Symbolic Cholesky decomposition

In the mathematical subfield of numerical analysis the symbolic Cholesky decomposition is an algorithm used to determine the non-zero pattern for the L {\displaystyle L} factors of a symmetric sparse matrix when applying the Cholesky decomposition or variants. == Algorithm == Let A = ( a i j ) ∈ K n × n {\displaystyle A=(a_{ij})\in \mathbb {K} ^{n\times n}} be a sparse symmetric positive definite matrix with elements from a field K {\displaystyle \mathbb {K} } , which we wish to factorize as A = L L T {\displaystyle A=LL^{T}\,} .

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Symbolic Cholesky decomposition

In the mathematical subfield of numerical analysis the symbolic Cholesky decomposition is an algorithm used to determine the non-zero pattern for the L {\displaystyle L} factors of a symmetric sparse matrix when applying the Cholesky decomposition or variants. == Algorithm == Let A = ( a i j ) ∈ K n × n {\displaystyle A=(a_{ij})\in \mathbb {K} ^{n\times n}} be a sparse symmetric positive definite matrix with elements from a field K {\displaystyle \mathbb {K} } , which we wish to factorize as A = L L T {\displaystyle A=LL^{T}\,} .

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Source: Wikipedia "Symbolic Cholesky decomposition" · CC BY-SA 4.0

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