Sample Solution

BMTE-141-Sample-Solution

bmte-141-sample-solution-00121e82-06b0-4090-b5ab-7e9d6642f92d

  1. i) Find the angle between the vectors 2 i + 2 j + 2 k 2 i + 2 j + 2 k sqrt2i+2j+2k\sqrt{2} \mathbf{i}+2 \mathbf{j}+2 \mathbf{k}2i+2j+2k and i + 2 j + 2 k i + 2 j + 2 k i+sqrt2j+sqrt2k\mathbf{i}+\sqrt{2} \mathbf{j}+\sqrt{2} \mathbf{k}i+2j+2k.
Answer:
To find the angle between two vectors, we use the dot product formula. The dot product of two vectors A A A\mathbf{A}A and B B B\mathbf{B}B is given by A B = | A | | B | cos ( θ ) A B = | A | | B | cos ( θ ) A*B=|A||B|cos(theta)\mathbf{A} \cdot \mathbf{B} = |\mathbf{A}| |\mathbf{B}| \cos(\theta)AB=|A||B|cos(θ), where θ θ theta\thetaθ is the angle between the vectors, and | A | | A | |A||\mathbf{A}||A| and | B | | B | |B||\mathbf{B}||B| are the magnitudes of the vectors.
The vectors given are A = 2 i + 2 j + 2 k A = 2 i + 2 j + 2 k A=sqrt2i+2j+2k\mathbf{A} = \sqrt{2} \mathbf{i} + 2 \mathbf{j} + 2 \mathbf{k}A=2i+2j+2k and B = i + 2 j + 2 k B = i + 2 j + 2 k B=i+sqrt2j+sqrt2k\mathbf{B} = \mathbf{i} + \sqrt{2} \mathbf{j} + \sqrt{2} \mathbf{k}B=i+2j+2k.
  1. Calculate the Dot Product A B A B A*B\mathbf{A} \cdot \mathbf{B}AB:
    A B = ( 2 i + 2 j + 2 k ) ( i + 2 j + 2 k ) A B = ( 2 i + 2 j + 2 k ) ( i + 2 j + 2 k ) A*B=(sqrt2i+2j+2k)*(i+sqrt2j+sqrt2k)\mathbf{A} \cdot \mathbf{B} = (\sqrt{2}\mathbf{i} + 2\mathbf{j} + 2\mathbf{k}) \cdot (\mathbf{i} + \sqrt{2}\mathbf{j} + \sqrt{2}\mathbf{k})AB=(2i+2j+2k)(i+2j+2k)
    = 2 1 + 2 2 + 2 2 = 2 1 + 2 2 + 2 2 =sqrt2*1+2*sqrt2+2*sqrt2= \sqrt{2} \cdot 1 + 2 \cdot \sqrt{2} + 2 \cdot \sqrt{2}=21+22+22
  2. Calculate the Magnitudes of A A A\mathbf{A}A and B B B\mathbf{B}B:
    • Magnitude of A A A\mathbf{A}A, | A | | A | |A||\mathbf{A}||A|: | A | = ( 2 ) 2 + 2 2 + 2 2 | A | = ( 2 ) 2 + 2 2 + 2 2 |A|=sqrt((sqrt2)^(2)+2^(2)+2^(2))|\mathbf{A}| = \sqrt{(\sqrt{2})^2 + 2^2 + 2^2}|A|=(2)2+22+22
    • Magnitude of B B B\mathbf{B}B, | B | | B | |B||\mathbf{B}||B|: | B | = 1 2 + ( 2 ) 2 + ( 2 ) 2 | B | = 1 2 + ( 2 ) 2 + ( 2 ) 2 |B|=sqrt(1^(2)+(sqrt2)^(2)+(sqrt2)^(2))|\mathbf{B}| = \sqrt{1^2 + (\sqrt{2})^2 + (\sqrt{2})^2}|B|=12+(2)2+(2)2
  3. Find the Angle θ θ theta\thetaθ:
    cos ( θ ) = A B | A | | B | cos ( θ ) = A B | A | | B | cos(theta)=(A*B)/(|A||B|)\cos(\theta) = \frac{\mathbf{A} \cdot \mathbf{B}}{|\mathbf{A}| |\mathbf{B}|}cos(θ)=AB|A||B|
    θ = cos 1 ( A B | A | | B | ) θ = cos 1 A B | A | | B | theta=cos^(-1)((A*B)/(|A||B|))\theta = \cos^{-1}\left(\frac{\mathbf{A} \cdot \mathbf{B}}{|\mathbf{A}| |\mathbf{B}|}\right)θ=cos1(AB|A||B|)
    We will calculate θ θ theta\thetaθ after obtaining the dot product and magnitudes.
