Difference between revisions of "Section 1.10 Homework"

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is a subspace of <math>V</math>.<br />
 
is a subspace of <math>V</math>.<br />
 
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''Proof:'' Suppose <math>x_1,x_2 \in L^{-1}(N)</math>. Then <math>L(x_1),L(x_2) \in N</math>. But <math>N</math> is a subspace and so <math>L(x_1)+L(x_2) \in N</math>. But <math>L</math> is linear so that <math>L(x_1+x_2) = L(x_1)+L(x_2) \in N</math> so that <math>x_1+x_2 \in L^{-1}(N)</math>. Thus, <math>L^{-1}(N)</math> is closed under vector addition. Now suppose <math>x \in L^{-1}(N)</math> and <math>\alpha \in \mathbb{F}</math>. Then <math>L(x) \in N</math> and since <math>N</math> is a subspace, <math>\alpha L(x) \in N</math>. But again <math>L</math> is linear so <math>L(\alpha x) = \alpha L(x) \in N</math>. This means <math>\alpha x \in L^{-1}(N)</math>. Hence <math>L^{-1}(N)</math> is closed under scalar multiplication. Therefore <math>L^{-1}(N)</math> is a subspace of <math>V</math>.<br />
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{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
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!Proof:
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|-
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|Suppose <math>x_1,x_2 \in L^{-1}(N)</math>. Then <math>L(x_1),L(x_2) \in N</math>. But <math>N</math> is a subspace and so <math>L(x_1)+L(x_2) \in N</math>. But <math>L</math> is linear so that <math>L(x_1+x_2) = L(x_1)+L(x_2) \in N</math> so that <math>x_1+x_2 \in L^{-1}(N)</math>. Thus, <math>L^{-1}(N)</math> is closed under vector addition. Now suppose <math>x \in L^{-1}(N)</math> and <math>\alpha \in \mathbb{F}</math>. Then <math>L(x) \in N</math> and since <math>N</math> is a subspace, <math>\alpha L(x) \in N</math>. But again <math>L</math> is linear so <math>L(\alpha x) = \alpha L(x) \in N</math>. This means <math>\alpha x \in L^{-1}(N)</math>. Hence <math>L^{-1}(N)</math> is closed under scalar multiplication. Therefore <math>L^{-1}(N)</math> is a subspace of <math>V</math>.<br />
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'''10.''' Show that if <math>M \subset V</math> and <math>N \subset W</math> are subspaces, then <math>M \times N \subset V \times W</math> is also a subspace.<br />
 
'''10.''' Show that if <math>M \subset V</math> and <math>N \subset W</math> are subspaces, then <math>M \times N \subset V \times W</math> is also a subspace.<br />
 
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''Proof:'' Suppose <math>(x_1,y_1),(x_2,y_2) \in M \times N</math>. Then <math>x_1,x_2 \in M</math> and <math>y_1,y_2 \in N</math>. But <math>M</math> is a subspace and so <math>x_1+x_2 \in M</math>. Also <math>N</math> is a subspace so <math>y_1 + y_2 \in N</math>. This means <math>(x_1+x_2,y_1+y_2) \in M \times N</math>. On the other hand <math>(x_1,y_1)+(x_2,y_2) = (x_1+x_2,y_1+y_2)</math>. Thus, <math>M \times N</math> is closed under vector addition. Now suppose <math>(x,y) \in M \times N</math> and <math>\alpha \in \mathbb{F}</math>. Then <math>x \in M</math> and <math>y \in N</math>. But <math>M</math> and <math>N</math> are subspaces so <math>\alpha x \in M</math> and <math>\alpha y \in N</math>. That means <math>(\alpha x, \alpha y) \in M \times N</math>. This means <math>\alpha (x,y) = (\alpha x, \alpha y) \in M \times N</math>. Hence <math>M \times N</math> is closed under scalar multiplication. Therefore <math>M \times N</math> is a subspace of <math>V \times W</math>.<br />
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{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
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!Proof:
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|-
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|Suppose <math>(x_1,y_1),(x_2,y_2) \in M \times N</math>. Then <math>x_1,x_2 \in M</math> and <math>y_1,y_2 \in N</math>. But <math>M</math> is a subspace and so <math>x_1+x_2 \in M</math>. Also <math>N</math> is a subspace so <math>y_1 + y_2 \in N</math>. This means <math>(x_1+x_2,y_1+y_2) \in M \times N</math>. On the other hand <math>(x_1,y_1)+(x_2,y_2) = (x_1+x_2,y_1+y_2)</math>. Thus, <math>M \times N</math> is closed under vector addition. Now suppose <math>(x,y) \in M \times N</math> and <math>\alpha \in \mathbb{F}</math>. Then <math>x \in M</math> and <math>y \in N</math>. But <math>M</math> and <math>N</math> are subspaces so <math>\alpha x \in M</math> and <math>\alpha y \in N</math>. That means <math>(\alpha x, \alpha y) \in M \times N</math>. This means <math>\alpha (x,y) = (\alpha x, \alpha y) \in M \times N</math>. Hence <math>M \times N</math> is closed under scalar multiplication. Therefore <math>M \times N</math> is a subspace of <math>V \times W</math>.<br />
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(a) Show that <math>G_L</math> is a subspace.<br />
 
