Prove that $forall t in mathbb R$ the set $f^{-1}({t})$ is a hyperplane of $X$











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Exercise :




Let $X$ be a vector space and $f:X to mathbb R$ be a linear functional. Show that for all $t in mathbb R$, the set $f^{-1}({t})$ is a hyperplane of $X$.




Attempt :



I have proved a slightly different example, showing that if $W$ is a hyperplane of $X$ then there exists a linear functional such that $W=f^{-1}({t})$. This was carried out by using the trick and setting $f(x) = f(lambda x + y)= lambda$, since we just needed to show that there exists some linear functional that would fullfill the given condition for some $t in mathbb R$



The case in this exercise though, is different, since we need to generally prove that for any linear functional and all $t in mathbb R$ the hyperplane condition holds.



Essentialy what I need to prove is that $f^{-1}({t})$ is a subspace of $X$ of $text{co}dim=1$ which then means that it is a hyperplane. Or, to prove that every element in this image can be written as $x = lambda x_0 + y$ with $x_0 notin Y$.



Question - Request : I can't see how to proceed proving the fact above though, as the only $text{co}dim$ statement that I recall is the kernel one. I would really appreciate any tips, hints or elaboration to help me work over this exercise and understand it.










share|cite|improve this question
























  • Hint: Since $f$ is linear, there is a relation between $f^{-1}(t)$ and $ker f$. Note that $f^{-1}(t)$ is not a linear subspace but only an affine one in general, since $0notin f^{-1}(t)$ for $tneq 0$.
    – asdq
    Nov 18 at 11:55












  • @asdq Hi, thanks for your input ! I am probably missing something, but what's the connection between $f^{-1}({t})$ and the kernel of $f$ ?
    – Rebellos
    Nov 18 at 12:01






  • 1




    If $f$ is nonzero then $f^{-1}(t)$ is obtained by translation of the kernel.
    – asdq
    Nov 18 at 13:11










  • @asdq I apologise but I cannot see a way to work around it. I would really appreciate an elaboration !
    – Rebellos
    Nov 18 at 13:20










  • Please see my answer.
    – asdq
    Nov 18 at 13:37















up vote
2
down vote

favorite












Exercise :




Let $X$ be a vector space and $f:X to mathbb R$ be a linear functional. Show that for all $t in mathbb R$, the set $f^{-1}({t})$ is a hyperplane of $X$.




Attempt :



I have proved a slightly different example, showing that if $W$ is a hyperplane of $X$ then there exists a linear functional such that $W=f^{-1}({t})$. This was carried out by using the trick and setting $f(x) = f(lambda x + y)= lambda$, since we just needed to show that there exists some linear functional that would fullfill the given condition for some $t in mathbb R$



The case in this exercise though, is different, since we need to generally prove that for any linear functional and all $t in mathbb R$ the hyperplane condition holds.



Essentialy what I need to prove is that $f^{-1}({t})$ is a subspace of $X$ of $text{co}dim=1$ which then means that it is a hyperplane. Or, to prove that every element in this image can be written as $x = lambda x_0 + y$ with $x_0 notin Y$.



Question - Request : I can't see how to proceed proving the fact above though, as the only $text{co}dim$ statement that I recall is the kernel one. I would really appreciate any tips, hints or elaboration to help me work over this exercise and understand it.










share|cite|improve this question
























  • Hint: Since $f$ is linear, there is a relation between $f^{-1}(t)$ and $ker f$. Note that $f^{-1}(t)$ is not a linear subspace but only an affine one in general, since $0notin f^{-1}(t)$ for $tneq 0$.
    – asdq
    Nov 18 at 11:55












  • @asdq Hi, thanks for your input ! I am probably missing something, but what's the connection between $f^{-1}({t})$ and the kernel of $f$ ?
    – Rebellos
    Nov 18 at 12:01






  • 1




    If $f$ is nonzero then $f^{-1}(t)$ is obtained by translation of the kernel.
    – asdq
    Nov 18 at 13:11










  • @asdq I apologise but I cannot see a way to work around it. I would really appreciate an elaboration !
    – Rebellos
    Nov 18 at 13:20










  • Please see my answer.
    – asdq
    Nov 18 at 13:37













up vote
2
down vote

favorite









up vote
2
down vote

favorite











Exercise :




Let $X$ be a vector space and $f:X to mathbb R$ be a linear functional. Show that for all $t in mathbb R$, the set $f^{-1}({t})$ is a hyperplane of $X$.