Let’s start by calculating the dot product and the magnitudes.
After calculating, we have the following results:
  1. Dot Product A B A B A*B\mathbf{A} \cdot \mathbf{B}AB:
    A B = 2 1 + 2 2 + 2 2 = 5 2 A B = 2 1 + 2 2 + 2 2 = 5 2 A*B=sqrt2*1+2*sqrt2+2*sqrt2=5sqrt2\mathbf{A} \cdot \mathbf{B} = \sqrt{2} \cdot 1 + 2 \cdot \sqrt{2} + 2 \cdot \sqrt{2} = 5\sqrt{2}AB=21+22+22=52
  2. Magnitude of A A A\mathbf{A}A, | A | | A | |A||\mathbf{A}||A|:
    | A | = ( 2 ) 2 + 2 2 + 2 2 = 10 | A | = ( 2 ) 2 + 2 2 + 2 2 = 10 |A|=sqrt((sqrt2)^(2)+2^(2)+2^(2))=sqrt10|\mathbf{A}| = \sqrt{(\sqrt{2})^2 + 2^2 + 2^2} = \sqrt{10}|A|=(2)2+22+22=10
  3. Magnitude of B B B\mathbf{B}B, | B | | B | |B||\mathbf{B}||B|:
    | B | = 1 2 + ( 2 ) 2 + ( 2 ) 2 = 5 | B | = 1 2 + ( 2 ) 2 + ( 2 ) 2 = 5 |B|=sqrt(1^(2)+(sqrt2)^(2)+(sqrt2)^(2))=sqrt5|\mathbf{B}| = \sqrt{1^2 + (\sqrt{2})^2 + (\sqrt{2})^2} = \sqrt{5}|B|=12+(2)2+(2)2=5
Now, we can find the angle θ θ theta\thetaθ between the vectors:
cos ( θ ) = A B | A | | B | = 5 2 10 5 = 1 cos ( θ ) = A B | A | | B | = 5 2 10 5 = 1 cos(theta)=(A*B)/(|A||B|)=(5sqrt2)/(sqrt10*sqrt5)=1\cos(\theta) = \frac{\mathbf{A} \cdot \mathbf{B}}{|\mathbf{A}| |\mathbf{B}|} = \frac{5\sqrt{2}}{\sqrt{10} \cdot \sqrt{5}}=1cos(θ)=AB|A||B|=52105=1
After calculating, we find that the angle θ θ theta\thetaθ between the vectors is 0 0 000 radians, which is equivalent to 0 0 0^(@)0^\circ0. This means the vectors are parallel to each other.
ii) Find the vector equation of the plane determined by the points ( 1 , 0 , 1 ) , ( 0 , 1 , 1 ) ( 1 , 0 , 1 ) , ( 0 , 1 , 1 ) (1,0,-1),(0,1,1)(1,0,-1),(0,1,1)(1,0,1),(0,1,1) and ( 1 , 1 , 0 ) ( 1 , 1 , 0 ) (-1,1,0)(-1,1,0)(1,1,0).
Answer:
To find the vector equation of a plane determined by three points, we first need to find two direction vectors that lie in the plane. These can be obtained by subtracting the coordinates of the points. Let’s denote the points as A = ( 1 , 0 , 1 ) A = ( 1 , 0 , 1 ) A=(1,0,-1)A = (1,0,-1)A=(1,0,1), B = ( 0 , 1 , 1 ) B = ( 0 , 1 , 1 ) B=(0,1,1)B = (0,1,1)B=(0,1,1), and C = ( 1 , 1 , 0 ) C = ( 1 , 1 , 0 ) C=(-1,1,0)C = (-1,1,0)C=(1,1,0). We can find two direction vectors, say A B A B vec(AB)\vec{AB}AB and A C A C vec(AC)\vec{AC}AC, by subtracting the coordinates of these points.
