They may be produced by right-multiplying a column vector by a row vector, and have unique inverses if their determinants are nonzero.
The existence of a singular value decomposition for these objects is guaranteed by the spectral theorem. Multiplying them together corresponds to composing linear maps. The roots of the characteristic equation of one of these objects are its eigenvalues. Collections of derivatives named for Jacobi and Hesse are examples of them. Symmetric ones are equal to their own transpose. One property of these objects is computed by cofactor expansion or by row reduction. They may be produced by right-multiplying a column vector by a row vector, and have unique inverses if their determinants are nonzero. For 10 points, name these arrays of numbers with rows and columns.
The existence of a singular value decomposition for these objects is guaranteed by the spectral theorem.
matrix [or matrices; accept Jacobian matrix; accept Hessian matrix; accept symmetric matrix; accept square matrix] &lt;AD&gt;