(a) Show that <math>G_L</math> is a subspace.<br />
 
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''Proof:'' Suppose <math>(x_1,L(x_1),(x_2,L(x_2) \in G_L</math>. Then <math>(x_1,L(x_1)+(x_2,L(x_2) = (x_1+x_2,L(x_1)+L(x_2)) = (x_1+x_2, L(x_1+x_2) \in G_L</math>. Here I used the fact that <math>L</math> is linear which means <math>L(x_1)+L(x_2) = L(x_1+x_2)</math>. Thus, <math>G_L</math> is closed under vector addition. Now suppose <math>(x,L(x)) \in G_L</math> and <math>\alpha \in \mathbb{F}</math>. Then <math>\alpha (x,L(x)) = (\alpha x, \alpha L(x)) = (\alpha x, L(\alpha x) \in G_L</math>. Again I used the linearity property to conclude <math>\alpha L(x) = L(\alpha x)</math>. Hence <math>G_L</math> is closed under scalar multiplication. Therefore <math>G_L</math> is a subspace of <math>V \times W</math>.<br />
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{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
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!Proof:
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|-
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|Suppose <math>(x_1,L(x_1),(x_2,L(x_2) \in G_L</math>. Then <math>(x_1,L(x_1)+(x_2,L(x_2) = (x_1+x_2,L(x_1)+L(x_2)) = (x_1+x_2, L(x_1+x_2) \in G_L</math>. Here I used the fact that <math>L</math> is linear which means <math>L(x_1)+L(x_2) = L(x_1+x_2)</math>. Thus, <math>G_L</math> is closed under vector addition. Now suppose <math>(x,L(x)) \in G_L</math> and <math>\alpha \in \mathbb{F}</math>. Then <math>\alpha (x,L(x)) = (\alpha x, \alpha L(x)) = (\alpha x, L(\alpha x) \in G_L</math>. Again I used the linearity property to conclude <math>\alpha L(x) = L(\alpha x)</math>. Hence <math>G_L</math> is closed under scalar multiplication. Therefore <math>G_L</math> is a subspace of <math>V \times W</math>.<br />
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(b) Show that the map <math>V \to G_L</math> that sends <math>x</math> to <math>(x,L(x)</math> is an isomorphism.<br />
 
(b) Show that the map <math>V \to G_L</math> that sends <math>x</math> to <math>(x,L(x)</math> is an isomorphism.<br />
 
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<br />
''Proof:'' Call this map <math>\hat{L}: V \to G_L</math>. That is <math>\hat{L}(x) = (x,L(x))</math>. First I will show this map is linear:  
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{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
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!Proof:
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|-
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|Call this map <math>\hat{L}: V \to G_L</math>. That is <math>\hat{L}(x) = (x,L(x))</math>. First I will show this map is linear:  
 