The vector A B A B vec(AB)\vec{AB}AB is given by:
A B = B A = ( 0 , 1 , 1 ) ( 1 , 0 , 1 ) A B = B A = ( 0 , 1 , 1 ) ( 1 , 0 , 1 ) vec(AB)=B-A=(0,1,1)-(1,0,-1)\vec{AB} = B – A = (0,1,1) – (1,0,-1)AB=BA=(0,1,1)(1,0,1)
Similarly, the vector A C A C vec(AC)\vec{AC}AC is:
A C = C A = ( 1 , 1 , 0 ) ( 1 , 0 , 1 ) A C = C A = ( 1 , 1 , 0 ) ( 1 , 0 , 1 ) vec(AC)=C-A=(-1,1,0)-(1,0,-1)\vec{AC} = C – A = (-1,1,0) – (1,0,-1)AC=CA=(1,1,0)(1,0,1)
Next, we find a normal vector to the plane by taking the cross product of A B A B vec(AB)\vec{AB}AB and A C A C vec(AC)\vec{AC}AC. The cross product of two vectors is perpendicular to both, and hence, will be normal to the plane.
The cross product n n vec(n)\vec{n}n of A B A B vec(AB)\vec{AB}AB and A C A C vec(AC)\vec{AC}AC is given by:
n = A B × A C n = A B × A C vec(n)= vec(AB)xx vec(AC)\vec{n} = \vec{AB} \times \vec{AC}n=AB×AC
= ( 1 , 1 , 2 ) × ( 2 , 1 , 1 ) = ( 1 , 1 , 2 ) × ( 2 , 1 , 1 ) =(-1,1,2)xx(-2,1,1)= (-1, 1, 2) \times (-2, 1, 1)=(1,1,2)×(2,1,1)
Let’s calculate the cross product:
n = | i j k 1 1 2 2 1 1 | n = i j k 1 1 2 2 1 1 vec(n)=|[i,j,k],[-1,1,2],[-2,1,1]|\vec{n} = \begin{vmatrix} \mathbf{i} & \mathbf{j} & \mathbf{k} \\ -1 & 1 & 2 \\ -2 & 1 & 1 \\ \end{vmatrix}n=|ijk112211|
Expanding this determinant, we get:
n = i ( 1 1 2 1 ) j ( 1 1 2 2 ) + k ( 1 1 1 2 ) n = i ( 1 1 2 1 ) j ( 1 1 2 2 ) + k ( 1 1 1 2 ) vec(n)=i(1*1-2*1)-j(-1*1-2*-2)+k(-1*1-1*-2)\vec{n} = \mathbf{i}(1 \cdot 1 – 2 \cdot 1) – \mathbf{j}(-1 \cdot 1 – 2 \cdot -2) + \mathbf{k}(-1 \cdot 1 – 1 \cdot -2)n=i(1121)j(1122)+k(1112)
So, the normal vector n n vec(n)\vec{n}n is:
n = ( 1 , 3 , 1 ) n = ( 1 , 3 , 1 ) vec(n)=(-1,-3,1)\vec{n} = (-1, -3, 1)n=(1,3,1)
The vector equation of the plane can be written as:
n ( r A ) = 0 n ( r A ) = 0 vec(n)*( vec(r)- vec(A))=0\vec{n} \cdot (\vec{r} – \vec{A}) = 0n(rA)=0
where r = ( x , y , z ) r = ( x , y , z ) vec(r)=(x,y,z)\vec{r} = (x, y, z)r=(x,y,z) is any point on the plane, and A A vec(A)\vec{A}A is one of the given points, say ( 1 , 0 , 1 ) ( 1 , 0 , 1 ) (1,0,-1)(1,0,-1)(1,0,1).
