En Matemáticas se define el determinante como una forma multilineal alternada de un cuerpo. Esta definición indica una serie de propiedades matemáticas y generaliza el concepto de determinante haciéndolo aplicable en numerosos campos. Sin embargo, el concepto de determinante o de volumen orientado fue introducido para estudiar el número de soluciones de los sistemas de ecuaciones lineales.

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In linear algebra, the determinant is a useful value that can be computed from the elements of a square matrix. The determinant of a matrix A is denoted det(A), detA , or |A|. It can be viewed as the scaling factor of the transformation described by the matrix. In the case of a 2 × 2 matrix, the specific formula for the determinant: Similarly, suppose we have a 3 × 3 matrix A, and we want the specific formula for its determinant |A|: Each determinant of a 2 × 2 matrix in this equation is called a "minor" of the matrix A. The same sort of procedure can be used to find the determinant of a 4 × 4 matrix, the determinant of a 5 × 5 matrix, and so forth. Determinants occur throughout mathematics. For example, a matrix is often used to represent the coefficients in a system of linear equations, and the determinant can be used to solve those equations, although more efficient techniques are actually used, some of which are determinant-revealing and consist of computationally effective ways of computing the determinant itself. The use of determinants in calculus includes the Jacobian determinant in the change of variables rule for integrals of functions of several variables. Determinants are also used to define the characteristic polynomial of a matrix, which is essential for eigenvalue problems in linear algebra. In analytical geometry, determinants express the signed n-dimensional volumes of n-dimensional parallelepipeds. Sometimes, determinants are used merely as a compact notation for expressions that would otherwise be unwieldy to write down. When the entries of the matrix are taken from a field (like the real or complex numbers), it can be proven that any matrix has a unique inverse if and only if its determinant is nonzero. Various other theorems can be proved as well, including that the determinant of a product of matrices is always equal to the product of determinants; and, the determinant of a Hermitian matrix is always real.

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