Characteristic polynomial of a linear operator in matrix space











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For $A in M_{ntimes n}(F)=V$, we define a linear operator $T$ such that $T(X)=AX$ for $Xin V$.



I need to show that the characteristic polynomial of $T$ is $(f_A(t))^n$, where $f_A(t)$ is the characteristic polynomial of $A$.



My latest approach has been to define $W$, the $T$-cyclic subspace of $V$ generated by some $X$. Then,



$beta = {X,,T(X),,T^2(X),,dots,,T^{k-1}(X)}$



is an ordered basis for $W$, where $k=dim(W)$. From here, I'm thinking I need to extend the basis to $n$ so that it's a basis for $V$ and then show somehow that, since $T^n(X)=A^nX$, my desired result falls out.



Am I on the right track? Any pushes in the right direction that could help me put the pieces together? Or is there a totally different way to solve this that has eluded me?










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  • Another route I have found to investigate is to start by using the fact that the characteristic polynomial of any $Ain M_{ntimes n}(F)$ is equal to $(-1)^n(a^nt^n + a_{n-1}t^{n-1} + dots + a_1t + a_0$).
    – justadampaul
    10 hours ago

















up vote
1
down vote

favorite
2












For $A in M_{ntimes n}(F)=V$, we define a linear operator $T$ such that $T(X)=AX$ for $Xin V$.



I need to show that the characteristic polynomial of $T$ is $(f_A(t))^n$, where $f_A(t)$ is the characteristic polynomial of $A$.



My latest approach has been to define $W$, the $T$-cyclic subspace of $V$ generated by some $X$. Then,



$beta = {X,,T(X),,T^2(X),,dots,,T^{k-1}(X)}$



is an ordered basis for $W$, where $k=dim(W)$. From here, I'm thinking I need to extend the basis to $n$ so that it's a basis for $V$ and then show somehow that, since $T^n(X)=A^nX$, my desired result falls out.



Am I on the right track? Any pushes in the right direction that could help me put the pieces together? Or is there a totally different way to solve this that has eluded me?










share|cite|improve this question
























  • Another route I have found to investigate is to start by using the fact that the characteristic polynomial of any $Ain M_{ntimes n}(F)$ is equal to $(-1)^n(a^nt^n + a_{n-1}t^{n-1} + dots + a_1t + a_0$).
    – justadampaul
    10 hours ago















up vote
1
down vote

favorite
2









up vote
1
down vote

favorite
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2





For $A in M_{ntimes n}(F)=V$, we define a linear operator $T$ such that $T(X)=AX$ for $Xin V$.



I need to show that the characteristic polynomial of $T$ is $(f_A(t))^n$, where $f_A(t)$ is the characteristic polynomial of $A$.



My latest approach has been to define $W$, the $T$-cyclic subspace of $V$ generated by some $X$. Then,



$beta = {X,,T(X),,T^2(X),,dots,,T^{k-1}(X)}$



is an ordered basis for $W$, where $k=dim(W)$. From here, I'm thinking I need to extend the basis to $n$ so that it's a basis for $V$ and then show somehow that, since $T^n(X)=A^nX$, my desired result falls out.



Am I on the right track? Any pushes in the right direction that could help me put the pieces together? Or is there a totally different way to solve this that has eluded me?










share|cite|improve this question















For $A in M_{ntimes n}(F)=V$, we define a linear operator $T$ such that $T(X)=AX$ for $Xin V$.



I need to show that the characteristic polynomial of $T$ is $(f_A(t))^n$, where $f_A(t)$ is the characteristic polynomial of $A$.



My latest approach has been to define $W$, the $T$-cyclic subspace of $V$ generated by some $X$. Then,



$beta = {X,,T(X),,T^2(X),,dots,,T^{k-1}(X)}$



is an ordered basis for $W$, where $k=dim(W)$. From here, I'm thinking I need to extend the basis to $n$ so that it's a basis for $V$ and then show somehow that, since $T^n(X)=A^nX$, my desired result falls out.



