In this unit, we introduce the concept of the determinant of a square matrix. The determinant is a function that associates a unique real number with any square matrix A. This number is denoted det(A), or |A|. The determinant of a matrix conveys some very important information.
If a and b are real numbers, then we know that the equation ax = b has the unique solution x = b/a, so long as a ≠ 0.
Another way of looking at this equation is to think of the coefficient a as a 1 × 1 matrix. Then the inverse, a-1 is just 1/a and we see that our solution is x = a-1b.
If a = 0, however, no solution exists, since we cannot divide by 0. The real number 0, considered as a matrix, has no inverse. In this unit, we will show that this relationship has an equivalent for any square matrix. That is, if A is any square matrix, then A-1 will exist, and hence Ax = b will have the unique solution x = A-1b if and only if det(A) ≠ 0.
In this unit, you will learn how to evaluate the determinant of a matrix by the method of cofactor expansion.
We also discuss how to find the cofactor matrix of a given square matrix, and based on this technique, the adjoint matrix. This process will lead to a formula for the inverse of an invertible matrix, which is of great theoretical importance.
Next, we consider Cramer’s Rule, a method for computing the solution to a system of n linear equations in n unknowns on the basis of the computation of n + 1 determinants. This method is particularly useful in computer applications, where programs for computing determinants are popular.
When you have completed this unit, you should be able to