Another participant introduces an alternative method for handling the Jordan block, suggesting it can be separated into simpler matrices.
  • A participant acknowledges the nilpotent nature of one of the matrices involved and seeks clarification on how to compute e^{At} and determine the fundamental matrix T.
  • Another participant draws a parallel between matrix arithmetic and derivatives, suggesting that a nilpotent matrix behaves similarly to an infinitesimal.

Areas of Agreement / Disagreement

Participants express various approaches and insights into the problem, but there is no consensus on the specific method for determining the fundamental matrix T or the final computation of e^{At}.

Contextual Notes

Some participants' calculations depend on assumptions about the properties of the matrix A and its Jordan form, which may not be fully resolved in the discussion.

Somefantastik
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[tex]A = \[ \left( \begin{array}{ccc}<br /> 0 & 0 & 1 \\<br /> 0 & 1 & 0 \\<br /> 1 & 0 & 0 \end{array} \right)\][/tex]

eigenvalues are [tex]\lambda_{1} = -1, \ \lambda_{2} = \lambda_{3} = 1[/tex]

[tex](A-\lambda_{1}I)u^{(1)} = 0 \ => \ u^{(1)} = \[ \left( \begin{array}{c}<br /> -1 \\<br /> 0 \\<br /> 1 \end{array} \right)\][/tex]

[tex](A-\lambda_{2}I)u^{(2)} = 0 \ => u^{(1)} = \[ \left( \begin{array}{c}<br /> 1 \\<br /> 0 \\<br /> 1 \end{array} \right)\][/tex]

[tex](A -\lambda_{3}I)u^{(3)} = u^{(2)} \ => \ <br /> \left(<br /> \begin{array}{ccc|c}<br /> 1&0&-1&-1\\<br /> 0&0 &0&1\\<br /> 0&0&0&0<br /> \end{array}<br /> \right)[/tex]

since we cannot have 0 = 1, we can say that there is only one eigenvector for

[tex]\lambda = 1[/tex]

which means that the Jordan form will be

[tex]\[ \left( \begin{array}{ccc}<br /> 1 & 1 & 0 \\<br /> 0 & 1 & 0 \\<br /> 0 & 0 & -1 \end{array} \right)\][/tex]

Am I correct?

Now I need to find exp(Jt) and I'm not sure how.

If I only have 2 eigenvectors, how can I find the fund. matrix T such that

[tex]e^{At} = Te^{Jt}T^{-1}[/tex]?
 
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In general, to find such a function of other than a "number", use the Taylor's series

eA= I+ A+ (1/2)A2+ (1/3!)A3+ ...

If A happens to be diagonal, that's easy: An is just the diagonal matrix with exponentials of the diagonal elements of A on its diagonal.

For Jordan form, its a little more complicated. Try calculating J2, J3, ... for this particular J yourself and see if you spot a pattern.
 
I noticed that A2k = I and A(2k+1)'s = A, but I don't know how to get eA from that.
 
Somefantastik said:
I noticed that A2k = I and A(2k+1)'s = A, but I don't know how to get eA from that.
How exactly are you having trouble summing the series?
 
I'm just an idiot. I didn't realize that the Taylor expansions' limits came out to be cosh and sinh. I think I finished this problem. Thanks for the help so far.
 
For the record, there's another method that can be useful. Note that you can separate that Jordan block into

[tex] \left[ \begin{array}{cc} 1 & 1 \\ 0 & 1 \end{array} \right]<br /> =<br /> \left[ \begin{array}{cc} 1 & 0 \\ 0 & 1 \end{array} \right]<br /> +<br /> \left[ \begin{array}{cc} 0 & 1 \\ 0 & 0 \end{array} \right][/tex]

...
 
Ah, I see, and the second matrix is nilpotent.

But still, if I got that, how would I compute

[tex] e^{At} = Te^{Jt}T^{-1} [/tex]

Not sure what T would be in this case.
 
Right. And you'll find the results of doing arithmetic look a lot like derivatives -- a nilpotent matrix behaves a little bit like an infinitessimal.

(Again, look to the series to get started)
 

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