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Determinants of Manipulated Matrices
How to Examples Exercise How to: In this section, we're going to look at what happens when we manipulate matrices, such as in the steps of Gauss-Jordan Elimination. Let's assume we have an NxN matrix, A = [v1 v2 v3 .. vN], where the v#'s are 1xN column vectors. What happens if we multiply one of the columns, say v2, by a scalar k: det([v1 k*v2 v3 ... vN]) = k*det([v1 v2 ... vN]) That is to say, changing a column by a scalar multiple, also changes the determinant by a scalar multiple. Now, let's assume A is composed of Nx1 row vectors, that is A = [v1; v2; ...; vN]. In performing Gauss-Jordan, we manipulate a matrix in three different ways: 1) Divide a row by a scalar, k 2) Swap rows 3) Add a scalar multiple of one row to another In all of these cases, the determinant of the new matrix is easily calculated knowing the determinant of the old matrix:
So, in Case (1) above, the determinant is also divided by k; in Case (2) we get the negative of our current determinant; and in Case (3) the determinant is unchanged. Examples: Here will be a good review of Gauss-Jordan Elimination. Starting with the matrix A = [3 6 6; 2 4 17; 2 6 14], whose determinant is det(A) = -78, let's put it into RREF, step-by-step, and keep track of the determinant along the way.
Our resulting matrix is simply the identity matrix, which we know always has a determinant of 1. But, keeping track of the determinant, step-by-step, as it changed, also gave us a result of 1. Exercise: | ||||||||||||||||||||||||||||