Learn Cholesky Algorithm for Reducing Matrices by Thursday

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The discussion focuses on understanding the Cholesky method for matrix reduction ahead of an upcoming test. The original poster seeks clarity on applying the algorithm, particularly how to compute elements like l21 and l22 after establishing the first column. A response provides a brief explanation of Cholesky decomposition, noting that it involves decomposing a Hermitian positive-definite matrix into a product of a lower triangular matrix and its conjugate transpose. Additional resources, such as a Wikipedia article, are suggested for further examples and clarification. Mastery of the Cholesky algorithm is essential for effective matrix reduction in mathematical applications.
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This is not a homework question per se, but i would like to understnad the cholesky method of reducing matrices before my test on thursday

up till now every search on the net has found me computer algorithms but i can't really understand those and apply those pracitcally

so givne some matrix
\left(\begin{array}{ccc} 2&-1&0\\-1&2&-1\\0&-1&2\end{array}\right)
i know for the first column let l_{11} = \sqrt{a_{11}}
and thereafter l_{j1}=\frac{a_{j1}}{l_{11}}
but what happens for l21,l22, and so on??
Please help me out i really need to understand this!

Thank you in advance
 
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Presumably the OP found an answer to the question, but if not or if others have the same question, here's some more information, based on this wiki article: https://en.wikipedia.org/wiki/Cholesky_decomposition
Starting with a Hermitian positive-definite matrix A, Cholesky decomposition decomposes A into a matrix product LL*, with L being a lower triangular matrix with real and positive entries on the diagonal, and L*, the complex conjugate transpose of L.
A few examples are shown on the wiki page in the link above.
 
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