Substituting n n vec(n)\vec{n}n and A A vec(A)\vec{A}A into the equation, we get:
( 1 , 3 , 1 ) ( ( x , y , z ) ( 1 , 0 , 1 ) ) = 0 ( 1 , 3 , 1 ) ( ( x , y , z ) ( 1 , 0 , 1 ) ) = 0 (-1,-3,1)*((x,y,z)-(1,0,-1))=0(-1, -3, 1) \cdot ((x, y, z) – (1, 0, -1)) = 0(1,3,1)((x,y,z)(1,0,1))=0
( 1 , 3 , 1 ) ( x 1 , y , z + 1 ) = 0 ( 1 , 3 , 1 ) ( x 1 , y , z + 1 ) = 0 (-1,-3,1)*(x-1,y,z+1)=0(-1, -3, 1) \cdot (x – 1, y, z + 1) = 0(1,3,1)(x1,y,z+1)=0
Expanding this, we have:
1 ( x 1 ) 3 y + 1 ( z + 1 ) = 0 1 ( x 1 ) 3 y + 1 ( z + 1 ) = 0 -1(x-1)-3y+1(z+1)=0-1(x – 1) – 3y + 1(z + 1) = 01(x1)3y+1(z+1)=0
x + 1 3 y + z + 1 = 0 x + 1 3 y + z + 1 = 0 -x+1-3y+z+1=0-x + 1 – 3y + z + 1 = 0x+13y+z+1=0
x 3 y + z + 2 = 0 x 3 y + z + 2 = 0 -x-3y+z+2=0-x – 3y + z + 2 = 0x3y+z+2=0
Therefore, the vector equation of the plane is:
x 3 y + z + 2 = 0 x 3 y + z + 2 = 0 -x-3y+z+2=0-x – 3y + z + 2 = 0x3y+z+2=0
iii) Check whether W = { ( x , y , z ) R 3 x + y z = 0 } W = ( x , y , z ) R 3 x + y z = 0 W={(x,y,z)inR^(3)∣x+y-z=0}W=\left\{(x, y, z) \in \mathbb{R}^3 \mid x+y-z=0\right\}W={(x,y,z)R3x+yz=0} is a subspace of R 3 R 3 R^(3)\mathbb{R}^3R3.
Answer:
To determine whether a set W W WWW is a subspace of R 3 R 3 R^(3)\mathbb{R}^3R3, it must satisfy three conditions:
  1. Non-emptiness: W W WWW must contain the zero vector of R 3 R 3 R^(3)\mathbb{R}^3R3.
  2. Closed under addition: For any two vectors u u vec(u)\vec{u}u and v v vec(v)\vec{v}v in W W WWW, the sum u + v u + v vec(u)+ vec(v)\vec{u} + \vec{v}u+v must also be in W W WWW.
  3. Closed under scalar multiplication: For any vector u u vec(u)\vec{u}u in W W WWW and any scalar c c ccc, the product c u c u c vec(u)c\vec{u}cu must also be in W W WWW.
Let’s check these conditions for W = { ( x , y , z ) R 3 x + y z = 0 } W = ( x , y , z ) R 3 x + y z = 0 W={(x,y,z)inR^(3)∣x+y-z=0}W = \left\{ (x, y, z) \in \mathbb{R}^3 \mid x + y – z = 0 \right\}W={(x,y,z)R3x+yz=0}.
  1. Non-emptiness:
    The zero vector in R 3 R 3 R^(3)\mathbb{R}^3R3 is ( 0 , 0 , 0 ) ( 0 , 0 , 0 ) (0,0,0)(0, 0, 0)(0,0,0). For this vector, x = 0 x = 0 x=0x = 0x=0, y = 0 y = 0 y=0y = 0y=0, and z = 0 z = 0 z=0z = 0z=0, so x + y z = 0 + 0 0 = 0 x + y z = 0 + 0 0 = 0 x+y-z=0+0-0=0x + y – z = 0 + 0 – 0 = 0x+yz=0+00=0. Therefore, the zero vector is in W W WWW, satisfying the non-emptiness condition.
