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Table of Contents
Last time
If $A$ is an invertible $n\times n$ matrix, then the unique $n\times n$ matrix $C$ with $AC=I_n=CA$ is called the inverse of $A$. If $A$ is invertible, then we write $A^{-1}$ to mean the (unique) inverse of $A$.
- $\def\mat#1{\left[\begin{smallmatrix}#1\end{smallmatrix}\right]}A=\mat{2&4\\0&1}$ is invertible, and $A^{-1}=\mat{\tfrac12&-2\\0&1}$.
- i.e. $\mat{2&4\\0&1}^{-1}=\mat{\tfrac12&-2\\0&1}$
- if $a$ is a non-zero scalar, then $[a]^{-1}=[\tfrac 1a]$
- $I_n^{-1}=I_n$ for any $n$
- $0_{n\times n}^{-1}$, $\mat{1&0\\0&0}^{-1}$ and $\mat{1&2\\-3&-6}^{-1}$ do not exist
- because these matrices aren't invertible
Warning
If $A$, $B$ are matrices, then $\frac AB$ doesn't make sense!
- Never write this down as it will almost always lead to mistakes.
- In particular, $A^{-1}$ definitely doesn't mean $\frac 1A$. Never write this either!
Proposition: solving $AX=B$ when $A$ is invertible
If $A$ is an invertible $n\times n$ matrix and $B$ is an $n\times k$ matrix, then $ AX=B$ has a unique solution: $X=A^{-1}B$.
Proof
- First check that $X=A^{-1}B$ really is a solution:
- $AX=A(A^{-1}B)=(AA^{-1})B=I_nB=B$
- Uniqueness: suppose $X$ and $Y$ are both solutions
- Then $AX=B$ and $AY=B$, so $AX=AY$.
- Multiply both sides on the left by $A^{-1}$:
- $A^{-1}AX=A^{-1}AY$, or $I_nX=I_n Y$, or $X=Y$.
- So any two solutions are equal.■
Corollary
If $A$ is an $n\times n$ matrix and there is a non-zero $n\times m$ matrix $K$ so that $AK=0_{n\times m}$, then $A$ is not invertible.
Proof
- $AX=0_{n\times m}$ has (at least) two solutions:
- $X=K$,
- and $X=0_{n\times m}$
- If $A$ was invertible, this would contradict the Proposition.
- So $A$ cannot be invertible. ■
Example
- Let $A=\mat{1&2\\-3&-6}$. $A$ isn't invertible… why?
- One column of $A$ is $2$ times the other… exploit this.
- Let $K=\mat{-2\\1}$
- $K$ is non-zero but $AK=\mat{1&2\\-3&-6}\mat{-2\\1}=\mat{0\\0}=0_{2\times 1}$
- So $A$ is not invertible, by the Corollary.
Example
- $A=\mat{1&4&5\\2&5&7\\3&6&9}$ is not invertible
- $X=\mat{1\\1\\-1}$ is non-zero
- and $AX=0_{3\times 1}$.
$2\times 2$ matrices: determinants and invertibility
Question
Which $2\times 2$ matrices are invertible? For the invertible matrices, can we find their inverse?
Lemma
If $A=\mat{a&b\\c&d}$ and $J=\mat{d&-b\\-c&a}$, then we have \[ AJ=\delta I_2=JA\] where $\delta=ad-bc$.
- Proof is a calculation!
Definition: the determinant of a $2\times 2$ matrix
The number $ad-bc$ is called the determinant of the $2\times 2$ matrix $A=\mat{a&b\\c&d}$. We write $\det(A)=ad-bc$ for this number.
Theorem: the determinant determines the invertibility (and inverse) of a $2\times 2$ matrix
Let $A=\mat{a&b\\c&d}$ be a $2\times 2$ matrix.
- $A$ is invertible if and only if $\det(A)\ne0$.
- If $A$ is invertible, then $A^{-1}=\frac{1}{\det(A)}\mat{d&-b\\-c&a}$.
Proof
- true for $A=0_{2\times 2}$!
- Now suppose $A\ne0_{2\times 2}$. Let $J=\mat{d&-b\\-c&a}$.
- By the previous lemma, $AJ=(\det(A))I_2=JA$.
- If $\det(A)\ne0$, multiply by $\frac1{\det(A)}$ and write $B=\tfrac1{\det(A)}J$: \[ AB= A(\tfrac1{\det(A)}J)=I_2=(\tfrac1{\det(A)}J) A=BA\]
- So $ AB=I_2=BA$, so $A$ invertible with inverse $B=\frac1{\det(A)}J=\frac1{\det(A)}\mat{d&-b\\-c&a}$.
- If $\det(A)=0$, then $AJ=0_{2\times 2}$ and $J\ne 0_{2\times2}$ [why?]
- Hence by the previous corollary, $A$ is not invertible in this case. ■
The transpose of a matrix
We defined this in tutorial sheet 4:
The transpose of an $n\times m$ matrix $A$ is the $m\times n$ matrix $A^T$ whose $(i,j)$ entry is the $(j,i)$ entry of $A$. In other words, to get $A^T$ from $A$, you write the rows of $A$ as columns, and vice versa; equivalently, you reflect $A$ in its main diagonal.
For example, $\def\mat#1{\begin{bmatrix}#1\end{bmatrix}}\mat{a&b\\c&d}^T=\mat{a&c\\b&d}$ and $\mat{1&2&3\\4&5&6}^T=\mat{1&4\\2&5\\3&6}$.
Exercise: simple properties of the transpose
Prove that for any matrix $A$:
- $(A^T)^T=A$; and
- $(A+B)^T=A^T+B^T$ if $A$ and $B$ are matrices of the same size; and
- $(cA)^T=c(A^T)$ for any scalar $c$.
In tutorial sheet 4, we proved:
Lemma: transposes and row-column multiplication
If $a$ is a $1\times m$ row vector and $b$ is an $m\times 1$ column vector, then \[ ab=b^Ta^T.\]
Examples
- $\det\mat{2&3\\-4&-6}=2(-6)-3(-4)=-12-(-12)=0$
- so $\mat{2&3\\-4&-6}$ is not invertible.
- $\det\mat{2&3\\-4&5}=2(5)-3(-4)=10-(-12)=22\ne0$
- so $\mat{2&3\\-4&5}$ is invertible
- with inverse \[\mat{2&3\\-4&5}^{-1}=\frac1{22}\mat{5&-3\\4&2} = \mat{\frac 5{22}&-\frac3{22}\\\frac2{11}&\frac1{11}}.\]
Using the inverse to solve a matrix equation
- Solve $\mat{1&5\\3&-2}X=\mat{4&1&0\\0&2&1}$ for $X$
- Write $A=\mat{1&5\\3&-2}$
- $\det(A)=1(-2)-5(3)=-2-15=-17$
- So $A$ is invertible, and $A^{-1}=-\tfrac1{17}\mat{-2&3\\5&1}$
- Solution is $X=A^{-1}\mat{4&1&0\\0&2&1}=-\tfrac1{17}\mat{-2&-5\\-3&1}\mat{4&1&0\\0&2&1}$