Attempt :



I have proved a slightly different example, showing that if $W$ is a hyperplane of $X$ then there exists a linear functional such that $W=f^{-1}({t})$. This was carried out by using the trick and setting $f(x) = f(lambda x + y)= lambda$, since we just needed to show that there exists some linear functional that would fullfill the given condition for some $t in mathbb R$



The case in this exercise though, is different, since we need to generally prove that for any linear functional and all $t in mathbb R$ the hyperplane condition holds.



Essentialy what I need to prove is that $f^{-1}({t})$ is a subspace of $X$ of $text{co}dim=1$ which then means that it is a hyperplane. Or, to prove that every element in this image can be written as $x = lambda x_0 + y$ with $x_0 notin Y$.



Question - Request : I can't see how to proceed proving the fact above though, as the only $text{co}dim$ statement that I recall is the kernel one. I would really appreciate any tips, hints or elaboration to help me work over this exercise and understand it.










share|cite|improve this question















Exercise :




Let $X$ be a vector space and $f:X to mathbb R$ be a linear functional. Show that for all $t in mathbb R$, the set $f^{-1}({t})$ is a hyperplane of $X$.




Attempt :



I have proved a slightly different example, showing that if $W$ is a hyperplane of $X$ then there exists a linear functional such that $W=f^{-1}({t})$. This was carried out by using the trick and setting $f(x) = f(lambda x + y)= lambda$, since we just needed to show that there exists some linear functional that would fullfill the given condition for some $t in mathbb R$



The case in this exercise though, is different, since we need to generally prove that for any linear functional and all $t in mathbb R$ the hyperplane condition holds.



Essentialy what I need to prove is that $f^{-1}({t})$ is a subspace of $X$ of $text{co}dim=1$ which then means that it is a hyperplane. Or, to prove that every element in this image can be written as $x = lambda x_0 + y$ with $x_0 notin Y$.



Question - Request : I can't see how to proceed proving the fact above though, as the only $text{co}dim$ statement that I recall is the kernel one. I would really appreciate any tips, hints or elaboration to help me work over this exercise and understand it.







real-analysis functional-analysis vector-spaces operator-theory geometric-functional-analysis






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edited Nov 18 at 11:54

























asked Nov 18 at 11:47









Rebellos

12.8k21041




12.8k21041












  • Hint: Since $f$ is linear, there is a relation between $f^{-1}(t)$ and $ker f$. Note that $f^{-1}(t)$ is not a linear subspace but only an affine one in general, since $0notin f^{-1}(t)$ for $tneq 0$.
    – asdq
    Nov 18 at 11:55












  • @asdq Hi, thanks for your input ! I am probably missing something, but what's the connection between $f^{-1}({t})$ and the kernel of $f$ ?
    – Rebellos
    Nov 18 at 12:01






  • 1




    If $f$ is nonzero then $f^{-1}(t)$ is obtained by translation of the kernel.
    – asdq
    Nov 18 at 13:11










  • @asdq I apologise but I cannot see a way to work around it. I would really appreciate an elaboration !
    – Rebellos
    Nov 18 at 13:20










  • Please see my answer.
    – asdq
    Nov 18 at 13:37


















  • Hint: Since $f$ is linear, there is a relation between $f^{-1}(t)$ and $ker f$. Note that $f^{-1}(t)$ is not a linear subspace but only an affine one in general, since $0notin f^{-1}(t)$ for $tneq 0$.
    – asdq
    Nov 18 at 11:55












