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Let each matrix in Exercises 1–6 act on \({\mathbb{C}^2}\). Find the eigenvalues and a basis for each eigenspace in \({\mathbb{C}^2}\).

5. \(\left( {\begin{aligned}{}0&{}&1\\{ - 8}&{}&{\,4}\end{aligned}} \right)\)

Short Answer

Expert verified

Eigenvalues are \(\lambda = 2 + 2i\) and \(\lambda = 2 - 2i\). The basis for each Eigenspace in \({\mathbb{C}^2}\) is \({{\bf{v}}_1} = \left( \begin{aligned}{}\,\,\,\,1\\2 + 2i\end{aligned} \right)\) and \({{\bf{v}}_2} = \left( \begin{aligned}{}\,\,\,\,1\\2 - 2i\end{aligned} \right)\).

Step by step solution

01

Find the characteristic equation

If \(A\) is a \(n \times n\) matrix, then \(det\left( {A - \lambda I} \right) = 0\), is called the characteristic equation of matrix \(A\).

It is given that\(A = \left( {\begin{aligned}{}0&{}&1\\{ - 8}&{}&{\,\,6}\end{aligned}} \right)\)and\(I = \left( {\begin{aligned}{}1&{}&0\\0&{}&1\end{aligned}} \right)\)is the identity matrix. Find the matrix\(\left( {A - \lambda I} \right)\)as shown below:

\(\begin{aligned}{}A - \lambda I &= \left( {\begin{aligned}{}0&{}&1\\{ - 8}&{}&{\,\,6}\end{aligned}} \right) - \lambda \left( {\begin{aligned}{}1&{}&0\\0&{}&1\end{aligned}} \right)\\ &= \left( {\begin{aligned}{}{ - \lambda }&{}&1\\{ - 8}&{}&{6 - \lambda }\end{aligned}} \right)\end{aligned}\)

Now calculate the determinant of the matrix\(\left( {A - \lambda I} \right)\)as shown below:

\(\begin{aligned}{}det\left( {A - \lambda I} \right) &= det\left( {\begin{aligned}{}{ - \lambda }&{}&1\\{ - 8}&{}&{6 - \lambda }\end{aligned}} \right)\\ &= \left( { - \lambda } \right)\left( {6 - \lambda } \right) + 8\\ &= {\lambda ^2} - 4\lambda + 8\end{aligned}\)

So, the characteristic equation of the matrix \(A\) is \({\lambda ^2} - 4\lambda + 8 = 0\).

02

Find the Eigenvalues

Thus, the eigenvalues of\(A\)are the solutions of the characteristic equation\(\det \left( {A - \lambda I} \right) = 0\). So, solve the characteristic equation\({\lambda ^2} - 4\lambda + 8 = 0\), as follows:

For the quadratic equation, \(a{x^2} + bx + c = 0\) , the general solution is given as\(x = \frac{{ - b \pm \sqrt {{b^2} - 4ac} \;\;}}{{2a}}\) .

Thus, the solution of the characteristic equation \({\lambda ^2} - 4\lambda + 8 = 0\) is obtained as follows:

\(\begin{aligned}{}{\lambda ^2} - 4\lambda + 8 &= 0\\\lambda &= \frac{{ - \left( { - 4} \right) \pm \sqrt {{{\left( { - 4} \right)}^2} - 4\left( 8 \right)} }}{2}\\ &= \frac{{4 \pm \sqrt { - 16} }}{2}\\ &= 2 \pm 2i\end{aligned}\)

The eigenvalues of \(A\) are \(\lambda = 2 + 2i\) and \(\lambda = 2 - 2i\) .

03

Find the Eigenvectors

For the Eigenvalue,\({\lambda _i}\), matrix A satisfies the system of equations\(\left( {A - {\lambda _i}} \right){\rm{x}} = {\rm{0}}\).

For the Eigenvector, \(\lambda = 2 + 2i\), the system \(\left( {A - \lambda I} \right)\) is solved as follows:

\(\begin{aligned}{}A - \left( {2 + 2i} \right)I &= \left( {\begin{aligned}{}0&{}&1\\{ - 8}&{}&{\,\,4}\end{aligned}} \right) - \left( {2 + 2i} \right)\left( {\begin{aligned}{}1&{}&0\\{\,0}&{}&1\end{aligned}} \right)\\ &= \left( {\begin{aligned}{}{ - 2 - 2i}&{}&1\\{ - 8}&{}&{2 - 2i}\end{aligned}} \right)\end{aligned}\)

The system of equations \(\left( {A - \lambda I} \right)x = 0\)gives the following equations:

\(\begin{aligned}{}\left( {\begin{aligned}{}{ - 2 - 2i}&{}&1\\{ - 8}&{}&{2 - 2i}\end{aligned}} \right) &= 0\\\left( { - 2 - 2i} \right){x_1} + {x_2} &= 0\\ - 8{x_1} + \left( {2 - 2i} \right){x_2} &= 0\end{aligned}\)

Both the equations are equivalent to the equation, \({x_2} = - \left( { - 2 - 2i} \right){x_1}\), in which \({x_1}\) the variable is free. So, the general solution is \({x_1}\left( \begin{aligned}{}\,\,\,\,1\\2 + 2i\end{aligned} \right)\) and the corresponding Eigenvector is \({{\bf{v}}_1} = \left( \begin{aligned}{}\,\,\,\,1\\2 + 2i\end{aligned} \right)\).