Am I on the right track? Any pushes in the right direction that could help me put the pieces together? Or is there a totally different way to solve this that has eluded me?







linear-algebra matrices vector-spaces linear-transformations






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edited 11 hours ago

























asked 11 hours ago









justadampaul

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567












  • Another route I have found to investigate is to start by using the fact that the characteristic polynomial of any $Ain M_{ntimes n}(F)$ is equal to $(-1)^n(a^nt^n + a_{n-1}t^{n-1} + dots + a_1t + a_0$).
    – justadampaul
    10 hours ago




















  • Another route I have found to investigate is to start by using the fact that the characteristic polynomial of any $Ain M_{ntimes n}(F)$ is equal to $(-1)^n(a^nt^n + a_{n-1}t^{n-1} + dots + a_1t + a_0$).
    – justadampaul
    10 hours ago


















Another route I have found to investigate is to start by using the fact that the characteristic polynomial of any $Ain M_{ntimes n}(F)$ is equal to $(-1)^n(a^nt^n + a_{n-1}t^{n-1} + dots + a_1t + a_0$).
– justadampaul
10 hours ago






Another route I have found to investigate is to start by using the fact that the characteristic polynomial of any $Ain M_{ntimes n}(F)$ is equal to $(-1)^n(a^nt^n + a_{n-1}t^{n-1} + dots + a_1t + a_0$).
– justadampaul
10 hours ago












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Extending the ordered basis so that $k=n$, we have



$beta = {X, AX, A^2X,...,A^{n-1}X}$



as a basis for $V$. Now we simply express $T$ as $[T]_{beta}$, the matrix form of the operator, and take the characteristic polynomial of the result. Note that:



$T(X)=AX$



$T(AX)=A^2X$



$dots$



$T(A^{n-1}X)=A^nX$



and thus



$[T]_{beta}=AI_n$



which has the characteristic polynomial given by $(f_A(t))^n$, as needed.






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    Extending the ordered basis so that $k=n$, we have



    $beta = {X, AX, A^2X,...,A^{n-1}X}$



    as a basis for $V$. Now we simply express $T$ as $[T]_{beta}$, the matrix form of the operator, and take the characteristic polynomial of the result. Note that:



    $T(X)=AX$



    $T(AX)=A^2X$



    $dots$



    $T(A^{n-1}X)=A^nX$



    and thus



    $[T]_{beta}=AI_n$



    which has the characteristic polynomial given by $(f_A(t))^n$, as needed.






    share|cite|improve this answer

























      up vote
      1
      down vote













      Extending the ordered basis so that $k=n$, we have



      $beta = {X, AX, A^2X,...,A^{n-1}X}$



      as a basis for $V$. Now we simply express $T$ as $[T]_{beta}$, the matrix form of the operator, and take the characteristic polynomial of the result. Note that:



      $T(X)=AX$



      $T(AX)=A^2X$



      $dots$



      $T(A^{n-1}X)=A^nX$



      and thus



      $[T]_{beta}=AI_n$



      which has the characteristic polynomial given by $(f_A(t))^n$, as needed.






      share|cite|improve this answer























        up vote
        1
        down vote










        up vote
        1
        down vote









        Extending the ordered basis so that $k=n$, we have



        $beta = {X, AX, A^2X,...,A^{n-1}X}$



        as a basis for $V$. Now we simply express $T$ as $[T]_{beta}$, the matrix form of the operator, and take the characteristic polynomial of the result. Note that:



        $T(X)=AX$



        $T(AX)=A^2X$



        $dots$



        $T(A^{n-1}X)=A^nX$



        and thus



        $[T]_{beta}=AI_n$



        which has the characteristic polynomial given by $(f_A(t))^n$, as needed.






        share|cite|improve this answer












        Extending the ordered basis so that $k=n$, we have



        $beta = {X, AX, A^2X,...,A^{n-1}X}$



        as a basis for $V$. Now we simply express $T$ as $[T]_{beta}$, the matrix form of the operator, and take the characteristic polynomial of the result. Note that:



        $T(X)=AX$



        $T(AX)=A^2X$



        $dots$



        $T(A^{n-1}X)=A^nX$



        and thus



        $[T]_{beta}=AI_n$



        which has the characteristic polynomial given by $(f_A(t))^n$, as needed.







        share|cite|improve this answer












        share|cite|improve this answer



        share|cite|improve this answer










        answered 14 mins ago









        justadampaul

        567




        567






























             

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