  • @asdq Hi, thanks for your input ! I am probably missing something, but what's the connection between $f^{-1}({t})$ and the kernel of $f$ ?
    – Rebellos
    Nov 18 at 12:01






  • 1




    If $f$ is nonzero then $f^{-1}(t)$ is obtained by translation of the kernel.
    – asdq
    Nov 18 at 13:11










  • @asdq I apologise but I cannot see a way to work around it. I would really appreciate an elaboration !
    – Rebellos
    Nov 18 at 13:20










  • Please see my answer.
    – asdq
    Nov 18 at 13:37
















Hint: Since $f$ is linear, there is a relation between $f^{-1}(t)$ and $ker f$. Note that $f^{-1}(t)$ is not a linear subspace but only an affine one in general, since $0notin f^{-1}(t)$ for $tneq 0$.
– asdq
Nov 18 at 11:55






Hint: Since $f$ is linear, there is a relation between $f^{-1}(t)$ and $ker f$. Note that $f^{-1}(t)$ is not a linear subspace but only an affine one in general, since $0notin f^{-1}(t)$ for $tneq 0$.
– asdq
Nov 18 at 11:55














@asdq Hi, thanks for your input ! I am probably missing something, but what's the connection between $f^{-1}({t})$ and the kernel of $f$ ?
– Rebellos
Nov 18 at 12:01




@asdq Hi, thanks for your input ! I am probably missing something, but what's the connection between $f^{-1}({t})$ and the kernel of $f$ ?
– Rebellos
Nov 18 at 12:01




1




1




If $f$ is nonzero then $f^{-1}(t)$ is obtained by translation of the kernel.
– asdq
Nov 18 at 13:11




If $f$ is nonzero then $f^{-1}(t)$ is obtained by translation of the kernel.
– asdq
Nov 18 at 13:11












@asdq I apologise but I cannot see a way to work around it. I would really appreciate an elaboration !
– Rebellos
Nov 18 at 13:20




@asdq I apologise but I cannot see a way to work around it. I would really appreciate an elaboration !
– Rebellos
Nov 18 at 13:20












Please see my answer.
– asdq
Nov 18 at 13:37




Please see my answer.
– asdq
Nov 18 at 13:37










1 Answer
1






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oldest

votes

















up vote
2
down vote



accepted










Assume that $f$ is nonzero. Then $f$ must be surjective, so $f^{-1}(t)$ is non empty. Pick any $vin f^{-1}(t)$. Then we have $f^{-1}(t)=v + ker f$: Clearly the right hand side is contained in the left hand side. Conversely, for any $win f^{-1}(t)$ we have $v-w in ker f$ by linearity of $f$, hence the left hand side is contained in the right hand side. Therefore $f^{-1}(t)$ is an affine translation of the kernel and you can apply the dimension theorem you mentioned.






share|cite|improve this answer





















  • Could you clarify what you mean by the word "affine" ? I'm afraid we haven't been using that.
    – Rebellos
    Nov 18 at 13:41






  • 1




    An affine subspace of a vector space just a linear subspace that does not necessarily contain $0$. This means that such a subspace is obtained by translating a linear subspace with some element in he vector space, i.e. exactly in the way I described.
    – asdq
    Nov 18 at 14:02











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Assume that $f$ is nonzero. Then $f$ must be surjective, so $f^{-1}(t)$ is non empty. Pick any $vin f^{-1}(t)$. Then we have $f^{-1}(t)=v + ker f$: Clearly the right hand side is contained in the left hand side. Conversely, for any $win f^{-1}(t)$ we have $v-w in ker f$ by linearity of $f$, hence the left hand side is contained in the right hand side. Therefore $f^{-1}(t)$ is an affine translation of the kernel and you can apply the dimension theorem you mentioned.






share|cite|improve this answer





















  • Could you clarify what you mean by the word "affine" ? I'm afraid we haven't been using that.
    – Rebellos
    Nov 18 at 13:41






