2×2 determinant
|a b; c d| = ad − bcMultiply the main diagonal, subtract the product of the other diagonal.
Enter integers, decimals, or scientific notation. Display precision does not round intermediate calculations.
Choose a row and calculate to see its alternating signs and cofactor contributions.
The selected row is used first. Inside each minor, the calculator chooses a row with the most zeros; open a contribution to follow that recursive expansion.
|a b; c d| = ad − bcMultiply the main diagonal, subtract the product of the other diagonal.
Cᵢⱼ = (−1)ⁱ⁺ʲ det(Mᵢⱼ)Mᵢⱼ is formed by deleting row i and column j. Here the displayed indices start at 1.
det(A) = Σⱼ aᵢⱼ CᵢⱼThe sign pattern alternates like a checkerboard, beginning with plus at position (1,1).
10⁵⁰ in magnitude. The chosen decimal places affect display only, and tiny cancellation residue may appear for decimal matrices.For A = [[2,−3,1],[2,0,−1],[1,4,5]], expanding along row 1 gives:
det(A) = 2(0·5 − (−1)·4) − (−3)(2·5 − (−1)·1) + 1(2·4 − 0·1) = 49
If an expansion entry is zero, its entire contribution is zero, so that minor determinant does not need to be evaluated.
Expanding the same matrix along row 2 or row 3 rearranges the arithmetic but still gives 49.
The absolute determinant is the factor by which a linear transformation scales area in two dimensions or volume in three dimensions. Its sign records orientation. A determinant of zero means the transformation collapses at least one dimension, so the matrix is singular and has no inverse.
Cofactor expansion is especially useful for learning, proofs, and matrices with many zeros. For large dense matrices, elimination-based methods such as LU decomposition are usually more efficient.
It is a single number defined for a square matrix. It describes signed scaling and helps determine whether the matrix is invertible.
It expresses a determinant as a sum of entries from one row or column, each multiplied by its alternating sign and minor determinant.
Yes. Every row and every column produces the same determinant. Choosing a row or column with many zeros usually shortens the work.
The rows or columns are linearly dependent, the matrix has no inverse, and the corresponding transformation collapses space into a lower dimension.
Recursive cofactor expansion grows very quickly. The limit keeps the complete step-by-step tree usable; elimination-based methods are better suited to larger dense matrices.
Binary floating-point cannot represent every decimal exactly, and subtraction can expose a small rounding residue. Increase or decrease displayed precision according to the accuracy of the inputs.
Yes. This page performs parsing, calculation, copying, and file creation locally. Its calculator code does not transmit or store your entries.
Last reviewed: August 4, 2026 by the Starlight Tools editorial team.
The calculator performs literal recursive cofactor expansion, skipping branches whose coefficient is exactly zero. It does not round intermediate values. Results for ill-conditioned decimal matrices should be interpreted at the precision justified by the input data.