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Question: Exercises 9-14 require techniques section 3.1. Find the characteristic polynomial of each matrix, using either a cofactor expansion or the special formula for \(3 \times 3\) determinants described prior to Exercise 15-18 in Section 3.1. (Note: Finding the characteristic polynomial of a \(3 \times 3\) matrix is not easy to do with just row operations, because the variable \(\lambda \) is involved.)

11. \(\left( {\begin{array}{*{20}{c}}4&0&0\\5&3&2\\{ - 2}&0&2\end{array}} \right)\)

Short Answer

Expert verified

The characteristic polynomial of the matrix is \({\lambda ^3} + 9{\lambda ^2} - 26\lambda + 24\).

Step by step solution

01

The Characteristic equation

Aneigenvalue of a\(n \times n\)matrix\(A\)is ascalar \(\lambda \)such that if\(\lambda \)satisfies the characteristic equation\(\det \left( {A - \lambda I} \right) = 0\).

02

Determine the characteristic polynomial of the matrix

The unique arrangement of zeros in \(A\) is to create a cofactor expansion on the first row.

Determine the characteristic polynomial of the matrix as shown below:

\(\begin{array}{c}\det \left( {A - \lambda I} \right) = \det \left( {\begin{array}{*{20}{c}}{4 - \lambda }&0&0\\5&{3 - \lambda }&2\\{ - 2}&0&{2 - \lambda }\end{array}} \right)\\ = \left( {4 - \lambda } \right)\det \left( {\begin{array}{*{20}{c}}{3 - \lambda }&2\\0&{2 - \lambda }\end{array}} \right)\\ = \left( {4 - \lambda } \right)\left( {3 - \lambda } \right)\left( {2 - \lambda } \right)\\ = \left( {4 - \lambda } \right)\left( {{\lambda ^2} - 5\lambda + 6} \right)\\ = {\lambda ^3} + 9{\lambda ^2} - 26\lambda + 24\end{array}\)

It would not be necessary to express the characteristic polynomial in the expanded form if only the eigenvalues were needed.

Thus, the characteristic polynomial of the matrix is \({\lambda ^3} + 9{\lambda ^2} - 26\lambda + 24\).

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Most popular questions from this chapter

Question: Find the characteristic polynomial and the eigenvalues of the matrices in Exercises 1-8.

3. \(\left[ {\begin{array}{*{20}{c}}3&-2\\1&-1\end{array}} \right]\)

For the matrix A, find real closed formulas for the trajectory x(t+1)=Ax¯(t) where x=[01]. Draw a rough sketchA=[7-156-11]

Consider the growth of a lilac bush. The state of this lilac bush for several years (at year’s end) is shown in the accompanying sketch. Let n(t) be the number of new branches (grown in the year t) and a(t) the number of old branches. In the sketch, the new branches are represented by shorter lines. Each old branch will grow two new branches in the following year. We assume that no branches ever die.

(a) Find the matrix A such that [nt+1at+1]=A[ntat]

(b) Verify that [11]and [2-1] are eigenvectors of A. Find the associated eigenvalues.

(c) Find closed formulas for n(t) and a(t).

Suppose \(A = PD{P^{ - 1}}\), where \(P\) is \(2 \times 2\) and \(D = \left( {\begin{array}{*{20}{l}}2&0\\0&7\end{array}} \right)\)

a. Let \(B = 5I - 3A + {A^2}\). Show that \(B\) is diagonalizable by finding a suitable factorization of \(B\).

b. Given \(p\left( t \right)\) and \(p\left( A \right)\) as in Exercise 5 , show that \(p\left( A \right)\) is diagonalizable.

Let\(D = \left\{ {{{\bf{d}}_1},{{\bf{d}}_2}} \right\}\) and \(B = \left\{ {{{\bf{b}}_1},{{\bf{b}}_2}} \right\}\) be bases for vector space \(V\) and \(W\), respectively. Let \(T:V \to W\) be a linear transformation with the property that

\(T\left( {{{\bf{d}}_1}} \right) = 2{{\bf{b}}_1} - 3{{\bf{b}}_2}\), \(T\left( {{{\bf{d}}_2}} \right) = - 4{{\bf{b}}_1} + 5{{\bf{b}}_2}\)

Find the matrix for \(T\) relative to \(D\), and\(B\).

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