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Let \(A = LU\), where L is an invertible lower triangular matrix and \(U\) is upper triangular. Explain why the first column of \(A\) is a multiple of the first column of \(L\). How is the second column of \(A\) related to the columns of \(L\)?

Short Answer

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The first column of A is a multiple of the first column of \(L\).The second column of A is a linear combination of the first two columns of \(L\).

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01

Explain that the first column of A is a multiple of the first column of L

Here, \(A = LU\) \({{\mathop{\rm col}\nolimits} _1}\left( A \right) = L \cdot {{\mathop{\rm col}\nolimits} _1}\left( U \right)\). \(L \cdot {{\mathop{\rm col}\nolimits} _1}\left( U \right)\) is a linear combination of the columns of L in which all weights, except probably the first, are zero since \({{\mathop{\rm col}\nolimits} _1}\left( U \right)\) contains a zero in every entry. Therefore, \({{\mathop{\rm col}\nolimits} _1}\left( A \right)\) is a multiple of \({{\mathop{\rm col}\nolimits} _1}\left( U \right)\).

Thus, the first column of A is a multiple of the first column of L.

02

Explain that the second column of A is related to a column of L

Likewise, \({{\mathop{\rm col}\nolimits} _2}\left( A \right) = L \cdot {{\mathop{\rm col}\nolimits} _2}\left( U \right)\) represents the linear combination of the columns of L using the first two entries in \({{\mathop{\rm col}\nolimits} _2}\left( U \right)\) as weights. It is because other entries in \({{\mathop{\rm col}\nolimits} _2}\left( U \right)\) are zero. It means \({{\mathop{\rm col}\nolimits} _2}\left( A \right)\) is a linear combination of the first two columns of \(L\).

Thus, the second column of A is a linear combination of the first two columns of L.

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Most popular questions from this chapter

A useful way to test new ideas in matrix algebra, or to make conjectures, is to make calculations with matrices selected at random. Checking a property for a few matrices does not prove that the property holds in general, but it makes the property more believable. Also, if the property is actually false, you may discover this when you make a few calculations.

38. Use at least three pairs of random \(4 \times 4\) matrices Aand Bto test the equalities \({\left( {A + B} \right)^T} = {A^T} + {B^T}\) and \({\left( {AB} \right)^T} = {A^T}{B^T}\). (See Exercise 37.) Report your conclusions. (Note:Most matrix programs use \(A'\) for \({A^{\bf{T}}}\).

Suppose the first two columns, \({{\bf{b}}_1}\) and \({{\bf{b}}_2}\), of Bare equal. What can you say about the columns of AB(if ABis defined)? Why?

Let Ube the \({\bf{3}} \times {\bf{2}}\) cost matrix described in Example 6 of Section 1.8. The first column of Ulists the costs per dollar of output for manufacturing product B, and the second column lists the costs per dollar of output for product C. (The costs are categorized as materials, labor, and overhead.) Let \({q_1}\) be a vector in \({\mathbb{R}^{\bf{2}}}\) that lists the output (measured in dollars) of products B and C manufactured during the first quarter of the year, and let \({q_{\bf{2}}}\), \({q_{\bf{3}}}\) and \({q_{\bf{4}}}\) be the analogous vectors that list the amounts of products B and C manufactured in the second, third, and fourth quarters, respectively. Give an economic description of the data in the matrix UQ, where \(Q = \left( {\begin{aligned}{*{20}{c}}{{{\bf{q}}_1}}&{{{\bf{q}}_2}}&{{{\bf{q}}_3}}&{{{\bf{q}}_4}}\end{aligned}} \right)\).

Suppose A, B, and Care \(n \times n\) matrices with A, X, and \(A - AX\) invertible, and suppose

\({\left( {A - AX} \right)^{ - 1}} = {X^{ - 1}}B\) …(3)

  1. Explain why B is invertible.
  2. Solve (3) for X. If you need to invert a matrix, explain why that matrix is invertible.

3. Find the inverse of the matrix \(\left( {\begin{aligned}{*{20}{c}}{\bf{8}}&{\bf{5}}\\{ - {\bf{7}}}&{ - {\bf{5}}}\end{aligned}} \right)\).

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