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Chapter 4 · Determinants

Exercise 4.5 · Q3: Is x+3y=5x+3y=5⁠, 2x+6y=82x+6y=8 consistent?

Exercise 4.5Solving systems AX = B · Section 4.6
The question

Examine the consistency of the system of equations.

x+3y=52x+6y=8\begin{aligned} x+3y&=5\\ 2x+6y&=8 \end{aligned}
Exam answer

The system is AX=BAX = B⁠, where

A=[1326],X=[xy], B=[58]\begin{aligned} A &= \begin{bmatrix} 1 & 3 \\ 2 & 6 \end{bmatrix}, \\ X &= \begin{bmatrix} x \\ y \end{bmatrix},\ B = \begin{bmatrix} 5 \\ 8 \end{bmatrix} \end{aligned} ∣A∣=∣1326∣=6−6=0|A| = \begin{vmatrix} 1 & 3 \\ 2 & 6 \end{vmatrix} = 6 - 6 = 0

∣A∣=0|A| = 0⁠. So AA is singular, and we find (adj⁡A)B(\operatorname{adj}A)B⁠.

adj⁡A=[6−3−21]\operatorname{adj}A = \begin{bmatrix} 6 & -3 \\ -2 & 1 \end{bmatrix} (adj⁡A)B=[6−3−21][58]=[30−24−10+8]=[6−2]≠O\begin{aligned} (\operatorname{adj}A)B &= \begin{bmatrix} 6 & -3 \\ -2 & 1 \end{bmatrix}\begin{bmatrix} 5 \\ 8 \end{bmatrix} \\ &= \begin{bmatrix} 30 - 24 \\ -10 + 8 \end{bmatrix} \\ &= \begin{bmatrix} 6 \\ -2 \end{bmatrix} \ne O \end{aligned}

Since ∣A∣=0|A| = 0 and (adj⁡A)B≠O(\operatorname{adj}A)B \ne O⁠, the system is inconsistent.

Want the reason behind every step, the basics and the checks?

The one idea this problem is built on

Here ∣A∣=0|A| = 0⁠, so AA has no inverse and the quick test of Q1 and Q2 is not available. The book's rule for this case: compute (adj⁡A)B(\operatorname{adj}A)B⁠. If any solution XX existed, then (adj⁡A)B=(adj⁡A)AX(\operatorname{adj}A)B = (\operatorname{adj}A)AX⁠, which equals ∣A∣X=O|A|X = O⁠. We find (adj⁡A)B≠O(\operatorname{adj}A)B \ne O⁠, so no solution can exist: the system is inconsistent. In plain terms, the second left side is exactly twice the first, but 8 is not twice 5. The two lines are parallel.

Given, to find, and the plan
Given
Two linear equations in xx and yy⁠.
To find
Whether the system is consistent or inconsistent.
Plan
(1) Write AX=BAX = B⁠. (2) Compute ∣A∣|A|⁠; it is 0. (3) Understand why (adj⁡A)B(\operatorname{adj}A)B decides the matter when ∣A∣=0|A| = 0⁠. (4) Find adj⁡A\operatorname{adj}A⁠. (5) Compute (adj⁡A)B(\operatorname{adj}A)B and conclude. (6) Confirm directly from the equations and a picture.

Basics you need

1Consistent and inconsistent

Section 4.6: consistent means at least one solution exists, inconsistent means none does. For two lines: crossing (one solution), parallel and distinct (none), the same line (infinitely many). Basics: two lines, cross, parallel or the same

2The 2×22\times2 determinant

For order 2 (Section 4.2.2):

∣abcd∣=ad−cb.\begin{vmatrix}a&b\\c&d\end{vmatrix}=ad-cb.

It is 0 exactly when one row is a multiple of the other, which for two equations means the lines have the same slope. Basics: where the determinant comes from

3Theorem 1

For every square matrix, (adj⁡A)A=∣A∣I(\operatorname{adj}A)A = |A|I⁠, whether or not ∣A∣|A| is zero. This is what makes the test in Step 3 work. Basics: why the inverse divides by |A|

4The zero matrix

OO is the matrix with every entry 0. A matrix is ≠O\ne O as soon as one entry is non-zero.

Solution

  1. Write the system as AX=BAX = B

    A=[1326]X=[xy],B=[58]\begin{gathered} A=\begin{bmatrix}1&3\\2&6\end{bmatrix}\\ X=\begin{bmatrix}x\\y\end{bmatrix},\quad B=\begin{bmatrix}5\\8\end{bmatrix} \end{gathered}

    AA is 2×22\times2⁠, XX is 2×12\times1⁠, so AXAX is 2×12\times1⁠:

    AX=[1⋅x+3⋅y2⋅x+6⋅y]=[x+3y2x+6y].AX=\begin{bmatrix}1\cdot x+3\cdot y\\2\cdot x+6\cdot y\end{bmatrix}=\begin{bmatrix}x+3y\\2x+6y\end{bmatrix}.

    So AX=BAX = B is exactly the given pair of equations.

