Matrices — Diagnostic Tests
Unit Tests
UT-1: Matrix Operations and Inverses
Question: Given A = ( 3 1 2 4 ) \mathbf{A} = \begin{pmatrix} 3 & 1 \\ 2 & 4 \end{pmatrix} A = ( 3 2 1 4 ) and B = ( 1 − 1 0 2 ) \mathbf{B} = \begin{pmatrix} 1 & -1 \\ 0 & 2 \end{pmatrix} B = ( 1 0 − 1 2 ) , (a) calculate A B \mathbf{AB} AB and B A \mathbf{BA} BA . Is matrix multiplication commutative? (b) Calculate det ( A ) \det(\mathbf{A}) det ( A ) and A − 1 \mathbf{A}^{-1} A − 1 . (c) Solve A x = ( 7 12 ) \mathbf{A}\mathbf{x} = \begin{pmatrix} 7 \\ 12 \end{pmatrix} Ax = ( 7 12 ) . (d) Calculate ( A B ) − 1 (\mathbf{AB})^{-1} ( AB ) − 1 and verify it equals B − 1 A − 1 \mathbf{B}^{-1}\mathbf{A}^{-1} B − 1 A − 1 .
Solution:
(a) A B = ( 3 1 2 4 ) ( 1 − 1 0 2 ) = ( 3 − 1 2 6 ) \mathbf{AB} = \begin{pmatrix} 3 & 1 \\ 2 & 4 \end{pmatrix}\begin{pmatrix} 1 & -1 \\ 0 & 2 \end{pmatrix} = \begin{pmatrix} 3 & -1 \\ 2 & 6 \end{pmatrix} AB = ( 3 2 1 4 ) ( 1 0 − 1 2 ) = ( 3 2 − 1 6 ) .
B A = ( 1 − 1 0 2 ) ( 3 1 2 4 ) = ( 1 − 3 4 8 ) \mathbf{BA} = \begin{pmatrix} 1 & -1 \\ 0 & 2 \end{pmatrix}\begin{pmatrix} 3 & 1 \\ 2 & 4 \end{pmatrix} = \begin{pmatrix} 1 & -3 \\ 4 & 8 \end{pmatrix} BA = ( 1 0 − 1 2 ) ( 3 2 1 4 ) = ( 1 4 − 3 8 ) .
A B ≠ B A \mathbf{AB} \ne \mathbf{BA} AB = BA , so matrix multiplication is not commutative.
(b) det ( A ) = 3 ( 4 ) − 1 ( 2 ) = 12 − 2 = 10 \det(\mathbf{A}) = 3(4) - 1(2) = 12 - 2 = 10 det ( A ) = 3 ( 4 ) − 1 ( 2 ) = 12 − 2 = 10 .
A − 1 = 1 10 ( 4 − 1 − 2 3 ) = ( 0.4 − 0.1 − 0.2 0.3 ) \mathbf{A}^{-1} = \frac{1}{10}\begin{pmatrix} 4 & -1 \\ -2 & 3 \end{pmatrix} = \begin{pmatrix} 0.4 & -0.1 \\ -0.2 & 0.3 \end{pmatrix} A − 1 = 10 1 ( 4 − 2 − 1 3 ) = ( 0.4 − 0.2 − 0.1 0.3 ) .
(c) x = A − 1 ( 7 12 ) = ( 0.4 − 0.1 − 0.2 0.3 ) ( 7 12 ) = ( 2.8 − 1.2 − 1.4 + 3.6 ) = ( 1.6 2.2 ) \mathbf{x} = \mathbf{A}^{-1}\begin{pmatrix} 7 \\ 12 \end{pmatrix} = \begin{pmatrix} 0.4 & -0.1 \\ -0.2 & 0.3 \end{pmatrix}\begin{pmatrix} 7 \\ 12 \end{pmatrix} = \begin{pmatrix} 2.8 - 1.2 \\ -1.4 + 3.6 \end{pmatrix} = \begin{pmatrix} 1.6 \\ 2.2 \end{pmatrix} x = A − 1 ( 7 12 ) = ( 0.4 − 0.2 − 0.1 0.3 ) ( 7 12 ) = ( 2.8 − 1.2 − 1.4 + 3.6 ) = ( 1.6 2.2 ) .
