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\(B\).

Short Answer

Expert verified

For any scalar \(\lambda \), the matrix \(G - \lambda I\) has the same partitioned form as \(G\), with \(A - \lambda I\) , and \(B - \lambda I\) as its diagonal blocks.

Step by step solution

01

Step 1: Write the echelon form

Consider \(G = \left( {\begin{aligned}{*{20}{c}}A&X\\0&B\end{aligned}} \right)\).

Assume \(U\) and \(V\) be echelon forms of \(A\) and \(B\) obtained by \(r\) and \(s\) row interchanges.

\(\begin{aligned}{l}\det A &= {\left( { - 1} \right)^r}\det U\\\det B &= {\left( { - 1} \right)^s}\det V\end{aligned}\)

02

Step 2: Explain why \(\det G = \left( {\det A} \right)\left( {\det B} \right)\)

Using row operations, when\(A\)is reduced to\(U\), then\(G\)is reduced to\(G' = \left( {\begin{aligned}{*{20}{c}}U&Y\\0&B\end{aligned}} \right)\).

Using row operations, when\(B\)is reduced to\(V\), then\(G\)is reduced to\(G'' = \left( {\begin{aligned}{*{20}{c}}U&Y\\0&V\end{aligned}} \right)\).

Since there are \(r + s\) row operations then we get,

\(\begin{aligned}{c}\det G &= \det \left( {\begin{aligned}{*{20}{c}}A&X\\0&B\end{aligned}} \right)\\ &= {\left( { - 1} \right)^{r + s}}\det \left( {\begin{aligned}{*{20}{c}}U&Y\\0&V\end{aligned}} \right)\\ &= {\left( { - 1} \right)^{r + s}}\left( {\det U} \right)\left( {\det V} \right)\\ &= \left( {\det A} \right)\left( {\det B} \right)\end{aligned}\)

Thus, \(\det \left( {G - \lambda I} \right) = \det \left( {A - \lambda I} \right)\det \left( {B - \lambda I} \right)\).

For any scalar \(\lambda \), the matrix \(G - \lambda I\) has the same partitioned form as \(G\), with \(A - \lambda I\) and \(B - \lambda I\) as its diagonal blocks, that is, \(\det \left( {G - \lambda I} \right) = \det \left( {A - \lambda I} \right)\det \left( {B - \lambda I} \right)\).

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Most popular questions from this chapter

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.

Define \(T:{{\rm P}_2} \to {\mathbb{R}^3}\) by \(T\left( {\bf{p}} \right) = \left( {\begin{aligned}{{\bf{p}}\left( { - 1} \right)}\\{{\bf{p}}\left( 0 \right)}\\{{\bf{p}}\left( 1 \right)}\end{aligned}} \right)\).

  1. Find the image under\(T\)of\({\bf{p}}\left( t \right) = 5 + 3t\).
  2. Show that \(T\) is a linear transformation.
  3. Find the matrix for \(T\) relative to the basis \(\left\{ {1,t,{t^2}} \right\}\)for \({{\rm P}_2}\)and the standard basis for \({\mathbb{R}^3}\).

Question 19: Let \(A\) be an \(n \times n\) matrix, and suppose A has \(n\) real eigenvalues, \({\lambda _1},...,{\lambda _n}\), repeated according to multiplicities, so that \(\det \left( {A - \lambda I} \right) = \left( {{\lambda _1} - \lambda } \right)\left( {{\lambda _2} - \lambda } \right) \ldots \left( {{\lambda _n} - \lambda } \right)\) . Explain why \(\det A\) is the product of the n eigenvalues of A. (This result is true for any square matrix when complex eigenvalues are considered.)

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 \(p\).

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

7. \(\left[ {\begin{array}{*{20}{c}}5&3\\- 4&4\end{array}} \right]\)

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