Home / IBDP Maths AI: Topic : AHL 1.15: Eigenvalues and eigenvectors: IB style Questions HL Paper 1

IBDP Maths AI: Topic : AHL 1.15: Eigenvalues and eigenvectors: IB style Questions HL Paper 1

Question

Consider the matrix M = \(\left[ {\begin{array}{*{20}{c}}
2 \\
{ – 1}
\end{array}\,\,\,\begin{array}{*{20}{c}}
{ – 4} \\
{ – 1}
\end{array}} \right]\).

a.Show that the linear transformation represented by M transforms any point on the line \(y = x\) to a point on the same line.[2]

b.Explain what happens to points on the line \(4y + x = 0\) when they are transformed by M.[3]

c.State the two eigenvalues of M.[2]

d.State two eigenvectors of M which correspond to the two eigenvalues.[2]

▶️Answer/Explanation

Markscheme

\(\left( {\begin{array}{*{20}{c}}
2 \\
{ – 1}
\end{array}\,\,\,\begin{array}{*{20}{c}}
{ – 4} \\
{ – 1}
\end{array}} \right)\left( {\begin{array}{*{20}{c}}
k \\
k
\end{array}} \right) = \left( {\begin{array}{*{20}{c}}
{ – 2k} \\
{ – 2k}
\end{array}} \right)\left( { = – 2\left( {\begin{array}{*{20}{c}}
k \\
k
\end{array}} \right)} \right)\) M1A1

hence still on the line \(y = x\) AG

[2 marks]

a.

consider \(\left( {\begin{array}{*{20}{c}}
2 \\
{ – 1}
\end{array}\,\,\,\begin{array}{*{20}{c}}
{ – 4} \\
{ – 1}
\end{array}} \right)\left( {\begin{array}{*{20}{c}}
{4k} \\
{ – k}
\end{array}} \right)\) M1

\( = \left( {\begin{array}{*{20}{c}}
{12k} \\
{ – 3k}
\end{array}} \right)\left( { = 3\left( {\begin{array}{*{20}{c}}
{4k} \\
{ – k}
\end{array}} \right)} \right)\) A1

hence the line is invariant A1

[3 marks]

b.

hence the eigenvalues are −2 and 3 A1A1

[2 marks]

c.

\(\left( {\begin{array}{*{20}{c}}
1 \\
1
\end{array}} \right)\) and \(\left( {\begin{array}{*{20}{c}}
4 \\
{ – 1}
\end{array}} \right)\) or equivalent A1A1

[2 marks]

Question

Consider the matrix M = \(\left[ {\begin{array}{*{20}{c}}
2 \\
{ – 1}
\end{array}\,\,\,\begin{array}{*{20}{c}}
{ – 4} \\
{ – 1}
\end{array}} \right]\).

a.Show that the linear transformation represented by M transforms any point on the line \(y = x\) to a point on the same line.[2]

b.Explain what happens to points on the line \(4y + x = 0\) when they are transformed by M.[3]

c.State the two eigenvalues of M.[2]

d.State two eigenvectors of M which correspond to the two eigenvalues.[2]

▶️Answer/Explanation

Markscheme

\(\left( {\begin{array}{*{20}{c}}
2 \\
{ – 1}
\end{array}\,\,\,\begin{array}{*{20}{c}}
{ – 4} \\
{ – 1}
\end{array}} \right)\left( {\begin{array}{*{20}{c}}
k \\
k
\end{array}} \right) = \left( {\begin{array}{*{20}{c}}
{ – 2k} \\
{ – 2k}
\end{array}} \right)\left( { = – 2\left( {\begin{array}{*{20}{c}}
k \\
k
\end{array}} \right)} \right)\) M1A1

hence still on the line \(y = x\) AG

[2 marks]

a.

consider \(\left( {\begin{array}{*{20}{c}}
2 \\
{ – 1}
\end{array}\,\,\,\begin{array}{*{20}{c}}
{ – 4} \\
{ – 1}
\end{array}} \right)\left( {\begin{array}{*{20}{c}}
{4k} \\
{ – k}
\end{array}} \right)\) M1

\( = \left( {\begin{array}{*{20}{c}}
{12k} \\
{ – 3k}
\end{array}} \right)\left( { = 3\left( {\begin{array}{*{20}{c}}
{4k} \\
{ – k}
\end{array}} \right)} \right)\) A1

hence the line is invariant A1

[3 marks]

b.

hence the eigenvalues are −2 and 3 A1A1

[2 marks]

c.