(d) det ( B ) = 1 ( 2 ) − ( − 1 ) ( 0 ) = 2 \det(\mathbf{B}) = 1(2) - (-1)(0) = 2 det ( B ) = 1 ( 2 ) − ( − 1 ) ( 0 ) = 2 . B − 1 = 1 2 ( 2 1 0 1 ) \mathbf{B}^{-1} = \frac{1}{2}\begin{pmatrix} 2 & 1 \\ 0 & 1 \end{pmatrix} B − 1 = 2 1 ( 2 0 1 1 ) .
B − 1 A − 1 = 1 20 ( 2 1 0 1 ) ( 4 − 1 − 2 3 ) = 1 20 ( 6 1 − 2 3 ) \mathbf{B}^{-1}\mathbf{A}^{-1} = \frac{1}{20}\begin{pmatrix} 2 & 1 \\ 0 & 1 \end{pmatrix}\begin{pmatrix} 4 & -1 \\ -2 & 3 \end{pmatrix} = \frac{1}{20}\begin{pmatrix} 6 & 1 \\ -2 & 3 \end{pmatrix} B − 1 A − 1 = 20 1 ( 2 0 1 1 ) ( 4 − 2 − 1 3 ) = 20 1 ( 6 − 2 1 3 ) .
( A B ) − 1 (\mathbf{AB})^{-1} ( AB ) − 1 : det ( A B ) = 3 ( 6 ) − ( − 1 ) ( 2 ) = 20 \det(\mathbf{AB}) = 3(6) - (-1)(2) = 20 det ( AB ) = 3 ( 6 ) − ( − 1 ) ( 2 ) = 20 .
( A B ) − 1 = 1 20 ( 6 1 − 2 3 ) (\mathbf{AB})^{-1} = \frac{1}{20}\begin{pmatrix} 6 & 1 \\ -2 & 3 \end{pmatrix} ( AB ) − 1 = 20 1 ( 6 − 2 1 3 ) . Confirmed equal.
UT-2: 3x3 Determinants and Inverses
Question: M = ( 1 2 0 0 1 3 2 0 1 ) \mathbf{M} = \begin{pmatrix} 1 & 2 & 0 \\ 0 & 1 & 3 \\ 2 & 0 & 1 \end{pmatrix} M = 1 0 2 2 1 0 0 3 1 . (a) Calculate det ( M ) \det(\mathbf{M}) det ( M ) . (b) Find M − 1 \mathbf{M}^{-1} M − 1 . (c) Solve M x = ( 5 7 4 ) \mathbf{M}\mathbf{x} = \begin{pmatrix} 5 \\ 7 \\ 4 \end{pmatrix} Mx = 5 7 4 . (d) Explain what det ( M ) = 0 \det(\mathbf{M}) = 0 det ( M ) = 0 would mean.
Solution:
(a) det ( M ) = 1 ∣ 1 3 0 1 ∣ − 2 ∣ 0 3 2 1 ∣ + 0 = 1 ( 1 − 0 ) − 2 ( 0 − 6 ) = 1 + 12 = 13 \det(\mathbf{M}) = 1\begin{vmatrix} 1 & 3 \\ 0 & 1 \end{vmatrix} - 2\begin{vmatrix} 0 & 3 \\ 2 & 1 \end{vmatrix} + 0 = 1(1 - 0) - 2(0 - 6) = 1 + 12 = 13 det ( M ) = 1 1 0 3 1 − 2 0 2 3 1 + 0 = 1 ( 1 − 0 ) − 2 ( 0 − 6 ) = 1 + 12 = 13 .
(b) Cofactors: C 11 = 1 C_{11} = 1 C 11 = 1 , C 12 = 6 C_{12} = 6 C 12 = 6 , C 13 = − 2 C_{13} = -2 C 13 = − 2 , C 21 = − 2 C_{21} = -2 C 21 = − 2 , C 22 = 1 C_{22} = 1 C 22 = 1 , C 23 = 4 C_{23} = 4 C 23 = 4 , C 31 = 6 C_{31} = 6 C 31 = 6 , C 32 = − 3 C_{32} = -3 C 32 = − 3 , C 33 = 1 C_{33} = 1 C 33 = 1 .