For the Eigenvector, \(\lambda = 2 - 2i\), the system \(\left( {A - \lambda I} \right)\) is solved as follows:

\(\begin{aligned}{}A - \left( {2 - 2i} \right)I &= \left( {\begin{aligned}{}0&{}&1\\{ - 8}&{}&{\,\,4}\end{aligned}} \right) - \left( {2 - 2i} \right)\left( {\begin{aligned}{}1&{}&0\\{\,0}&{}&1\end{aligned}} \right)\\ &= \left( {\begin{aligned}{}{ - 2 + 2i}&{}&1\\{ - 8}&{}&{2 + 2i}\end{aligned}} \right)\end{aligned}\)

The system of equations \(\left( {A - \lambda I} \right)x = 0\)gives the following equations:

\(\begin{aligned}{}\left( {\begin{aligned}{}{ - 2 + 2i}&{}&1\\{ - 8}&{}&{2 + 2i}\end{aligned}} \right) &= 0\\\left( { - 2 + 2i} \right){x_1} + {x_2} &= 0\\ - 8{x_1} + \left( {2 + 2i} \right){x_2} &= 0\end{aligned}\)

Both the equations are equivalent to the equation, \({x_2} = - \left( { - 2 + 2i} \right){x_1}\), in which \({x_1}\) the variable is free. So, the general solution is \({x_1}\left( \begin{aligned}{}\,\,\,\,1\\2 - 2i\end{aligned} \right)\) and the corresponding Eigenvector is \({{\bf{v}}_2} = \left( \begin{aligned}{}\,\,\,\,1\\2 - 2i\end{aligned} \right)\).

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Most popular questions from this chapter

Question: For the matrices in Exercises 15-17, list the eigenvalues, repeated according to their multiplicities.

17. \(\left[ {\begin{array}{*{20}{c}}3&0&0&0&0\\- 5&1&0&0&0\\3&8&0&0&0\\0&- 7&2&1&0\\- 4&1&9&- 2&3\end{array}} \right]\)

Let\(G = \left( {\begin{aligned}{*{20}{c}}A&X\\{\bf{0}}&B\end{aligned}} \right)\). Use formula\(\left( {\bf{1}} \right)\)for the determinant in section\({\bf{5}}{\bf{.2}}\)to explain why\(\det G = \left( {\det A} \right)\left( {\det B} \right)\). From this, deduce that the characteristic polynomial of\(G\)is the product of the characteristic polynomials of\(A\)and\(B\).

Question: Let \(A = \left( {\begin{array}{*{20}{c}}{ - 6}&{28}&{21}\\4&{ - 15}&{ - 12}\\{ - 8}&a&{25}\end{array}} \right)\). For each value of \(a\) in the set \(\left\{ {32,31.9,31.8,32.1,32.2} \right\}\), compute the characteristic polynomial of \(A\) and the eigenvalues. In each case, create a graph of the characteristic polynomial \(p\left( t \right) = \det \left( {A - tI} \right)\) for \(0 \le t \le 3\). If possible, construct all graphs on one coordinate system. Describe how the graphs reveal the changes in the eigenvalues of \(a\) changes.

Use mathematical induction to show that if \(\lambda \) is an eigenvalue of an \(n \times n\) matrix \(A\), with a corresponding eigenvector, then, for each positive integer \(m\), \({\lambda ^m}\)is an eigenvalue of \({A^m}\), with \({\rm{x}}\) a corresponding eigenvector.

Exercises 19–23 concern the polynomial \(p\left( t \right) = {a_{\bf{0}}} + {a_{\bf{1}}}t + ... + {a_{n - {\bf{1}}}}{t^{n - {\bf{1}}}} + {t^n}\) and \(n \times n\) matrix \({C_p}\) called the companion matrix of \(p\): \({C_p} = \left( {\begin{aligned}{*{20}{c}}{\bf{0}}&{\bf{1}}&{\bf{0}}&{...}&{\bf{0}}\\{\bf{0}}&{\bf{0}}&{\bf{1}}&{}&{\bf{0}}\\:&{}&{}&{}&:\\{\bf{0}}&{\bf{0}}&{\bf{0}}&{}&{\bf{1}}\\{ - {a_{\bf{0}}}}&{ - {a_{\bf{1}}}}&{ - {a_{\bf{2}}}}&{...}&{ - {a_{n - {\bf{1}}}}}\end{aligned}} \right)\).

21. Use mathematical induction to prove that for \(n \ge {\bf{2}}\),\(\begin{aligned}{c}det\left( {{C_p} - \lambda I} \right) = {\left( { - {\bf{1}}} \right)^n}\left( {{a_{\bf{0}}} + {a_{\bf{1}}}\lambda + ... + {a_{n - {\bf{1}}}}{\lambda ^{n - {\bf{1}}}} + {\lambda ^n}} \right)\\ = {\left( { - {\bf{1}}} \right)^n}p\left( \lambda \right)\end{aligned}\)

(Hint: Expanding by cofactors down the first column, show that \(det\left( {{C_p} - \lambda I} \right)\) has the form \(\left( { - \lambda B} \right) + {\left( { - {\bf{1}}} \right)^n}{a_{\bf{0}}}\) where \(B\) is a certain polynomial (by the induction assumption).)

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