  2. Closed under addition:
    Let u = ( x 1 , y 1 , z 1 ) u = ( x 1 , y 1 , z 1 ) vec(u)=(x_(1),y_(1),z_(1))\vec{u} = (x_1, y_1, z_1)u=(x1,y1,z1) and v = ( x 2 , y 2 , z 2 ) v = ( x 2 , y 2 , z 2 ) vec(v)=(x_(2),y_(2),z_(2))\vec{v} = (x_2, y_2, z_2)v=(x2,y2,z2) be any two vectors in W W WWW. This means x 1 + y 1 z 1 = 0 x 1 + y 1 z 1 = 0 x_(1)+y_(1)-z_(1)=0x_1 + y_1 – z_1 = 0x1+y1z1=0 and x 2 + y 2 z 2 = 0 x 2 + y 2 z 2 = 0 x_(2)+y_(2)-z_(2)=0x_2 + y_2 – z_2 = 0x2+y2z2=0. We need to check if their sum u + v = ( x 1 + x 2 , y 1 + y 2 , z 1 + z 2 ) u + v = ( x 1 + x 2 , y 1 + y 2 , z 1 + z 2 ) vec(u)+ vec(v)=(x_(1)+x_(2),y_(1)+y_(2),z_(1)+z_(2))\vec{u} + \vec{v} = (x_1 + x_2, y_1 + y_2, z_1 + z_2)u+v=(x1+x2,y1+y2,z1+z2) also satisfies the condition of W W WWW.
    For u + v u + v vec(u)+ vec(v)\vec{u} + \vec{v}u+v, we have:
    ( x 1 + x 2 ) + ( y 1 + y 2 ) ( z 1 + z 2 ) = ( x 1 + y 1 z 1 ) + ( x 2 + y 2 z 2 ) = 0 + 0 = 0 ( x 1 + x 2 ) + ( y 1 + y 2 ) ( z 1 + z 2 ) = ( x 1 + y 1 z 1 ) + ( x 2 + y 2 z 2 ) = 0 + 0 = 0 (x_(1)+x_(2))+(y_(1)+y_(2))-(z_(1)+z_(2))=(x_(1)+y_(1)-z_(1))+(x_(2)+y_(2)-z_(2))=0+0=0(x_1 + x_2) + (y_1 + y_2) – (z_1 + z_2) = (x_1 + y_1 – z_1) + (x_2 + y_2 – z_2) = 0 + 0 = 0(x1+x2)+(y1+y2)(z1+z2)=(x1+y1z1)+(x2+y2z2)=0+0=0
    Therefore, u + v u + v vec(u)+ vec(v)\vec{u} + \vec{v}u+v is in W W WWW, satisfying the closure under addition.
  3. Closed under scalar multiplication:
    Let u = ( x , y , z ) u = ( x , y , z ) vec(u)=(x,y,z)\vec{u} = (x, y, z)u=(x,y,z) be any vector in W W WWW and c c ccc be any scalar. Since u u vec(u)\vec{u}u is in W W WWW, x + y z = 0 x + y z = 0 x+y-z=0x + y – z = 0x+yz=0. We need to check if c u = ( c x , c y , c z ) c u = ( c x , c y , c z ) c vec(u)=(cx,cy,cz)c\vec{u} = (cx, cy, cz)cu=(cx,cy,cz) also satisfies the condition of W W WWW.
    For c u c u c vec(u)c\vec{u}cu, we have:
    c x + c y c z = c ( x + y z ) = c 0 = 0 c x + c y c z = c ( x + y z ) = c 0 = 0 cx+cy-cz=c(x+y-z)=c*0=0cx + cy – cz = c(x + y – z) = c \cdot 0 = 0cx+cycz=c(x+yz)=c0=0
    Therefore, c u c u c vec(u)c\vec{u}cu is in W W WWW, satisfying the closure under scalar multiplication.
Since W W WWW satisfies all three conditions, it is a subspace of R 3 R 3 R^(3)\mathbb{R}^3R3.
iv) Check whether the set of vectors { 1 + x , x + x 2 , 1 + x 3 } 1 + x , x + x 2 , 1 + x 3 {1+x,x+x^(2),1+x^(3)}\left\{1+x, x+x^2, 1+x^3\right\}{1+x,x+x2,1+x3} is a linearly independent set of vectors in P 3 P 3 P_(3)\mathbf{P}_3P3, the vector space of polynomials of degree 3 3 <= 3\leq 33.