M − 1 = 1 13 ( 1 − 2 6 6 1 − 3 − 2 4 1 ) \mathbf{M}^{-1} = \frac{1}{13}\begin{pmatrix} 1 & -2 & 6 \\ 6 & 1 & -3 \\ -2 & 4 & 1 \end{pmatrix} M − 1 = 13 1 1 6 − 2 − 2 1 4 6 − 3 1 .
(c) x = M − 1 ( 5 7 4 ) = 1 13 ( 5 − 14 + 24 30 + 7 − 12 − 10 + 28 + 4 ) = 1 13 ( 15 25 22 ) \mathbf{x} = \mathbf{M}^{-1}\begin{pmatrix} 5 \\ 7 \\ 4 \end{pmatrix} = \frac{1}{13}\begin{pmatrix} 5 - 14 + 24 \\ 30 + 7 - 12 \\ -10 + 28 + 4 \end{pmatrix} = \frac{1}{13}\begin{pmatrix} 15 \\ 25 \\ 22 \end{pmatrix} x = M − 1 5 7 4 = 13 1 5 − 14 + 24 30 + 7 − 12 − 10 + 28 + 4 = 13 1 15 25 22 .
(d) If det ( M ) = 0 \det(\mathbf{M}) = 0 det ( M ) = 0 , the matrix is singular (non-invertible). This means: the rows (and columns) are linearly dependent, the matrix does not have full rank, the system M x = b \mathbf{M}\mathbf{x} = \mathbf{b} Mx = b has either no solution or infinitely many solutions (depending on b \mathbf{b} b ), and the corresponding linear transformation collapses the space into a lower dimension.
UT-3: Eigenvalues and Eigenvectors
Question: A = ( 4 1 2 3 ) \mathbf{A} = \begin{pmatrix} 4 & 1 \\ 2 & 3 \end{pmatrix} A = ( 4 2 1 3 ) . (a) Find the eigenvalues of A \mathbf{A} A . (b) Find the corresponding eigenvectors. (c) Form the matrix P \mathbf{P} P of eigenvectors and P − 1 A P \mathbf{P}^{-1}\mathbf{A}\mathbf{P} P − 1 AP . What form does this take? (d) Use the eigenvalues to calculate A 5 \mathbf{A}^5 A 5 .
Solution:
(a) det ( A − λ I ) = ∣ 4 − λ 1 2 3 − λ ∣ = ( 4 − λ ) ( 3 − λ ) − 2 = λ 2 − 7 λ + 10 = 0 \det(\mathbf{A} - \lambda\mathbf{I}) = \begin{vmatrix} 4-\lambda & 1 \\ 2 & 3-\lambda \end{vmatrix} = (4-\lambda)(3-\lambda) - 2 = \lambda^2 - 7\lambda + 10 = 0 det ( A − λ I ) = 4 − λ 2 1 3 − λ = ( 4 − λ ) ( 3 − λ ) − 2 = λ 2 − 7 λ + 10 = 0 .
( λ − 5 ) ( λ − 2 ) = 0 (\lambda - 5)(\lambda - 2) = 0 ( λ − 5 ) ( λ − 2 ) = 0 . Eigenvalues: λ 1 = 5 \lambda_1 = 5 λ 1 = 5 , λ 2 = 2 \lambda_2 = 2 λ 2 = 2 .
(b) For λ = 5 \lambda = 5 λ = 5 : ( A − 5 I ) v = 0 (\mathbf{A} - 5\mathbf{I})\mathbf{v} = \mathbf{0} ( A − 5 I ) v = 0 . ( − 1 1 2 − 2 ) ( x y ) = 0 \begin{pmatrix} -1 & 1 \\ 2 & -2 \end{pmatrix}\begin{pmatrix} x \\ y \end{pmatrix} = \mathbf{0} ( − 1 2 1 − 2 ) ( x y ) = 0 . − x + y = 0 -x + y = 0 − x + y = 0 , y = x y = x y = x . Eigenvector: ( 1 1 ) \begin{pmatrix} 1 \\ 1 \end{pmatrix} ( 1 1 ) .
