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Numerical analysis Definition

Sparse matrix

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Definition

Let AA be an m×nm \times n matrix, and let nnz⁡(A)\operatorname{nnz}(A) be the number of its nonzero entries. The matrix AA is sparse when nnz⁡(A)\operatorname{nnz}(A) is small compared with mnmn, so that it pays to store and process only the nonzero entries. For a family of n×nn \times n matrices with nn growing, a common precise form of this condition is nnz⁡(A)=O(n)\operatorname{nnz}(A) = O(n).

Remarks

The notion has no fixed threshold; it depends on the size of the matrix and on the algorithms in use. The density of AA is nnz⁡(A)/(mn)\operatorname{nnz}(A) / (mn), and a matrix that is not sparse is called dense. Example: the n×nn \times n tridiagonal matrix with 22 on the diagonal and −1-1 beside it has 3n−23n - 2 nonzero entries, which is O(n)O(n), so the family is sparse. Non-example: the n×nn \times n matrix with all entries 11 has n2n^2 nonzero entries, so it is dense. Common storage formats are the coordinate list and the compressed sparse row format.

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Further reading

  1. Web https://en.wikipedia.org/wiki/Sparse_matrix
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Changed2 November 2026

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