    Row 1 of AA is the coefficients of the first equation, row 2 those of the second. Already the rows look related: row 2, (2,6)(2, 6)⁠, is twice row 1, (1,3)(1, 3)⁠.
  2. Compute ∣A∣|A|

    ∣A∣=∣1326∣=1⋅6−2⋅3=6−6=0|A|=\begin{vmatrix}1&3\\2&6\end{vmatrix}=1\cdot6-2\cdot3=6-6=0

    So AA is singular and A−1A^{-1} does not exist (Theorem 4, Section 4.5).

    With ∣A∣=0|A| = 0 we cannot divide by ∣A∣|A|⁠, so the route X=A−1BX = A^{-1}B is closed. That does not yet tell us whether solutions exist: a singular system can have none or infinitely many. This is Case II of Section 4.6.1, and it needs one more calculation.
  3. Why (adj⁡A)B(\operatorname{adj}A)B decides it

    Suppose some column X0X_0 did satisfy AX0=BAX_0 = B⁠. Multiply both sides on the left by adj⁡A\operatorname{adj}A⁠:

    (adj⁡A)B=(adj⁡A)(AX0)=((adj⁡A)A)X0=(∣A∣I)X0=∣A∣ X0=0⋅X0=O\begin{aligned} (\operatorname{adj}A)B&=(\operatorname{adj}A)(AX_0)\\ &=\big((\operatorname{adj}A)A\big)X_0\\ &=\big(|A|I\big)X_0=|A|\,X_0\\ &=0\cdot X_0=O \end{aligned}

    So if a solution exists, then (adj⁡A)B=O(\operatorname{adj}A)B = O. Turned around: if (adj⁡A)B≠O(\operatorname{adj}A)B \ne O⁠, no solution can exist, and the system is inconsistent. This is the rule of Section 4.6.1, Case II.

    The second line uses associativity of matrix multiplication, and the third uses Theorem 1, (adj⁡A)A=∣A∣I(\operatorname{adj}A)A = |A|I⁠, then IX0=X0IX_0 = X_0⁠. Theorem 1 holds even when ∣A∣=0|A| = 0⁠: the book's verification of it never divides by ∣A∣|A|⁠, it only uses that a row (or column) times its own cofactors gives ∣A∣|A| and times the cofactors of a different row (or column) gives 0. The last line is 0⋅X0=O0\cdot X_0 = O because ∣A∣=0|A| = 0 here. The argument only works in one direction: (adj⁡A)B=O(\operatorname{adj}A)B = O would not prove that a solution exists. That is why the book says that in that case the system "may be either consistent or inconsistent".
    Theorem 1, Section 4.5.1. Lesson: solving systems AX = B
  4. Cofactors and adj⁡A\operatorname{adj}A

    Each minor of a 2×22\times2 matrix is the single entry left after deleting a row and a column, and Aij=(−1)i+jMijA_{ij} = (-1)^{i+j}M_{ij}⁠:

    A11=(−1)1+1(6)=6A12=(−1)1+2(2)=−2A21=(−1)2+1(3)=−3A22=(−1)2+2(1)=1\begin{aligned} A_{11}&=(-1)^{1+1}(6)=6\\ A_{12}&=(-1)^{1+2}(2)=-2\\ A_{21}&=(-1)^{2+1}(3)=-3\\ A_{22}&=(-1)^{2+2}(1)=1 \end{aligned} adj⁡A=[A11A21A12A22]=[6−3−21]\operatorname{adj}A=\begin{bmatrix}A_{11}&A_{21}\\A_{12}&A_{22}\end{bmatrix}=\begin{bmatrix}6&-3\\-2&1\end{bmatrix}
    The adjoint is the transpose of the matrix of cofactors, so A21=−3A_{21} = -3 goes to row 1, column 2. The shortcut for order 2 agrees: swap 1 and 6 on the diagonal, change the signs of 3 and 2. Cofactors exist for every square matrix; only the division by ∣A∣|A| needs ∣A∣≠0|A| \ne 0⁠.
    Definition 3, Section 4.5.1. Lesson: the adjoint
  5. Compute (adj⁡A)B(\operatorname{adj}A)B and conclude

    adj⁡A\operatorname{adj}A is 2×22\times2 and BB is 2×12\times1⁠, so the product is 2×12\times1⁠:

    (adj⁡A)B=[6−3−21][58]=[6⋅5+(−3)⋅8(−2)⋅5+1⋅8]=[30−24−10+8]=[6−2]\begin{aligned} (\operatorname{adj}A)B&=\begin{bmatrix}6&-3\\-2&1\end{bmatrix}\begin{bmatrix}5\\8\end{bmatrix}\\ &=\begin{bmatrix}6\cdot5+(-3)\cdot8\\(-2)\cdot5+1\cdot8\end{bmatrix}\\ &=\begin{bmatrix}30-24\\-10+8\end{bmatrix}=\begin{bmatrix}6\\-2\end{bmatrix} \end{aligned}

    Both entries are non-zero, so (adj⁡A)B≠O(\operatorname{adj}A)B \ne O⁠. By Step 3, the system is inconsistent: it has no solution.