For λ = 2 \lambda = 2 λ = 2 : ( A − 2 I ) v = 0 (\mathbf{A} - 2\mathbf{I})\mathbf{v} = \mathbf{0} ( A − 2 I ) v = 0 . ( 2 1 2 1 ) ( x y ) = 0 \begin{pmatrix} 2 & 1 \\ 2 & 1 \end{pmatrix}\begin{pmatrix} x \\ y \end{pmatrix} = \mathbf{0} ( 2 2 1 1 ) ( x y ) = 0 . 2 x + y = 0 2x + y = 0 2 x + y = 0 , y = − 2 x y = -2x y = − 2 x . Eigenvector: ( 1 − 2 ) \begin{pmatrix} 1 \\ -2 \end{pmatrix} ( 1 − 2 ) .
(c) P = ( 1 1 1 − 2 ) \mathbf{P} = \begin{pmatrix} 1 & 1 \\ 1 & -2 \end{pmatrix} P = ( 1 1 1 − 2 ) . det ( P ) = − 3 \det(\mathbf{P}) = -3 det ( P ) = − 3 . P − 1 = 1 − 3 ( − 2 − 1 − 1 1 ) = 1 3 ( 2 1 1 − 1 ) \mathbf{P}^{-1} = \frac{1}{-3}\begin{pmatrix} -2 & -1 \\ -1 & 1 \end{pmatrix} = \frac{1}{3}\begin{pmatrix} 2 & 1 \\ 1 & -1 \end{pmatrix} P − 1 = − 3 1 ( − 2 − 1 − 1 1 ) = 3 1 ( 2 1 1 − 1 ) .
D = P − 1 A P = ( 5 0 0 2 ) \mathbf{D} = \mathbf{P}^{-1}\mathbf{A}\mathbf{P} = \begin{pmatrix} 5 & 0 \\ 0 & 2 \end{pmatrix} D = P − 1 AP = ( 5 0 0 2 ) (diagonal matrix of eigenvalues).
(d) A 5 = P D 5 P − 1 = ( 1 1 1 − 2 ) ( 3125 0 0 32 ) 1 3 ( 2 1 1 − 1 ) \mathbf{A}^5 = \mathbf{P}\mathbf{D}^5\mathbf{P}^{-1} = \begin{pmatrix} 1 & 1 \\ 1 & -2 \end{pmatrix}\begin{pmatrix} 3125 & 0 \\ 0 & 32 \end{pmatrix}\frac{1}{3}\begin{pmatrix} 2 & 1 \\ 1 & -1 \end{pmatrix} A 5 = P D 5 P − 1 = ( 1 1 1 − 2 ) ( 3125 0 0 32 ) 3 1 ( 2 1 1 − 1 ) .
= 1 3 ( 3125 32 3125 − 64 ) ( 2 1 1 − 1 ) = 1 3 ( 6282 3093 6186 3189 ) = ( 2094 1031 2062 1063 ) = \frac{1}{3}\begin{pmatrix} 3125 & 32 \\ 3125 & -64 \end{pmatrix}\begin{pmatrix} 2 & 1 \\ 1 & -1 \end{pmatrix} = \frac{1}{3}\begin{pmatrix} 6282 & 3093 \\ 6186 & 3189 \end{pmatrix} = \begin{pmatrix} 2094 & 1031 \\ 2062 & 1063 \end{pmatrix} = 3 1 ( 3125 3125 32 − 64 ) ( 2 1 1 − 1 ) = 3 1 ( 6282 6186 3093 3189 ) = ( 2094 2062 1031 1063 ) .
Integration Tests
Question: The matrix T = ( 0 − 1 1 0 ) \mathbf{T} = \begin{pmatrix} 0 & -1 \\ 1 & 0 \end{pmatrix} T = ( 0 1 − 1 0 ) represents a rotation. (a) Find the angle and direction of rotation. (b) The point ( 3 , 4 ) (3, 4) ( 3 , 4 ) is transformed by T \mathbf{T} T . Calculate the image. (c) If S = ( − 1 0 0 1 ) \mathbf{S} = \begin{pmatrix} -1 & 0 \\ 0 & 1 \end{pmatrix} S = ( − 1 0 0 1 ) (reflection in the y y y -axis), find T S \mathbf{TS} TS and describe the combined transformation. (d) Calculate det ( T ) \det(\mathbf{T}) det ( T ) and det ( S ) \det(\mathbf{S}) det ( S ) , and explain how determinants relate to area scale factors.
