Question: Consider an \(n \times n\) matrix A with the property that the row sums all equal the same number s. Show that s is an eigenvalue of A. (Hint: Find an eigenvector.)

Short Answer

Expert verified

It is proved that s is an eigenvalue of A.

Step by step solution

01

Assume the matrix A

Let the matrix A is:

\(A = \left( {\begin{array}{*{20}{c}}{{a_{11}}}&{{a_{12}}}& \cdots &{{a_{1n}}}\\{{a_{21}}}&{{a_{22}}}& \cdots &{{a_{2n}}}\\ \ldots & \cdots & \cdots & \cdots \\{{a_{n1}}}&{{a_{n2}}}& \cdots &{{a_{mn}}}\end{array}} \right)\)

For the elements of all the rows, the given property is:

\(\sum {{a_{1i}}} = \sum {{a_{2i}}} = .....\sum {{a_m}} = s\)

For \(i = 1,2,.....,n\)

02

Check whether s is the eigenvalue of A

Let the eigenvector be:

\(v = \left( {\begin{array}{*{20}{c}}1\\1\\ \vdots \\1\end{array}} \right)\)

Using the characteristic equation:

\(\begin{array}{c}A{\bf{v}} = \left( {\begin{array}{*{20}{c}}{{a_{11}}}&{{a_{12}}}& \cdots &{{a_{1n}}}\\{{a_{21}}}&{{a_{22}}}& \cdots &{{a_{2n}}}\\ \ldots & \cdots & \cdots & \cdots \\{{a_{n1}}}&{{a_{n2}}}& \cdots &{{a_{mn}}}\end{array}} \right)\left( {\begin{array}{*{20}{c}}1\\1\\ \vdots \\1\end{array}} \right)\\ = \left( {\begin{array}{*{20}{c}}{\sum {{a_{1i}}} }\\{\sum {{a_{2i}}} }\\ \vdots \\{\sum {{a_{ni}}} }\end{array}} \right)\\ = \left( {\begin{array}{*{20}{c}}s\\s\\ \vdots \\s\end{array}} \right)\\ = s\left( {\begin{array}{*{20}{c}}1\\1\\ \vdots \\1\end{array}} \right)\\ = s{\bf{v}}\end{array}\)

Therefore, s is an eigenvalue of matrix A.

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Most popular questions from this chapter

Question: Is \(\lambda = 2\) an eigenvalue of \(\left( {\begin{array}{*{20}{c}}3&2\\3&8\end{array}} \right)\)? Why or why not?

Question: Is \(\left( {\begin{array}{*{20}{c}}1\\{ - 2}\\1\end{array}} \right)\) an eigenvector of\(\left){\begin{array}{*{20}{c}}3&6&7\\3&3&7\\5&6&5\end{array}} \right)\)? If so, find the eigenvalue.

M] In Exercises 19 and 20, find (a) the largest eigenvalue and (b) the eigenvalue closest to zero. In each case, set \[{{\bf{x}}_{\bf{0}}}{\bf{ = }}\left( {{\bf{1,0,0,0}}} \right)\] and carry out approximations until the approximating sequence seems accurate to four decimal places. Include the approximate eigenvector.

19.\[A{\bf{=}}\left[{\begin{array}{*{20}{c}}{{\bf{10}}}&{\bf{7}}&{\bf{8}}&{\bf{7}}\\{\bf{7}}&{\bf{5}}&{\bf{6}}&{\bf{5}}\\{\bf{8}}&{\bf{6}}&{{\bf{10}}}&{\bf{9}}\\{\bf{7}}&{\bf{5}}&{\bf{9}}&{{\bf{10}}}\end{array}} \right]\]

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]

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 \(p\): \({C_p} = \left[ {\begin{aligned}{*{20}{c}}{\bf{0}}&{\bf{1}}&{\bf{0}}&{...}&{\bf{0}}\\{\bf{0}}&{\bf{0}}&{\bf{1}}&{}&{\bf{0}}\\:&{}&{}&{}&:\\{\bf{0}}&{\bf{0}}&{\bf{0}}&{}&{\bf{1}}\\{ - {a_{\bf{0}}}}&{ - {a_{\bf{1}}}}&{ - {a_{\bf{2}}}}&{...}&{ - {a_{n - {\bf{1}}}}}\end{aligned}} \right]\).

22. Let \(p\left( t \right) = {a_{\bf{0}}} + {a_{\bf{1}}}t + {a_{\bf{2}}}{t^{\bf{2}}} + {t^{\bf{3}}}\), and let \(\lambda \) be a zero of \(p\).

  1. Write the companion matrix for \(p\).
  2. Explain why \({\lambda ^{\bf{3}}} = - {a_{\bf{0}}} - {a_{\bf{1}}}\lambda - {a_{\bf{2}}}{\lambda ^{\bf{2}}}\), and show that \(\left( {{\bf{1}},\lambda ,{\lambda ^2}} \right)\) is an eigenvector of the companion matrix for \(p\).
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