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lecture_4_slides

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↓ Slide 1

Example

Use EROs to find the intersection of the planes \begin{align*} 3x+4y+7z&=2\\x+3z&=0\\y-2z&=5\end{align*}

↓ Slide 2

Solution 1

\begin{align*} \def\go#1#2#3{\left[\begin{smallmatrix}#1\\#2\\#3\end{smallmatrix}\right]} \def\ar#1{\\\xrightarrow{#1}&} &\go{3&4&7&2}{1&0&3&0}{0&1&-2&5} \ar{\text{reorder rows}}\go{1&0&3&0}{0&1&-2&5}{3&4&7&2} \ar{R3\to R3-3R1}\go{1&0&3&0}{0&1&-2&5}{0&4&-2&2} \ar{R3\to R3-4R2}\go{1&0&3&0}{0&1&-2&5}{0&0&6&-18} \ar{R3\to \tfrac16 R3}\go{1&0&3&0}{0&1&-2&5}{0&0&1&-3} \end{align*}

$\go{1&0&3&0}{0&1&-2&5}{0&0&1&-3}$

  • from the last row, we get $z=-3$
  • from the second row, we get $y-2z=5$
    • so $y-2(-3)=5$
    • so $y=-1$
  • from the first row, we get $x+3z=0$
    • so $x+3(-3)=0$
    • so $x=9$
  • Conclusion: $\begin{bmatrix}x\\y\\z\end{bmatrix}=\begin{bmatrix}9\\-1\\-3\end{bmatrix}$ is the only solution.
↓ Slide 3

Solution 2

We start in the same way, but by performing more EROs we make the algebra at the end simpler.

\begin{align*} \def\go#1#2#3{\left[\begin{smallmatrix}#1\\#2\\#3\end{smallmatrix}\right]} \def\ar#1{\\\xrightarrow{#1}&} &\go{3&4&7&2}{1&0&3&0}{0&1&-2&5} \ar{\ldots \text{same EROs as above}\ldots}\go{1&0&3&0}{0&1&-2&5}{0&0&1&-3} \ar{R2\to R2+2R3}\go{1&0&3&0}{0&1&0&-1}{0&0&1&-3} \ar{R1\to R1-3R3}\go{1&0&0&9}{0&1&0&-1}{0&0&1&-3} \end{align*}

\[ \go{1&0&0&9}{0&1&0&-1}{0&0&1&-3}\]

  • from the last row, we get $z=-3$
  • from the second row, we get $y=-1$
  • from the first row, we get $x=9$
  • So $\begin{bmatrix}x\\y\\z\end{bmatrix}=\begin{bmatrix}9\\-1\\-3\end{bmatrix}$ is the only solution.
↓ Slide 4

Discussion

Both solutions use EROs to transform the augmented matrix.

  • Solution 1: $\left[\begin{smallmatrix}1&0&3&0\\0&1&-2&5\\0&0&1&-3\end{smallmatrix}\right]$.
    • “Staircase pattern”: 1s on “steps”, zeros below steps
    • Called row echelon form
    • Needed algebra to finish solution.
  • Solution 2: $\left[\begin{smallmatrix}1&0&0&9\\0&1&0&-1\\0&0&1&-3\end{smallmatrix}\right]$
    • Staircase with zeros above 1s on steps (and below).
    • Called reduced row echelon form
    • No extra algebra needed to finish solution.
→ Slide 5

Row echelon form and reduced row echelon form

↓ Slide 6

Row echelon form (REF)

A matrix is in row echelon form, or REF, if:

  1. the zero rows of the matrix (if any) are all at the bottom of the matrix; and
  2. in every non-zero row of the matrix, the leading entry is $1$; and
  3. as you go down the rows, the leading entries go to the right.
  • $\left[\begin{smallmatrix} 1&2&3&4&5\\0&1&2&3&4\\0&0&1&2&3\end{smallmatrix}\right]$ $\left[\begin{smallmatrix} 1&2&3&4&5\\0&1&2&3&4\\0&0&1&2&3\\0&0&0&0&0\end{smallmatrix}\right]$ $\left[\begin{smallmatrix} 1&2&3&4&5\\0&0&0&0&0\\0&0&1&2&3\end{smallmatrix}\right]$ $\left[\begin{smallmatrix} 1&2&3&4&5\\0&0&0&0&0\\0&0&1&2&3\\0&0&0&0&0\end{smallmatrix}\right]$ $\left[\begin{smallmatrix} 1&2&3&4&5\\0&2&3&4&1\\0&0&1&2&3\end{smallmatrix}\right]$ $\left[\begin{smallmatrix} 0&1&2&3&4\\1&2&3&4&5\\0&0&1&2&3\end{smallmatrix}\right]$ $\left[\begin{smallmatrix} 1&2&3&4&5\\1&5&4&3&2\\0&1&2&3&4\end{smallmatrix}\right]$
  • Which are in REF?
↓ Slide 7

Reduced row echelon form (RREF)