\(\left( {\begin{array}{*{20}{c}}
1 \\
1
\end{array}} \right)\) and \(\left( {\begin{array}{*{20}{c}}
4 \\
{ – 1}
\end{array}} \right)\) or equivalent A1A1

[2 marks]

Question

The matrix M is defined by M = \(\left( {\begin{array}{*{20}{c}}a&b\\c&d\end{array}} \right)\).

 

The eigenvalues of M are denoted by \({\lambda _1},{\text{ }}{\lambda _2}\).

(a)     Show that \({\lambda _1} + {\lambda _2} = a + d\) and \({\lambda _1}{\lambda _2} = \det \)(M).

(b)     Given that \(a + b = c + d = 1\), show that 1 is an eigenvalue of M.

(c)     Find eigenvectors for the matrix \(\left( {\begin{array}{*{20}{c}}2&{ – 1}\\3&{ – 2}\end{array}} \right)\).

▶️Answer/Explanation

Markscheme

(a)     the eigenvalues satisfy \(\left| {\begin{array}{*{20}{c}}   {a – \lambda }&b \\   c&{d – \lambda } \end{array}} \right| = 0\)     (M1)

\({\lambda ^2} – (a + d)\lambda  + ad – bc = 0\)     A1

using the sum and product properties of the roots of a quadratic equation     R1

\({\lambda _1} + {\lambda _2} = a + d,{\text{ }}{\lambda _1}{\lambda _2} = ad – bc = \det \,\)(M)     AG

[3 marks]

 

(b)     let \(f(\lambda ) = {\lambda ^2} – (a + d)\lambda  + ad – bc\)

putting \(b = 1 – a\) and \(d = 1 – c\), consider     M1

\(f(1) = 1 – a – 1 + c + a – ac – c + ac = 0\)     A1

therefore \(\lambda  = 1\) is an eigenvalue     AG

[2 marks]

Note: Allow substitution for \(b\), \(c\) into the quadratic equation for \(\lambda \) followed by solution of this equation.

(c)     using any valid method     (M1)

the eigenvalues are 1 and –1     A1

an eigenvector corresponding to \(\lambda  = 1\) satisfies

\(\left( {\begin{array}{*{20}{c}}2&{ – 1}\\3&{ – 2}\end{array}} \right)\left( \begin{array}{l}x\\y\end{array} \right) = \left( \begin{array}{l}x\\y\end{array} \right)\) or \(\left( {\begin{array}{*{20}{c}}1&{ – 1}\\3&{ – 3}\end{array}} \right)\left( \begin{array}{l}x\\y\end{array} \right) = \left( \begin{array}{l}0\\0\end{array} \right)\)     M1A1

\(\left( \begin{array}{l}x\\y\end{array} \right) = \left( \begin{array}{l}1\\1\end{array} \right)\) or any multiple     A1

an eigenvector corresponding to \(\lambda  =  – 1\) satisfies

\(\left( {\begin{array}{*{20}{c}}2&{ – 1}\\3&{ – 2}\end{array}} \right)\left( \begin{array}{l}x\\y\end{array} \right) =  – \left( \begin{array}{l}x\\y\end{array} \right)\) or \(\left( {\begin{array}{*{20}{c}}3&{ – 1}\\3&{ – 1}\end{array}} \right)\left( \begin{array}{l}x\\y\end{array} \right) = \left( \begin{array}{l}0\\0\end{array} \right)\)     M1

\(\left( \begin{array}{l}x\\y\end{array} \right) = \left( \begin{array}{l}1\\3\end{array} \right)\) or any multiple     A1

Note: Award M1A1A1 for calculating the first eigenvector and M1A1 for the second irrespective of the order in which they are calculated.

