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Let V be a vector space- If v V define Tv - R -- V by Tv(x) - xv for.docx

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Let V be a vector space- If v V define Tv - R -- V by Tv(x) - xv for.docx

Let V be a vector space. If v V define Tv : R -> V by Tv(x) = xv for all x in R. Show that Tv : R -> V is a linear transformation for each v in V and show that every linear transformation T:R-->V arises for a uniquely determined vector v in V.
Solution
To see that this is a linear transformation:

if x and y are two values in R:
T(x + y) = (x + y)v = xv + yv = T(x) + T(y)
So T is closed under addition.
Closure under multiplication:
if x is in R and k is a scalar
T(kx) = (kx)v = k(xv) = kT(x)
So T is closed under scalar multiplication.
Now for the second part: If T is a linear transformation, then T(1)=w for some vector w. Since T is linear, for any x in R, T(x)=T(x * 1) = x T(1) = xw.
So T is uniquely defined by where it sends x.
.

Let V be a vector space. If v V define Tv : R -> V by Tv(x) = xv for all x in R. Show that Tv : R -> V is a linear transformation for each v in V and show that every linear transformation T:R-->V arises for a uniquely determined vector v in V.
Solution
To see that this is a linear transformation:

if x and y are two values in R:
T(x + y) = (x + y)v = xv + yv = T(x) + T(y)
So T is closed under addition.
Closure under multiplication:
if x is in R and k is a scalar
T(kx) = (kx)v = k(xv) = kT(x)
So T is closed under scalar multiplication.
Now for the second part: If T is a linear transformation, then T(1)=w for some vector w. Since T is linear, for any x in R, T(x)=T(x * 1) = x T(1) = xw.
So T is uniquely defined by where it sends x.
.

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Let V be a vector space- If v V define Tv - R -- V by Tv(x) - xv for.docx

1. 1. Let V be a vector space. If v V define Tv : R -> V by Tv(x) = xv for all x in R. Show that Tv : R -> V is a linear transformation for each v in V and show that every linear transformation T:R-- >V arises for a uniquely determined vector v in V. Solution To see that this is a linear transformation: Closure under addition: if x and y are two values in R: T(x + y) = (x + y)v = xv + yv = T(x) + T(y) So T is closed under addition. Closure under multiplication: if x is in R and k is a scalar T(kx) = (kx)v = k(xv) = kT(x) So T is closed under scalar multiplication. Now for the second part: If T is a linear transformation, then T(1)=w for some vector w. Since T is linear, for any x in R, T(x)=T(x * 1) = x T(1) = xw. So T is uniquely defined by where it sends x.