  • 1




    An affine subspace of a vector space just a linear subspace that does not necessarily contain $0$. This means that such a subspace is obtained by translating a linear subspace with some element in he vector space, i.e. exactly in the way I described.
    – asdq
    Nov 18 at 14:02















up vote
2
down vote



accepted










Assume that $f$ is nonzero. Then $f$ must be surjective, so $f^{-1}(t)$ is non empty. Pick any $vin f^{-1}(t)$. Then we have $f^{-1}(t)=v + ker f$: Clearly the right hand side is contained in the left hand side. Conversely, for any $win f^{-1}(t)$ we have $v-w in ker f$ by linearity of $f$, hence the left hand side is contained in the right hand side. Therefore $f^{-1}(t)$ is an affine translation of the kernel and you can apply the dimension theorem you mentioned.






share|cite|improve this answer





















  • Could you clarify what you mean by the word "affine" ? I'm afraid we haven't been using that.
    – Rebellos
    Nov 18 at 13:41






  • 1




    An affine subspace of a vector space just a linear subspace that does not necessarily contain $0$. This means that such a subspace is obtained by translating a linear subspace with some element in he vector space, i.e. exactly in the way I described.
    – asdq
    Nov 18 at 14:02













up vote
2
down vote



accepted







up vote
2
down vote



accepted






Assume that $f$ is nonzero. Then $f$ must be surjective, so $f^{-1}(t)$ is non empty. Pick any $vin f^{-1}(t)$. Then we have $f^{-1}(t)=v + ker f$: Clearly the right hand side is contained in the left hand side. Conversely, for any $win f^{-1}(t)$ we have $v-w in ker f$ by linearity of $f$, hence the left hand side is contained in the right hand side. Therefore $f^{-1}(t)$ is an affine translation of the kernel and you can apply the dimension theorem you mentioned.






share|cite|improve this answer












Assume that $f$ is nonzero. Then $f$ must be surjective, so $f^{-1}(t)$ is non empty. Pick any $vin f^{-1}(t)$. Then we have $f^{-1}(t)=v + ker f$: Clearly the right hand side is contained in the left hand side. Conversely, for any $win f^{-1}(t)$ we have $v-w in ker f$ by linearity of $f$, hence the left hand side is contained in the right hand side. Therefore $f^{-1}(t)$ is an affine translation of the kernel and you can apply the dimension theorem you mentioned.







share|cite|improve this answer












share|cite|improve this answer



share|cite|improve this answer










answered Nov 18 at 13:36









asdq

1,7211418




1,7211418












  • Could you clarify what you mean by the word "affine" ? I'm afraid we haven't been using that.
    – Rebellos
    Nov 18 at 13:41






  • 1




    An affine subspace of a vector space just a linear subspace that does not necessarily contain $0$. This means that such a subspace is obtained by translating a linear subspace with some element in he vector space, i.e. exactly in the way I described.
    – asdq
    Nov 18 at 14:02


















  • Could you clarify what you mean by the word "affine" ? I'm afraid we haven't been using that.
    – Rebellos
    Nov 18 at 13:41






  • 1




    An affine subspace of a vector space just a linear subspace that does not necessarily contain $0$. This means that such a subspace is obtained by translating a linear subspace with some element in he vector space, i.e. exactly in the way I described.
    – asdq
    Nov 18 at 14:02
















Could you clarify what you mean by the word "affine" ? I'm afraid we haven't been using that.
– Rebellos
Nov 18 at 13:41




Could you clarify what you mean by the word "affine" ? I'm afraid we haven't been using that.
– Rebellos
Nov 18 at 13:41




1




1




An affine subspace of a vector space just a linear subspace that does not necessarily contain $0$. This means that such a subspace is obtained by translating a linear subspace with some element in he vector space, i.e. exactly in the way I described.
– asdq
Nov 18 at 14:02




An affine subspace of a vector space just a linear subspace that does not necessarily contain $0$. This means that such a subspace is obtained by translating a linear subspace with some element in he vector space, i.e. exactly in the way I described.
– asdq
Nov 18 at 14:02


















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