Solution:
(a) T \mathbf{T} T maps ( 1 , 0 ) (1, 0) ( 1 , 0 ) to ( 0 , 1 ) (0, 1) ( 0 , 1 ) and ( 0 , 1 ) (0, 1) ( 0 , 1 ) to ( − 1 , 0 ) (-1, 0) ( − 1 , 0 ) . This is a rotation of 90 ∘ 90^\circ 9 0 ∘ anticlockwise about the origin.
(b) ( 0 − 1 1 0 ) ( 3 4 ) = ( − 4 3 ) \begin{pmatrix} 0 & -1 \\ 1 & 0 \end{pmatrix}\begin{pmatrix} 3 \\ 4 \end{pmatrix} = \begin{pmatrix} -4 \\ 3 \end{pmatrix} ( 0 1 − 1 0 ) ( 3 4 ) = ( − 4 3 ) . Image: ( − 4 , 3 ) (-4, 3) ( − 4 , 3 ) .
(c) T S = ( 0 − 1 1 0 ) ( − 1 0 0 1 ) = ( 0 − 1 − 1 0 ) \mathbf{TS} = \begin{pmatrix} 0 & -1 \\ 1 & 0 \end{pmatrix}\begin{pmatrix} -1 & 0 \\ 0 & 1 \end{pmatrix} = \begin{pmatrix} 0 & -1 \\ -1 & 0 \end{pmatrix} TS = ( 0 1 − 1 0 ) ( − 1 0 0 1 ) = ( 0 − 1 − 1 0 ) .
This maps ( 1 , 0 ) (1,0) ( 1 , 0 ) to ( 0 , − 1 ) (0,-1) ( 0 , − 1 ) and ( 0 , 1 ) (0,1) ( 0 , 1 ) to ( − 1 , 0 ) (-1,0) ( − 1 , 0 ) : a reflection in the line y = − x y = -x y = − x .
(d) det ( T ) = 0 × 0 − ( − 1 ) × 1 = 1 \det(\mathbf{T}) = 0 \times 0 - (-1) \times 1 = 1 det ( T ) = 0 × 0 − ( − 1 ) × 1 = 1 . det ( S ) = − 1 × 1 − 0 = − 1 \det(\mathbf{S}) = -1 \times 1 - 0 = -1 det ( S ) = − 1 × 1 − 0 = − 1 .
The absolute value of the determinant gives the area scale factor: T \mathbf{T} T preserves area (scale factor 1), S \mathbf{S} S preserves area (scale factor ∣ − 1 ∣ = 1 |-1| = 1 ∣ − 1∣ = 1 ). The sign indicates orientation: positive = = = orientation preserved (rotation), negative = = = orientation reversed (reflection).
IT-2: Systems of Linear Equations (with Complex Numbers)
Question: Solve the system: x + 2 y + z = 4 x + 2y + z = 4 x + 2 y + z = 4 , 2 x − y + 3 z = 9 2x - y + 3z = 9 2 x − y + 3 z = 9 , x + y + z = 5 x + y + z = 5 x + y + z = 5 . (a) Write in matrix form A x = b \mathbf{A}\mathbf{x} = \mathbf{b} Ax = b . (b) Calculate det ( A ) \det(\mathbf{A}) det ( A ) . (c) Find A − 1 \mathbf{A}^{-1} A − 1 and solve for x \mathbf{x} x . (d) Explain what would happen if det ( A ) = 0 \det(\mathbf{A}) = 0 det ( A ) = 0 .
Solution:
(a) ( 1 2 1 2 − 1 3 1 1 1 ) ( x y z ) = ( 4 9 5 ) \begin{pmatrix} 1 & 2 & 1 \\ 2 & -1 & 3 \\ 1 & 1 & 1 \end{pmatrix}\begin{pmatrix} x \\ y \\ z \end{pmatrix} = \begin{pmatrix} 4 \\ 9 \\ 5 \end{pmatrix} 1 2 1 2 − 1 1 1 3 1 x y z = 4 9 5 .
(b) det ( A ) = 1 ( − 1 − 3 ) − 2 ( 2 − 3 ) + 1 ( 2 + 1 ) = − 4 + 2 + 3 = 1 \det(\mathbf{A}) = 1(-1 - 3) - 2(2 - 3) + 1(2 + 1) = -4 + 2 + 3 = 1 det ( A ) = 1 ( − 1 − 3 ) − 2 ( 2 − 3 ) + 1 ( 2 + 1 ) = − 4 + 2 + 3 = 1 .