Answer:
To determine whether the set of vectors { 1 + x , x + x 2 , 1 + x 3 } { 1 + x , x + x 2 , 1 + x 3 } {1+x,x+x^(2),1+x^(3)}\{1+x, x+x^2, 1+x^3\}{1+x,x+x2,1+x3} is linearly independent in the vector space P 3 P 3 P_(3)\mathbf{P}_3P3 (the space of polynomials of degree 3 3 <= 3\leq 33), we need to check if the only solution to the linear combination equation
c 1 ( 1 + x ) + c 2 ( x + x 2 ) + c 3 ( 1 + x 3 ) = 0 c 1 ( 1 + x ) + c 2 ( x + x 2 ) + c 3 ( 1 + x 3 ) = 0 c_(1)(1+x)+c_(2)(x+x^(2))+c_(3)(1+x^(3))=0c_1(1+x) + c_2(x+x^2) + c_3(1+x^3) = 0c1(1+x)+c2(x+x2)+c3(1+x3)=0
is c 1 = c 2 = c 3 = 0 c 1 = c 2 = c 3 = 0 c_(1)=c_(2)=c_(3)=0c_1 = c_2 = c_3 = 0c1=c2=c3=0, where c 1 , c 2 , c 1 , c 2 , c_(1),c_(2),c_1, c_2,c1,c2, and c 3 c 3 c_(3)c_3c3 are constants.
Expanding the equation, we get:
c 1 + c 1 x + c 2 x + c 2 x 2 + c 3 + c 3 x 3 = 0 c 1 + c 1 x + c 2 x + c 2 x 2 + c 3 + c 3 x 3 = 0 c_(1)+c_(1)x+c_(2)x+c_(2)x^(2)+c_(3)+c_(3)x^(3)=0c_1 + c_1x + c_2x + c_2x^2 + c_3 + c_3x^3 = 0c1+c1x+c2x+c2x2+c3+c3x3=0
This can be rearranged as:
( c 1 + c 3 ) + ( c 1 + c 2 ) x + c 2 x 2 + c 3 x 3 = 0 ( c 1 + c 3 ) + ( c 1 + c 2 ) x + c 2 x 2 + c 3 x 3 = 0 (c_(1)+c_(3))+(c_(1)+c_(2))x+c_(2)x^(2)+c_(3)x^(3)=0(c_1 + c_3) + (c_1 + c_2)x + c_2x^2 + c_3x^3 = 0(c1+c3)+(c1+c2)x+c2x2+c3x3=0
For this polynomial to be identically zero, each coefficient must be zero. Therefore, we have the system of equations:
  1. c 1 + c 3 = 0 c 1 + c 3 = 0 c_(1)+c_(3)=0c_1 + c_3 = 0c1+c3=0
  2. c 1 + c 2 = 0 c 1 + c 2 = 0 c_(1)+c_(2)=0c_1 + c_2 = 0c1+c2=0
  3. c 2 = 0 c 2 = 0 c_(2)=0c_2 = 0c2=0
  4. c 3 = 0 c 3 = 0 c_(3)=0c_3 = 0c3=0
From equation 3, we immediately have c 2 = 0 c 2 = 0 c_(2)=0c_2 = 0c2=0. Substituting this into equation 2 gives c 1 = 0 c 1 = 0 c_(1)=0c_1 = 0c1=0. Finally, substituting c 1 = 0 c 1 = 0 c_(1)=0c_1 = 0c1=0 into equation 1 gives c 3 = 0 c 3 = 0 c_(3)=0c_3 = 0c3=0.
Since the only solution to the system is c 1 = c 2 = c 3 = 0 c 1 = c 2 = c 3 = 0 c_(1)=c_(2)=c_(3)=0c_1 = c_2 = c_3 = 0c1=c2=c3=0, the set of vectors { 1 + x , x + x 2 , 1 + x 3 } { 1 + x , x + x 2 , 1 + x 3 } {1+x,x+x^(2),1+x^(3)}\{1+x, x+x^2, 1+x^3\}{1+x,x+x2,1+x3} is linearly independent in P 3 P 3 P_(3)\mathbf{P}_3P3.
v) Check whether T : R 2 R 2 T : R 2 R 2 T:R^(2)rarrR^(2)T: \mathbb{R}^2 \rightarrow \mathbb{R}^2T:R2R2, defined by T ( x , y ) = ( y , x ) T ( x , y ) = ( y , x ) T(x,y)=(-y,x)T(x, y)=(-y, x)T(x,y)=(y,x) is a linear transformation.
