LU solve for matrix with zeros on diagonal

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LU decomposition can be challenging when the matrix A has zeros on its diagonal, but row swapping can help mitigate this issue. However, a high condition number of 10^8 raises concerns about the stability and accuracy of the solutions derived from LU decomposition, as it may lead to significant round-off errors. It is advisable to consider alternative methods, such as singular value decomposition, to verify the solutions. The presence of NaN entries in the solution vector x indicates potential numerical instability. Overall, careful handling of the matrix's properties is essential for obtaining reliable results.
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Is it possible to obtain a solution of the linear system Ax = b with LU decomposition when A contains zeros on its diagonal? I am trying to obtain a solution with LU decomposition and then perform a forward/backward substitution but I get NaN entries in the solution vector x. The condition number of my matrix is 10^8. Appreciate any help/comments.
 
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If the matrix has 0s on the diagonal, you can get rid of those by swapping rows. Since that is a "row operation" it should not give you any trouble with finding the LU decomposition.
 
nawidgc said:
Is it possible to obtain a solution of the linear system Ax = b with LU decomposition when A contains zeros on its diagonal? I am trying to obtain a solution with LU decomposition and then perform a forward/backward substitution but I get NaN entries in the solution vector x. The condition number of my matrix is 10^8. Appreciate any help/comments.

I would be concerned trying to use LU decomp on a matrix with such a high condition number, regardless of whether there are zeroes on the main diagonal. A high condition number means that the solutions obtained from the LU decomp are subject to round-off error during their calculation, so much so that these solutions may be meaningless.

Instead of plain vanilla LU decomp, perhaps you should apply some other techniques to the matrix as well, to check your original solutions. I would recommend you try the singular value decomposition.

http://en.wikipedia.org/wiki/Condition_number

http://en.wikipedia.org/wiki/Singular_value
 
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