<math>\hat{L}(x_1+x_2) =(x_1+x_2, L(x_1+x_2)) = (x_1+x_2,L(x_1)+L(x_2)) = (x_1,L(x_1))+(x_2,L(x_2)) = \hat{L}(x_1)+\hat{L}(x_2)</math>
 
<math>\hat{L}(x_1+x_2) =(x_1+x_2, L(x_1+x_2)) = (x_1+x_2,L(x_1)+L(x_2)) = (x_1,L(x_1))+(x_2,L(x_2)) = \hat{L}(x_1)+\hat{L}(x_2)</math>
 
and <math>\hat{L}(\alpha x) =(\alpha x, L(\alpha x)) = (\alpha x,\alpha L(x)) = \alpha (x,L(x)) = \alpha \hat{L}(x)</math>. Thus <math>\hat{L}</math> is linear. Now to show <math>\hat{L}</math> is bijective. If <math>(x,L(x)) \in G_L</math>, then <math>\hat{L}(x) = (x,L(x))</math> so <math>\hat{L}</math> is trivially onto. In fact, we essentially chose to the codomain of our function <math>\hat{L}</math> to just be the image/range of the map to ensure it was onto. Now to show <math>\hat{L}</math> is one-to-one. Suppose <math>\hat{L}(x_1) = \hat{L}(x_2)</math>. Then <math>(x_1,L(x_1)) = (x_2,L(x_2)</math>. But two ordered pairs are equal if and only if both components are equal. That is, <math>x_1 = x_2</math>. Thus <math>\hat{L}</math> is one-to-one. Therefore <math>\hat{L}</math> is an isomorphism.
 
and <math>\hat{L}(\alpha x) =(\alpha x, L(\alpha x)) = (\alpha x,\alpha L(x)) = \alpha (x,L(x)) = \alpha \hat{L}(x)</math>. Thus <math>\hat{L}</math> is linear. Now to show <math>\hat{L}</math> is bijective. If <math>(x,L(x)) \in G_L</math>, then <math>\hat{L}(x) = (x,L(x))</math> so <math>\hat{L}</math> is trivially onto. In fact, we essentially chose to the codomain of our function <math>\hat{L}</math> to just be the image/range of the map to ensure it was onto. Now to show <math>\hat{L}</math> is one-to-one. Suppose <math>\hat{L}(x_1) = \hat{L}(x_2)</math>. Then <math>(x_1,L(x_1)) = (x_2,L(x_2)</math>. But two ordered pairs are equal if and only if both components are equal. That is, <math>x_1 = x_2</math>. Thus <math>\hat{L}</math> is one-to-one. Therefore <math>\hat{L}</math> is an isomorphism.
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|}

Latest revision as of 00:03, 16 November 2015

3. Let be a linear map and a subspace. Show that: is a subspace of .

Proof:
Suppose . Then . But is a subspace and so . But is linear so that so that . Thus, is closed under vector addition. Now suppose and . Then and since is a subspace, . But again is linear so . This means . Hence is closed under scalar multiplication. Therefore is a subspace of .


10. Show that if and are subspaces, then is also a subspace.

Proof:
Suppose . Then and . But is a subspace and so . Also is a subspace so . This means . On the other hand . Thus, is closed under vector addition. Now suppose and . Then and . But and are subspaces so and . That means . This means . Hence is closed under scalar multiplication. Therefore is a subspace of .


12. Let be a linear map and consider the graph (a) Show that is a subspace.

Proof:
Suppose . Then . Here I used the fact that is linear which means . Thus, is closed under vector addition. Now suppose and . Then . Again I used the linearity property to conclude . Hence is closed under scalar multiplication. Therefore is a subspace of .


(b) Show that the map that sends to is an isomorphism.

Proof:
Call this map . That is . First I will show this map is linear:

and . Thus is linear. Now to show is bijective. If , then so is trivially onto. In fact, we essentially chose to the codomain of our function to just be the image/range of the map to ensure it was onto. Now to show is one-to-one. Suppose . Then . But two ordered pairs are equal if and only if both components are equal. That is, . Thus is one-to-one. Therefore is an isomorphism.