Answer:
To determine whether a function T : R 2 R 2 T : R 2 R 2 T:R^(2)rarrR^(2)T: \mathbb{R}^2 \rightarrow \mathbb{R}^2T:R2R2 is a linear transformation, it must satisfy two properties for all vectors u , v R 2 u , v R 2 vec(u), vec(v)inR^(2)\vec{u}, \vec{v} \in \mathbb{R}^2u,vR2 and any scalar c c ccc:
  1. Additivity: T ( u + v ) = T ( u ) + T ( v ) T ( u + v ) = T ( u ) + T ( v ) T( vec(u)+ vec(v))=T( vec(u))+T( vec(v))T(\vec{u} + \vec{v}) = T(\vec{u}) + T(\vec{v})T(u+v)=T(u)+T(v)
  2. Homogeneity: T ( c u ) = c T ( u ) T ( c u ) = c T ( u ) T(c vec(u))=cT( vec(u))T(c\vec{u}) = cT(\vec{u})T(cu)=cT(u)
Let’s check these properties for T T TTT defined by T ( x , y ) = ( y , x ) T ( x , y ) = ( y , x ) T(x,y)=(-y,x)T(x, y) = (-y, x)T(x,y)=(y,x).
  1. Additivity:
    Let u = ( x 1 , y 1 ) u = ( x 1 , y 1 ) vec(u)=(x_(1),y_(1))\vec{u} = (x_1, y_1)u=(x1,y1) and v = ( x 2 , y 2 ) v = ( x 2 , y 2 ) vec(v)=(x_(2),y_(2))\vec{v} = (x_2, y_2)v=(x2,y2) be any vectors in R 2 R 2 R^(2)\mathbb{R}^2R2. We need to check if T ( u + v ) = T ( u ) + T ( v ) T ( u + v ) = T ( u ) + T ( v ) T( vec(u)+ vec(v))=T( vec(u))+T( vec(v))T(\vec{u} + \vec{v}) = T(\vec{u}) + T(\vec{v})T(u+v)=T(u)+T(v).
    First, calculate u + v u + v vec(u)+ vec(v)\vec{u} + \vec{v}u+v:
    u + v = ( x 1 + x 2 , y 1 + y 2 ) u + v = ( x 1 + x 2 , y 1 + y 2 ) vec(u)+ vec(v)=(x_(1)+x_(2),y_(1)+y_(2))\vec{u} + \vec{v} = (x_1 + x_2, y_1 + y_2)u+v=(x1+x2,y1+y2)
    Then, apply T T TTT to u + v u + v vec(u)+ vec(v)\vec{u} + \vec{v}u+v:
    T ( u + v ) = T ( x 1 + x 2 , y 1 + y 2 ) = ( ( y 1 + y 2 ) , x 1 + x 2 ) T ( u + v ) = T ( x 1 + x 2 , y 1 + y 2 ) = ( ( y 1 + y 2 ) , x 1 + x 2 ) T( vec(u)+ vec(v))=T(x_(1)+x_(2),y_(1)+y_(2))=(-(y_(1)+y_(2)),x_(1)+x_(2))T(\vec{u} + \vec{v}) = T(x_1 + x_2, y_1 + y_2) = (-(y_1 + y_2), x_1 + x_2)T(u+v)=T(x1+x2,y1+y2)=((y1+y2),x1+x2)
    Now, calculate T ( u ) T ( u ) T( vec(u))T(\vec{u})T(u) and T ( v ) T ( v ) T( vec(v))T(\vec{v})T(v):
    T ( u ) = T ( x 1 , y 1 ) = ( y 1 , x 1 ) T ( u ) = T ( x 1 , y 1 ) = ( y 1 , x 1 ) T( vec(u))=T(x_(1),y_(1))=(-y_(1),x_(1))T(\vec{u}) = T(x_1, y_1) = (-y_1, x_1)T(u)=T(x1,y1)=(y1,x1)
