Scalar Equations: How to solve them

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SUMMARY

The discussion focuses on solving scalar equations, specifically in the context of eigenvalue problems using the divide and conquer algorithm. Abhishek Agrawal seeks clarification on the transformation of the scalar equation 1 + wT(D − λI)−1 w = 0 into the summation form 1 + ∑_{j=1}^{m} (w_{j}^{2}/(d_{j} - λ)) = 0. Participants explain that D is a diagonal matrix, and thus D - λI retains this structure, allowing for straightforward matrix inversion and multiplication with vector w. The discussion concludes with a request for further clarification on the notation d_{j} in the equation.

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abhimanipal
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Hi,
My name is Abhishek Agrawal. I am a grad student in Computer Science. I know very little about scalar equations. But my research has led me to them and I am at my wits end on how to go about solving them. I have looked around every where but I am unable to start.

Homework Statement



http://en.wikipedia.org/wiki/Divide-and-conquer_eigenvalue_algorithm

This is a Wikipedia link on how to use the divide and conquer algorithm to solve for eigen values of a matrix. I understood most of the stuff but towards the end of the link, the author ends up with this equation

1 + wT(D − λI)−1 w = 0

which is a scalar equation. He transforms this equation into an another form. (The formatting came bad on this post, better to view it in Wiki)

1 + \sum_{j=1}^{m} \frac{w_{j}^{2}}{d_{j} - \lambda} = 0.


What I cannot understand is how is the summation applied. How does the author get the wj and dj terms from the matrix . Is he using an entire row or is there some thing I am missing ?

I would appreciate if some one could give me some links so as to what I am missing or could point me to some tutorials
Any help would be appreciated
 
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Hint: if you wrap the TeX code in tex tags (type [ tex ] without the spaces, then this code, then [ / tex ] without the spaces - ie [/tex]), then you will get a nice formatting, like so:
[tex]1 + \sum_{j=1}^{m} \frac{w_{j}^{2}}{d_{j} - \lambda} = 0.[/tex]

Answer to your question: note that D is a diagonal matrix. Therefore, D - λI is a diagonal matrix as well, looking like
[tex]D - \lambda I = \begin{pmatrix} d_1 - \lambda & & 0 \\ & \ddots & \\ 0 & & d_m - \lambda \end{pmatrix}[/tex]

The inverse of this matrix is then simply
[tex](D - \lambda I)^{-1} = \begin{pmatrix} 1/( d_1 - \lambda ) & \cdots & 0 \\ \vdots & \ddots & \\ 0 & & 1 / (d_m - \lambda) \end{pmatrix}[/tex]

If you now perform the matrix multiplication explicitly for a vector w = (w1, ..., wm) you will find the second expression.
 
Thank you for your quick reply. I need one more clarification.
When the author writes
[tex] 1 + \sum_{j=1}^{m} \frac{w_{j}^{2}}{d_{j} - \lambda} = 0. [/tex]

in this equation [tex]d_{j}[/tex], does this mean [tex]d_{j,j}[/tex] ?
 

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