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Unformatted text preview: MA 35100 HOMEWORK ASSIGNMENT #11 SOLUTIONS Problem 1. pg. 218; prob. 28 Consider an orthogonal transformation L from R n to R n . Show that L preserves the dot product: ~v ~w = L ( ~v ) L ( ~w ) , for all ~v and ~w in R n . Solution: The idea is to express the dot product in terms of lengths of vectors. For any ~x and ~ y in R n , we have  ~x + ~ y  2 = ( ~x + ~ y ) ( ~x + ~ y ) =  ~x  2 + 2( ~x ~ y ) +  ~ y  2 . We may write the dot product as ~x ~ y = 1 2  ~x + ~ y  2  ~x  2  ~ y  2 . Let ~x = L ( ~v ) and ~ y = L ( ~w ). Then we have L ( ~v ) L ( ~w ) = 1 2  L ( ~v ) + L ( ~w )  2  L ( ~v )  2  L ( ~w )  2 = 1 2  L ( ~v + ~w )  2  L ( ~v )  2  L ( ~w )  2 ( L is linear) = 1 2  ~v + ~w  2  ~v  2  ~w  2 ( L preserves lengths) = ~v ~w. Problem 2. pg. 218; prob. 29 Show that an orthogonal transformation L from R n to R n preserves angles: The angle between two nonzero vectors ~v and ~w in R n equals the angle between L ( ~v ) and L ( ~w ). Conversely, is any linear transformation that preserves angles orthogonal? Solution: Let be the angle between ~v and ~w , and be the angle between L ( ~v ) and L ( ~w ). We want to show = . According to Definition 5.1.12 on page 196 of the text, we have cos = ~v ~w  ~v  ~w  and cos = L ( ~v ) L ( ~w )  L ( ~v )  L ( ~w )  . Since L is an orthogonal transformation, we know that  L ( ~v )  =  ~v  and  L ( ~w )  =  ~w  . We showed in Exercise 5.3.28 (i.e., Problem 1 above) that L ( ~v ) L ( ~w ) = ~v ~w . This gives cos = cos , so = as desired. Conversely, a linear transformation that preserves angles is not orthogonal. As an example, con sider the linear transformation L : R 2 R 2 defined by L ( ~x ) = 2 ~x . Then  L ( ~x )  = 2  ~x  so that L is not orthogonal, but L ( ~v ) L ( ~w )  L ( ~v )  L ( ~w )  = 2 ~v 2 ~w 2  ~v  2  ~w  = ~v ~w  ~v  ~w  1 so that L does indeed preserve angles. Remark: A linear transformation L that preserves the dot product preserves both angles and lengths and hence must be orthogonal. Heres why. Let ~u i = L ( ~e i ) be the image of the standard basis vector for i = 1 , 2 ,...,n , so that the matrix of L is A = ~u 1 ~u 2 ~u n . Then ~u i ~u j = L ( ~e i ) L ( ~e j ) = ~e i ~e j = ( 1 if i = j , 0 otherwise....
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This note was uploaded on 03/31/2012 for the course MA 351 taught by Professor ?? during the Spring '08 term at Purdue UniversityWest Lafayette.
 Spring '08
 ??
 Linear Algebra, Algebra, Dot Product

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