(c) Cofactors: C 11 = − 4 C_{11} = -4 C 11 = − 4 , C 12 = 1 C_{12} = 1 C 12 = 1 , C 13 = 3 C_{13} = 3 C 13 = 3 , C 21 = − 1 C_{21} = -1 C 21 = − 1 , C 22 = 0 C_{22} = 0 C 22 = 0 , C 23 = 1 C_{23} = 1 C 23 = 1 , C 31 = 7 C_{31} = 7 C 31 = 7 , C 32 = − 1 C_{32} = -1 C 32 = − 1 , C 33 = − 5 C_{33} = -5 C 33 = − 5 .
A − 1 = ( − 4 − 1 7 1 0 − 1 3 1 − 5 ) \mathbf{A}^{-1} = \begin{pmatrix} -4 & -1 & 7 \\ 1 & 0 & -1 \\ 3 & 1 & -5 \end{pmatrix} A − 1 = − 4 1 3 − 1 0 1 7 − 1 − 5 .
x = A − 1 ( 4 9 5 ) = ( − 16 − 9 + 35 4 + 0 − 5 12 + 9 − 25 ) = ( 10 − 1 − 4 ) \mathbf{x} = \mathbf{A}^{-1}\begin{pmatrix} 4 \\ 9 \\ 5 \end{pmatrix} = \begin{pmatrix} -16 - 9 + 35 \\ 4 + 0 - 5 \\ 12 + 9 - 25 \end{pmatrix} = \begin{pmatrix} 10 \\ -1 \\ -4 \end{pmatrix} x = A − 1 4 9 5 = − 16 − 9 + 35 4 + 0 − 5 12 + 9 − 25 = 10 − 1 − 4 .
x = 10 x = 10 x = 10 , y = − 1 y = -1 y = − 1 , z = − 4 z = -4 z = − 4 . Verification: 10 − 2 − 4 = 4 ✓ 10 - 2 - 4 = 4 \checkmark 10 − 2 − 4 = 4 ✓ ; 20 + 1 − 12 = 9 ✓ 20 + 1 - 12 = 9 \checkmark 20 + 1 − 12 = 9 ✓ ; 10 − 1 − 4 = 5 ✓ 10 - 1 - 4 = 5 \checkmark 10 − 1 − 4 = 5 ✓ .
(d) If det ( A ) = 0 \det(\mathbf{A}) = 0 det ( A ) = 0 , the matrix is singular and A − 1 \mathbf{A}^{-1} A − 1 does not exist. This means the three equations are linearly dependent. The system has either no unique solution: either no solution (inconsistent) or infinitely many solutions.
IT-3: Matrix Applications (with Differential Equations)
Question: The matrix A = ( 2 1 1 2 ) \mathbf{A} = \begin{pmatrix} 2 & 1 \\ 1 & 2 \end{pmatrix} A = ( 2 1 1 2 ) defines a system of coupled differential equations ◆ L B ◆ d x ◆ R B ◆◆ L B ◆ d t ◆ R B ◆ = A x \frac◆LB◆d\mathbf{x}◆RB◆◆LB◆dt◆RB◆ = \mathbf{A}\mathbf{x} L ◆ B ◆ d x ◆ R B ◆◆ L B ◆ d t ◆ R B ◆ = Ax where x = ( x y ) \mathbf{x} = \begin{pmatrix} x \\ y \end{pmatrix} x = ( x y ) . (a) Find the eigenvalues and eigenvectors of A \mathbf{A} A . (b) Write the general solution for x ( t ) \mathbf{x}(t) x ( t ) given that x ( 0 ) = ( 3 1 ) \mathbf{x}(0) = \begin{pmatrix} 3 \\ 1 \end{pmatrix} x ( 0 ) = ( 3 1 ) . (c) Calculate x ( 1 ) \mathbf{x}(1) x ( 1 ) . (d) Describe the long-term behaviour of the solution.
