20. Inverses

20. Inverses

In the next few videos, we're going to answer the question: can you divide by a matrix?

Theorem:

If M = ( a b c d ) is a 2-by-2 matrix with a ⁢ d - b ⁢ c ≠ 0 then the matrix M - 1 = 1 a ⁢ d - b ⁢ c ⁢ ( d - b - c a ) satisfies M - 1 ⁢ M = M ⁢ M - 1 = I . We say that M - 1 is the inverse of M .

This is the analogue of the reciprocal x - 1 = 1 / x of a number: the equation M - 1 ⁢ M = I is the analogue of x - 1 ⁢ x = 1 .

Let's just check M - 1 ⁢ M = I (check the other equality for yourself). 1 a ⁢ d - b ⁢ c ⁢ ( d - b - c a ) ⁢ ( a b c d ) = 1 a ⁢ d - b ⁢ c ⁢ ( d ⁢ a - b ⁢ c d ⁢ b - b ⁢ d - c ⁢ a + a ⁢ c - c ⁢ b + a ⁢ d ) = ( 1 0 0 1 ) = I .

We can use this to "divide" by a matrix: if we have a matrix equation A ⁢ B = C then we can multiply both sides on the left by A - 1 to get A - 1 ⁢ A ⁢ B = A - 1 ⁢ C , and since A - 1 ⁢ A = I this means B = A - 1 ⁢ C .

With great power comes great responsibility: you should never write B A for matrices A , B ! It's not clear if you're doing A - 1 ⁢ B or B ⁢ A - 1 (and these are different because A - 1 and B might not commute).

We can use inverses to solve simultaneous equations. For example: x - y = - 1 , x + y = 3 is equivalent to A ⁢ v = b where A = ( 1 - 1 1 1 ) and b = ( - 1 3 ) . We can compute A - 1 = 1 2 ⁢ ( 1 1 - 1 1 ) , so v = A - 1 ⁢ b = 1 2 ⁢ ( 1 1 - 1 1 ) ⁢ ( - 1 3 ) = ( 1 2 ) , and this coincides with the solution x = 1 , y = 2 we found earlier.

Bigger matrices

We'd like to generalise the notion of inverse to bigger matrices.

Definition:

Let A be an n -by- n matrix. We say that A is invertible if there exists a matrix B such that A ⁢ B = B ⁢ A = I . (Here I is the n -by- n identity matrix). If such a B exists, then it's unique, so we're justified in calling it the inverse of A and writing it as A - 1 .

To see that the inverse is unique when it exists, suppose you had two inverses B , C for A : A ⁢ B = A ⁢ C = I , B ⁢ A = C ⁢ A = I . Now evaluate B ⁢ A ⁢ C in two ways:

  • B ⁢ A ⁢ C = ( B ⁢ A ) ⁢ C = I ⁢ C = C ,

  • B ⁢ A ⁢ C = B ⁢ ( A ⁢ C ) = B ⁢ I = B ,

so C = B ⁢ A ⁢ C = B .

Lemma:

If A , B are invertible matrices then A ⁢ B is invertible with inverse ( A ⁢ B ) - 1 = B - 1 ⁢ A - 1 .

we have ( A ⁢ B ) ⁢ ( B - 1 ⁢ A - 1 ) = A ⁢ ( B ⁢ B - 1 ) ⁢ A - 1 = A ⁢ I ⁢ A - 1 = A ⁢ A - 1 = I and ( B - 1 ⁢ A - 1 ) ⁢ ( A ⁢ B ) = B - 1 ⁢ ( A - 1 ⁢ A ) ⁢ B = B - 1 ⁢ I ⁢ B = B - 1 ⁢ B = I , so B - 1 ⁢ A - 1 is an inverse for A ⁢ B .

Had we tried to use A - 1 ⁢ B - 1 instead, we would have obtained A ⁢ B ⁢ A - 1 ⁢ B - 1 , and we couldn't have cancelled anything because the various terms don't commute.

We saw for 2-by-2 matrices that a matrix is invertible if a ⁢ d - b ⁢ c ≠ 0 . Even more basically, a 1-by-1 matrix ( x ) is invertible if and only if x ≠ 0 . We'll see in a few videos' time that there is an analogous quantity (the determinant) det ⁡ ( A ) which is nonzero precisely when A is invertible. First though, we're going to explain how to calculate inverses of n -by- n matrices.