Matrix Determinant det() Function

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A Matrix Determinant det() Function is a matrix function [math]\displaystyle{ \sum_{\sigma \in S_n} \operatorname{sgn}(\sigma) \prod_{i=1}^n A_{i,\sigma_i}.\ }[/math], for square matrix [math]\displaystyle{ A }[/math] of size [math]\displaystyle{ n }[/math], where [math]\displaystyle{ \S_n }[/math] is set of permutations of the numbers [math]\displaystyle{ {1,2,....n} }[/math], [math]\displaystyle{ \sigma }[/math] is a single permutation taken out of that set and [math]\displaystyle{ \operatorname{sgn}(\sigma) }[/math] is a signator function (that returns +1 if the permutation [math]\displaystyle{ \sigma }[/math] is even and -1 if the permutation [math]\displaystyle{ \sigma }[/math] is odd). \sigma(i), then, is the i-th element of the permutation [math]\displaystyle{ \sigma }[/math].



References

2013

  • http://en.wikipedia.org/wiki/Determinant
    • In linear algebra, the determinant is a value associated with a square matrix. It can be computed from the entries of the matrix by a specific arithmetic expression, while other ways to determine its value exist as well. The determinant provides important information when the matrix is that of the coefficients of a system of linear equations, or when it corresponds to a linear transformation of a vector space: in the first case the system has a unique solution exactly when the determinant is nonzero; when the determinant is zero there are either no solutions or many solutions. In the second case that same condition means that the transformation has an inverse operation. A geometric interpretation can be given to the value of the determinant of a square matrix with real entries: the absolute value of the determinant gives the scale factor by which area or volume is multiplied under the associated linear transformation, while its sign indicates whether the transformation preserves orientation. Thus a 2 × 2 matrix with determinant −2, when applied to a region of the plane with finite area, will transform that region into one with twice the area, while reversing its orientation.

      Determinants occur throughout mathematics. The use of determinants in calculus includes the Jacobian determinant in the substitution rule for integrals of functions of several variables. They are used to define the characteristic polynomial of a matrix that is an essential tool in eigenvalue problems in linear algebra. In some cases they are used just as a compact notation for expressions that would otherwise be unwieldy to write down.

      The determinant of a matrix A is denoted det(A), det A, or |A|.[1] In the case where the matrix entries are written out in full, the determinant is denoted by surrounding the matrix entries by vertical bars instead of the brackets or parentheses of the matrix. For instance, the determinant of the matrix :[math]\displaystyle{ \begin{bmatrix}a&b&c\\d&e&f\\g&h&i\end{bmatrix} }[/math]

      is written :[math]\displaystyle{ \begin{vmatrix} a & b & c\\d & e & f\\g & h & i \end{vmatrix} }[/math] and has the value [math]\displaystyle{ aei+bfg+cdh-ceg-bdi-afh.\, }[/math]

      Although most often used for matrices whose entries are real or complex numbers, the definition of the determinant only involves addition, subtraction and multiplication, and so it can be defined for square matrices with entries taken from any commutative ring. Thus for instance the determinant of a matrix with integer coefficients will be an integer, and the matrix has an inverse with integer coefficients if and only if this determinant is 1 or −1 (these being the only invertible elements of the integers). For square matrices with entries in a non-commutative ring, for instance the quaternions, there is no unique definition for the determinant, and no definition that has all the usual properties of determinants over commutative rings.