Solution:
(a) det ( A − λ I ) = ( 2 − λ ) 2 − 1 = λ 2 − 4 λ + 3 = 0 \det(\mathbf{A} - \lambda\mathbf{I}) = (2-\lambda)^2 - 1 = \lambda^2 - 4\lambda + 3 = 0 det ( A − λ I ) = ( 2 − λ ) 2 − 1 = λ 2 − 4 λ + 3 = 0 . λ 1 = 3 \lambda_1 = 3 λ 1 = 3 , λ 2 = 1 \lambda_2 = 1 λ 2 = 1 .
λ = 3 \lambda = 3 λ = 3 : eigenvector ( 1 1 ) \begin{pmatrix} 1 \\ 1 \end{pmatrix} ( 1 1 ) . λ = 1 \lambda = 1 λ = 1 : eigenvector ( 1 − 1 ) \begin{pmatrix} 1 \\ -1 \end{pmatrix} ( 1 − 1 ) .
(b) General solution: x ( t ) = c 1 e 3 t ( 1 1 ) + c 2 e t ( 1 − 1 ) \mathbf{x}(t) = c_1 e^{3t}\begin{pmatrix} 1 \\ 1 \end{pmatrix} + c_2 e^{t}\begin{pmatrix} 1 \\ -1 \end{pmatrix} x ( t ) = c 1 e 3 t ( 1 1 ) + c 2 e t ( 1 − 1 ) .
x ( 0 ) = c 1 ( 1 1 ) + c 2 ( 1 − 1 ) = ( 3 1 ) \mathbf{x}(0) = c_1\begin{pmatrix} 1 \\ 1 \end{pmatrix} + c_2\begin{pmatrix} 1 \\ -1 \end{pmatrix} = \begin{pmatrix} 3 \\ 1 \end{pmatrix} x ( 0 ) = c 1 ( 1 1 ) + c 2 ( 1 − 1 ) = ( 3 1 ) .
c 1 + c 2 = 3 c_1 + c_2 = 3 c 1 + c 2 = 3 and c 1 − c 2 = 1 c_1 - c_2 = 1 c 1 − c 2 = 1 . Solving: c 1 = 2 c_1 = 2 c 1 = 2 , c 2 = 1 c_2 = 1 c 2 = 1 .
x ( t ) = 2 e 3 t ( 1 1 ) + e t ( 1 − 1 ) = ( 2 e 3 t + e t 2 e 3 t − e t ) \mathbf{x}(t) = 2e^{3t}\begin{pmatrix} 1 \\ 1 \end{pmatrix} + e^{t}\begin{pmatrix} 1 \\ -1 \end{pmatrix} = \begin{pmatrix} 2e^{3t} + e^t \\ 2e^{3t} - e^t \end{pmatrix} x ( t ) = 2 e 3 t ( 1 1 ) + e t ( 1 − 1 ) = ( 2 e 3 t + e t 2 e 3 t − e t ) .
(c) x ( 1 ) = ( 2 e 3 + e 2 e 3 − e ) = ( 2 ( 20.086 ) + 2.718 2 ( 20.086 ) − 2.718 ) = ( 42.89 37.45 ) \mathbf{x}(1) = \begin{pmatrix} 2e^3 + e \\ 2e^3 - e \end{pmatrix} = \begin{pmatrix} 2(20.086) + 2.718 \\ 2(20.086) - 2.718 \end{pmatrix} = \begin{pmatrix} 42.89 \\ 37.45 \end{pmatrix} x ( 1 ) = ( 2 e 3 + e 2 e 3 − e ) = ( 2 ( 20.086 ) + 2.718 2 ( 20.086 ) − 2.718 ) = ( 42.89 37.45 ) .
(d) As t → ∞ t \to \infty t → ∞ , the term e 3 t e^{3t} e 3 t dominates (both eigenvalues are positive). Both x x x and y y y grow exponentially, with x ≈ 2 e 3 t x \approx 2e^{3t} x ≈ 2 e 3 t and y ≈ 2 e 3 t y \approx 2e^{3t} y ≈ 2 e 3 t . The solution diverges away from the origin -- the origin is an unstable node . The ratio x / y → 1 x/y \to 1 x / y → 1 as t → ∞ t \to \infty t → ∞ , meaning the trajectory approaches the direction of the eigenvector ( 1 1 ) \begin{pmatrix} 1 \\ 1 \end{pmatrix} ( 1 1 ) .