A matrix is in reduced row echelon form or RREF if it is in row echelon form (REF) and also has the property:

<html><ol start=“4”><li class=“level1”><div class=“li”></html> If a column contains the leading entry of a row, then every other entry in that column is $0$. <html></div></li></ol></html>

  • e.g. $\left[\begin{smallmatrix} {\color{blue}1}&{\color{red}2}&{\color{red}3}&4&5\\0&{\color{blue}1}&{\color{red}2}&3&4\\0&0&{\color{blue}1}&2&3\end{smallmatrix}\right]$ and $\left[\begin{smallmatrix} {\color{blue}1}&0&{\color{red}3}&4&5\\0&{\color{blue}1}&0&3&4\\0&0&{\color{blue}1}&2&3\end{smallmatrix}\right]$ are in REF but not RREF
  • e.g. $\left[\begin{smallmatrix} {\color{blue}1}&0&0&4&5\\0&{\color{blue}1}&0&3&4\\0&0&{\color{blue}1}&2&3\end{smallmatrix}\right]$ is in RREF.
↓ Slide 8

Example

Use EROs to put $\go{1&2&3&4&5}{0&1&2&3&4}{0&0&1&2&3}$ into RREF. Solve the corresponding linear system.

↓ Slide 9

Solution

\begin{align*} &\go{1&2&3&4&5}{0&1&2&3&4}{0&0&1&2&3} \ar{R2\to R2-2R3}\go{1&2&3&4&5}{0&1&0&-1&-2}{0&0&1&2&3} \ar{R1\to R1-3R3}\go{1&2&0&-2&-4}{0&1&0&-1&-2}{0&0&1&2&3} \ar{R1\to R1-2R2}\go{1&0&0&0&0}{0&1&0&-1&-2}{0&0&1&2&3},\text{ in RREF} \end{align*}

\[ \go{1&0&0&0&0}{0&1&0&-1&-2}{0&0&1&2&3} \]

  • Write $x_i$ for the variable corresponding to the $i$th column.
    • Column 4 has no leading variable. So we set $x_4=t$, a free parameter ($t\in\mathbb{R}$).
    • From row 3: $x_3+2t=3$, so $x_3=3-2t$
    • From row 2: $x_2-t=-2$, so $x_2=-2+t$
    • From row 1: $x_1=0$
  • Solution: $\left[\begin{smallmatrix}x_1\\x_2\\x_3\\x_4\end{smallmatrix}\right]=\left[\begin{smallmatrix}0\\-2\\3\\0\end{smallmatrix}\right]+t\left[\begin{smallmatrix}0\\1\\-2\\1\end{smallmatrix}\right],\quad t\in\mathbb{R}$.
  • (Geometrically, this is a line in 4-dimensional space $\mathbb{R}^4$).
→ Slide 10

Solving a system in REF or RREF

Given an augmented matrix in REF (or RREF), each column except the last column corresponds to a variable. These come in two types:

  • leading variables are variables whose column contains the leading entry of some row;
  • free variables are all the other variables.

To solve the corresponding linear system:

  1. assign a free parameter (a letter like $r,s,t,\dots$ representing an arbitrary real number) to each free variable
  2. starting at the bottom of the matrix, write out each row and rearrange it to give an equation for its leading variable, substituting the other variables as needed.
↓ Slide 11

Example

$\newcommand{\sm}{\left[\begin{smallmatrix}}\newcommand{\esm}{\end{smallmatrix}\right]} \sm 1&2&3&0&0&8\\0&0&1&1&1&5\\0&0&0&1&3&4\esm$ is in REF.

* Using variables $x_1,x_2,x_3,x_4,x_5$:

  • $x_1$, $x_3$ and $x_4$ are leading variables, since their columns have a leading entry
  • $x_2$ and $x_5$ are free variables, since their columns do not have a leading entry
  1. $x_2$ and $x_5$ are free, so set $x_2=s$ and $x_5=t$ where $s,t\in \mathbb{R}$
  2. Working from the bottom:
    • $ x_4+3x_5=4\implies x_4=4-3x_5=4-3t$
    • $ x_3+x_4+x_5=5\implies x_3=5-x_4-x_5=5-(4-3t)-t=1+2t$
    • $ x_1+2x_2+3x_3=8\implies x_1=8-2x_2-3x_3=8-2s-3(1+2t)=5-2s-6t.$
  • So $ \left[\begin{smallmatrix} x_1\\x_2\\x_3\\x_4 \\x_5\end{smallmatrix}\right]= \left[\begin{smallmatrix} 5\\0\\1\\4\\0\end{smallmatrix}\right] +s\left[\begin{smallmatrix} -2\\1\\0\\0\\0\end{smallmatrix}\right] +t\left[\begin{smallmatrix} -6\\0\\2\\-3\\1\end{smallmatrix}\right],\quad s,t\in \mathbb{R}.$
  • (The solution set is a $2$-dimensional subset of $5$-dimensional space).
lecture_4_slides.1454513211.txt.gz · Last modified: by rupert

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