    One non-zero entry would already be enough. With ∣A∣=0|A| = 0 and (adj⁡A)B≠O(\operatorname{adj}A)B \ne O⁠, Step 3 shows that assuming a solution leads to a contradiction, so none exists.
  6. See it directly in the equations

    Multiply the first equation by 2:

    2(x+3y)=2(5)gives2x+6y=10.2(x+3y)=2(5)\quad\text{gives}\quad 2x+6y=10.

    The second equation says 2x+6y=82x + 6y = 8⁠. The same quantity 2x+6y2x + 6y cannot equal both 10 and 8, so no pair (x,y)(x, y) satisfies both equations.

    −1 0 1 2 3 4 5 −1 0 1 2 x y x + 3y = 5 2x + 6y = 8 same slope −1/3, different heights: parallel, never meet
    Both lines have slope −13-\tfrac13 but cross the yy-axis at different heights, 53\tfrac53 and 43\tfrac43⁠. Parallel, distinct lines never meet: no solution.
    Solving each equation for yy gives y=5−x3y = \frac{5 - x}{3} and y=4−x3y = \frac{4 - x}{3}⁠: the same slope, different intercepts. This is the picture behind ∣A∣=0|A| = 0 (same slope) and (adj⁡A)B≠O(\operatorname{adj}A)B \ne O (different lines). Had the second equation been 2x+6y=102x + 6y = 10⁠, the lines would coincide and there would be infinitely many solutions.
    Same slope, different intercepts: parallel lines. Basics: two lines, cross, parallel or the same
Result

∣A∣=0|A| = 0 and (adj⁡A)B(\operatorname{adj}A)B has entries 6 and −2-2⁠, so (adj⁡A)B≠O(\operatorname{adj}A)B \ne O⁠. The system is inconsistent (no solution). (Textbook answer: Inconsistent.)

Check it with numbers

Try to make the first equation true and test the second. Points on x+3y=5x + 3y = 5 include (5,0)(5, 0)⁠, (2,1)(2, 1) and (−1,2)(-1, 2)⁠. For each, 2x+6y2x + 6y is 1010⁠, 4+6=104 + 6 = 10 and −2+12=10-2 + 12 = 10⁠: always 10, never 8. Every point of the first line gives 10, because 2x+6y=2(x+3y)=2⋅52x + 6y = 2(x + 3y) = 2\cdot5⁠.

And the "what if" in Step 6: with BB changed to the column with entries 5 and 10, (adj⁡A)B(\operatorname{adj}A)B has entries 30−30=030 - 30 = 0 and −10+10=0-10 + 10 = 0⁠, so it is OO⁠, matching the infinitely many solutions in that case.

Common mistakes
  1. Stopping at ∣A∣=0|A| = 0 and writing "inconsistent". ∣A∣=0|A| = 0 alone does not decide it; Q3 is inconsistent only because (adj⁡A)B≠O(\operatorname{adj}A)B \ne O⁠.
  2. Writing X=A−1BX = A^{-1}B anyway. A−1A^{-1} does not exist when ∣A∣=0|A| = 0⁠; dividing by 0 is meaningless.
  3. Thinking (adj⁡A)B=O(\operatorname{adj}A)B = O would prove consistency. The test only works one way; in that case the system needs further checking.
  4. Computing B(adj⁡A)B(\operatorname{adj}A)⁠. A 2×12\times1 times a 2×22\times2 is not even defined. The adjoint goes on the left.
What to take away
  1. When ∣A∣=0|A| = 0⁠, compute (adj⁡A)B(\operatorname{adj}A)B⁠. If it is not OO⁠, the system is inconsistent.
  2. The reason: a solution X0X_0 would force (adj⁡A)B=∣A∣X0=O(\operatorname{adj}A)B = |A|X_0 = O⁠.
  3. For two unknowns, ∣A∣=0|A| = 0 means equal slopes; then the lines are either parallel (no solution) or the same line (infinitely many).

Every fact used, and where it comes from

FactUsed inSource
Consistent and inconsistent systemsSteps 5, 6Section 4.6 (Lesson: solving systems AX = B)
2×22\times2 determinant =ad−cb= ad - cbStep 2Section 4.2.2
∣A∣=0|A| = 0 ⇒\Rightarrow no inverseStep 2Theorem 4, Section 4.5
(adj⁡A)A=∣A∣I(\operatorname{adj}A)A = |A|IStep 3Theorem 1, Section 4.5.1
∣A∣=0|A| = 0 and (adj⁡A)B≠O(\operatorname{adj}A)B \ne O ⇒\Rightarrow inconsistentSteps 3, 5Section 4.6.1, Case II
Aij=(−1)i+jMijA_{ij} = (-1)^{i+j}M_{ij}⁠; adjoint = transpose of cofactor matrixStep 4Definitions 1, 2 (Section 4.4) and 3 (Section 4.5.1)
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