[7 marks]

Question

Given that the elements of a \(2 \times 2\) symmetric matrix are real, show that

a.  (i)     the eigenvalues are real;

  (ii)     the eigenvectors are orthogonal if the eigenvalues are distinct.[11]

b.The matrix \(\boldsymbol{A}\) is given by\[\boldsymbol{A} = \left( {\begin{array}{*{20}{c}}

{11}&{\sqrt 3 }\\
{\sqrt 3 }&9
\end{array}} \right) .\]Find the eigenvalues and eigenvectors of \(\boldsymbol{A}\).[7]

c.The ellipse \(E\) has equation \({{\boldsymbol{X}}^T}{\boldsymbol{AX}} = 24\) where \(\boldsymbol{X} = \left( \begin{array}{l}

x\\
y
\end{array} \right)\) and \(\boldsymbol{A}\) is as defined in part (b).

   (i)     Show that \(E\) can be rotated about the origin onto the ellipse \(E’\) having equation \(2{x^2} + 3{y^2} = 6\) .

   (ii)     Find the acute angle through which \(E\) has to be rotated to coincide with \(E’\) .[7]

 
▶️Answer/Explanation

Markscheme

(i)     let \(\boldsymbol{M} = \left( {\begin{array}{*{20}{c}}
a&b\\
b&c
\end{array}} \right)\)     (M1)

the eigenvalues satisfy

\(\det (\boldsymbol{M} – \lambda \boldsymbol{I}) = 0\)     (M1)

\((a – \lambda )(c – \lambda ) – {b^2} = 0\)     (A1)

\({\lambda ^2} – \lambda (a + c) + ac – {b^2} = 0\)     A1

discriminant \( = {(a + c)^2} – 4(ac – {b^2})\)     M1

\( = {(a – c)^2} + 4{b^2} \ge 0\)     A1

this shows that the eigenvalues are real     AG

 

(ii)     let the distinct eigenvalues be \({\lambda _1},{\lambda _2}\)  , with eigenvectors \({{\boldsymbol{X}}_1}\), \({{\boldsymbol{X}}_2}\)

then

\({\lambda _1}{{\boldsymbol{X}}_1} = {\boldsymbol{M}}{{\boldsymbol{X}}_1}\) and \({\lambda _2}{{\boldsymbol{X}}_2} = {\boldsymbol{M}}{{\boldsymbol{X}}_1}\)     M1

transpose the first equation and postmultiply by \({{\boldsymbol{X}}_2}\) to give

\({\lambda _1}{\boldsymbol{X}}_1^T{{\boldsymbol{X}}_2} = {\boldsymbol{X}}_1^T{\boldsymbol{M}}{{\boldsymbol{X}}_2}\)     A1

premultiply the second equation by \({\boldsymbol{X}}_1^T\)

\({\lambda _2}{\boldsymbol{X}}_1^T{{\boldsymbol{X}}_2} = {\boldsymbol{X}}_1^T{\boldsymbol{M}}{{\boldsymbol{X}}_2}\)     A1

it follows that

\((\lambda 1 – {\lambda _2}){\boldsymbol{X}}_1^T{{\boldsymbol{X}}_2} = 0\)     A1

since \(\lambda 1 \ne {\lambda _2}\) , it follows that \({\boldsymbol{X}}_1^T{{\boldsymbol{X}}_2} = 0\) so that the eigenvectors are orthogonal     R1

 

[11 marks]

a.

the eigenvalues satisfy \(\left| \begin{array}{l}
11 – \lambda \\
\sqrt 3
\end{array} \right.\left. \begin{array}{l}
\sqrt 3 \\
9 – \lambda
\end{array} \right| = 0\)     M1A1

\({\lambda ^2} – 20\lambda  + 96 = 0\)    A1

\(\lambda  = 8,12\)     A1

first eigenvector satisfies

\(\left( {\begin{array}{*{20}{c}}
3&{\sqrt 3 }\\
{\sqrt 3 }&1
\end{array}} \right)\left( \begin{array}{l}
x\\
y
\end{array} \right) = \left( \begin{array}{l}
0\\
0
\end{array} \right)\)     M1