    T ( v ) = T ( x 2 , y 2 ) = ( y 2 , x 2 ) T ( v ) = T ( x 2 , y 2 ) = ( y 2 , x 2 ) T( vec(v))=T(x_(2),y_(2))=(-y_(2),x_(2))T(\vec{v}) = T(x_2, y_2) = (-y_2, x_2)T(v)=T(x2,y2)=(y2,x2)
    Finally, add T ( u ) T ( u ) T( vec(u))T(\vec{u})T(u) and T ( v ) T ( v ) T( vec(v))T(\vec{v})T(v):
    T ( u ) + T ( v ) = ( y 1 , x 1 ) + ( y 2 , x 2 ) = ( ( y 1 + y 2 ) , x 1 + x 2 ) T ( u ) + T ( v ) = ( y 1 , x 1 ) + ( y 2 , x 2 ) = ( ( y 1 + y 2 ) , x 1 + x 2 ) T( vec(u))+T( vec(v))=(-y_(1),x_(1))+(-y_(2),x_(2))=(-(y_(1)+y_(2)),x_(1)+x_(2))T(\vec{u}) + T(\vec{v}) = (-y_1, x_1) + (-y_2, x_2) = (-(y_1 + y_2), x_1 + x_2)T(u)+T(v)=(y1,x1)+(y2,x2)=((y1+y2),x1+x2)
    Since T ( u + v ) = T ( u ) + T ( v ) T ( u + v ) = T ( u ) + T ( v ) T( vec(u)+ vec(v))=T( vec(u))+T( vec(v))T(\vec{u} + \vec{v}) = T(\vec{u}) + T(\vec{v})T(u+v)=T(u)+T(v), the additivity property is satisfied.
  2. Homogeneity:
    Let u = ( x , y ) u = ( x , y ) vec(u)=(x,y)\vec{u} = (x, y)u=(x,y) be any vector in R 2 R 2 R^(2)\mathbb{R}^2R2 and c c ccc be any scalar. We need to check if T ( c u ) = c T ( u ) T ( c u ) = c T ( u ) T(c vec(u))=cT( vec(u))T(c\vec{u}) = cT(\vec{u})T(cu)=cT(u).
    First, calculate c u c u c vec(u)c\vec{u}cu:
    c u = c ( x , y ) = ( c x , c y ) c u = c ( x , y ) = ( c x , c y ) c vec(u)=c(x,y)=(cx,cy)c\vec{u} = c(x, y) = (cx, cy)cu=c(x,y)=(cx,cy)
    Then, apply T T TTT to c u c u c vec(u)c\vec{u}cu:
    T ( c u ) = T ( c x , c y ) = ( c y , c x ) T ( c u ) = T ( c x , c y ) = ( c y , c x ) T(c vec(u))=T(cx,cy)=(-cy,cx)T(c\vec{u}) = T(cx, cy) = (-cy, cx)T(cu)=T(cx,cy)=(cy,cx)
    Now, calculate T ( u ) T ( u ) T( vec(u))T(\vec{u})T(u) and then multiply by c c ccc:
    T ( u ) = T ( x , y ) = ( y , x ) T ( u ) = T ( x , y ) = ( y , x ) T( vec(u))=T(x,y)=(-y,x)T(\vec{u}) = T(x, y) = (-y, x)T(u)=T(x,y)=(y,x)
    c T ( u ) = c ( y , x ) = ( c y , c x ) c T ( u ) = c ( y , x ) = ( c y , c x ) cT( vec(u))=c(-y,x)=(-cy,cx)cT(\vec{u}) = c(-y, x) = (-cy, cx)cT(u)=c(y,x)=(cy,cx)
    Since T ( c u ) = c T ( u ) T ( c u ) = c T ( u ) T(c vec(u))=cT( vec(u))T(c\vec{u}) = cT(\vec{u})T(cu)=cT(u), the homogeneity property is satisfied.
Since T T TTT satisfies both the additivity and homogeneity properties, it is a linear transformation.
Verified Answer
5/5
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