\(\left( \begin{array}{l}
x\\
y
\end{array} \right) = \) (any multiple of) \(\left( {\begin{array}{*{20}{c}}
1\\
{ – \sqrt 3 }
\end{array}} \right)\)     A1

second eigenvector satisfies

\(\left( {\begin{array}{*{20}{c}}
{ – 1}&{\sqrt 3 }\\
{\sqrt 3 }&{ – 3}
\end{array}} \right)\left( \begin{array}{l}
x\\
y
\end{array} \right) = \left( \begin{array}{l}
0\\
0
\end{array} \right)\)

\(\left( \begin{array}{l}
x\\
y
\end{array} \right) = \) (any multiple of ) \(\left( {\begin{array}{*{20}{c}}
{\sqrt 3 }\\
1
\end{array}} \right)\)     A1

[7 marks]

b.

(i)     consider the rotation in which \((x,y)\) is transformed onto \((x’,y’)\) defined by

\(\left( \begin{array}{l}
{x’}\\
{y’}
\end{array} \right) = \left( {\begin{array}{*{20}{c}}
{\frac{1}{2}}&{ – \frac{{\sqrt 3 }}{2}}\\
{\frac{{\sqrt 3 }}{2}}&{\frac{1}{2}}
\end{array}} \right)\left( \begin{array}{l}
x\\
y
\end{array} \right)\) so that \(\left( \begin{array}{l}
x\\
y
\end{array} \right) = \left( {\begin{array}{*{20}{c}}
{\frac{1}{2}}&{\frac{{\sqrt 3 }}{2}}\\
{ – \frac{{\sqrt 3 }}{2}}&{\frac{1}{2}}
\end{array}} \right)\left( \begin{array}{l}
{x’}\\
{y’}
\end{array} \right)\)     M1A1

the ellipse \(E\) becomes

\(\left( {\begin{array}{*{20}{c}}
{x’}&{y’}
\end{array}} \right)\left( {\begin{array}{*{20}{c}}
{\frac{1}{2}}&{ – \frac{{\sqrt 3 }}{2}}\\
{\frac{{\sqrt 3 }}{2}}&{\frac{1}{2}}
\end{array}} \right)\left( {\begin{array}{*{20}{c}}
{11}&{\sqrt 3 }\\
{\sqrt 3 }&9
\end{array}} \right)\left( {\begin{array}{*{20}{c}}
{\frac{1}{2}}&{\frac{{\sqrt 3 }}{2}}\\
{ – \frac{{\sqrt 3 }}{2}}&{\frac{1}{2}}
\end{array}} \right)\left( \begin{array}{l}
{x’}\\
{y’}
\end{array} \right) = 24\)     M1A1

\(\left( {\begin{array}{*{20}{c}}
{x’}&{y’}
\end{array}} \right)\left( {\begin{array}{*{20}{c}}
8&0\\
0&{12}
\end{array}} \right)\left( \begin{array}{l}
{x’}\\
{y’}
\end{array} \right) = 24\)     A1

\(2{(x’)^2} + 3{(y’)^2} = 6\)    AG

 

(ii)     the angle of rotation is given by \(\cos \theta  = \frac{1}{2},\sin \theta  = \frac{{\sqrt 3 }}{2}\)     M1

since a rotational matrix has the form \(\left( {\begin{array}{*{20}{c}}
{\cos \theta }&{ – \sin \theta }\\
{\sin \theta }&{\cos \theta }
\end{array}} \right)\)

so \(\theta  = {60^ \circ }\) (anticlockwise)     A1

[7 marks]

c.

[MAI 1.15] TRANSFORMATION MATRICES-loyola

Question

[Maximum mark: 5]
Let M be a transformation matrix.
(a) The matrix M maps the point (x, y) to the point (x’, y’) . Write down two liner equations for x’ and y’ in terms of x and y . [2]
(b) Find images of the following points
(i)    O(0,0)                       (ii)    A(1,1)                    (iii)     B(3,5).               [3]

▶️Answer/Explanation

Answer:

1. (a) x’ = 2x + 5y
y’ = x + 4y
(b) The image of O(0,0) is O(0,0) itself.
The image of A(1,1) is A΄(7,5).
The image of B(3,5) is B΄(31,23).

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