Why does $V=K_lambda_i$ for $k=1$?

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Theorem 7.3. Let $T$ be a linear operator on a finite-dimensional vector space $V$ such that the characteristic polynomial of $T$ splits, and lett $lambda_1,lambda_2,...,lambda_k$ be the distinct eigenvalues of $T$. Then, for every $xin V$, there exist vectors $v_i in K_lambda_i$, $1le i le k$, such that



$x = v_1 + v_2 + cdots +v_k$.



Proof. The proof is by mathematical induction on the number $k$ of distinct eigenvalues of $T$. First suppose that $k = 1$, and let $m$ be the multiplicity of $lambda_1$. Then $(lambda_1 - t)^m$is the characteristic polynomial of $T$, and hence $(lambda_1 I - T)^m = T_0$ by the Cayley-Hamilton theorem(p.317). Thus $V=K_lambda_i$, and the result follows.




where $K_lambda_i$ = $v in V: (T-lambda_1 I)^p(v) = 0$ for some positive integer $p$.



I wanted to know why it follows that $V=K_lambda_i$?







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    Theorem 7.3. Let $T$ be a linear operator on a finite-dimensional vector space $V$ such that the characteristic polynomial of $T$ splits, and lett $lambda_1,lambda_2,...,lambda_k$ be the distinct eigenvalues of $T$. Then, for every $xin V$, there exist vectors $v_i in K_lambda_i$, $1le i le k$, such that



    $x = v_1 + v_2 + cdots +v_k$.



    Proof. The proof is by mathematical induction on the number $k$ of distinct eigenvalues of $T$. First suppose that $k = 1$, and let $m$ be the multiplicity of $lambda_1$. Then $(lambda_1 - t)^m$is the characteristic polynomial of $T$, and hence $(lambda_1 I - T)^m = T_0$ by the Cayley-Hamilton theorem(p.317). Thus $V=K_lambda_i$, and the result follows.




    where $K_lambda_i$ = $v in V: (T-lambda_1 I)^p(v) = 0$ for some positive integer $p$.



    I wanted to know why it follows that $V=K_lambda_i$?







    share|cite|improve this question





















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      Theorem 7.3. Let $T$ be a linear operator on a finite-dimensional vector space $V$ such that the characteristic polynomial of $T$ splits, and lett $lambda_1,lambda_2,...,lambda_k$ be the distinct eigenvalues of $T$. Then, for every $xin V$, there exist vectors $v_i in K_lambda_i$, $1le i le k$, such that



      $x = v_1 + v_2 + cdots +v_k$.



      Proof. The proof is by mathematical induction on the number $k$ of distinct eigenvalues of $T$. First suppose that $k = 1$, and let $m$ be the multiplicity of $lambda_1$. Then $(lambda_1 - t)^m$is the characteristic polynomial of $T$, and hence $(lambda_1 I - T)^m = T_0$ by the Cayley-Hamilton theorem(p.317). Thus $V=K_lambda_i$, and the result follows.




      where $K_lambda_i$ = $v in V: (T-lambda_1 I)^p(v) = 0$ for some positive integer $p$.



      I wanted to know why it follows that $V=K_lambda_i$?







      share|cite|improve this question












      Theorem 7.3. Let $T$ be a linear operator on a finite-dimensional vector space $V$ such that the characteristic polynomial of $T$ splits, and lett $lambda_1,lambda_2,...,lambda_k$ be the distinct eigenvalues of $T$. Then, for every $xin V$, there exist vectors $v_i in K_lambda_i$, $1le i le k$, such that



      $x = v_1 + v_2 + cdots +v_k$.



      Proof. The proof is by mathematical induction on the number $k$ of distinct eigenvalues of $T$. First suppose that $k = 1$, and let $m$ be the multiplicity of $lambda_1$. Then $(lambda_1 - t)^m$is the characteristic polynomial of $T$, and hence $(lambda_1 I - T)^m = T_0$ by the Cayley-Hamilton theorem(p.317). Thus $V=K_lambda_i$, and the result follows.




      where $K_lambda_i$ = $v in V: (T-lambda_1 I)^p(v) = 0$ for some positive integer $p$.



      I wanted to know why it follows that $V=K_lambda_i$?









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      asked 13 hours ago









      K.M

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          Cayley-Hamilton tells you that the characteristic polynomial of your linear operator annihilates it. Hence, what you must write is $(lambda_1I-T)^m=0_operatornameEnd(V)$. Now, consider any $vin V$. We have $$0=0_operatornameEnd(V)(v)=(lambda_1I-T)^m(v)$$
          Hence, by the definition you gave of $K_lambda_1$, we may conclude that $vin K_lambda_1$.






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            Cayley-Hamilton tells you that the characteristic polynomial of your linear operator annihilates it. Hence, what you must write is $(lambda_1I-T)^m=0_operatornameEnd(V)$. Now, consider any $vin V$. We have $$0=0_operatornameEnd(V)(v)=(lambda_1I-T)^m(v)$$
            Hence, by the definition you gave of $K_lambda_1$, we may conclude that $vin K_lambda_1$.






            share|cite|improve this answer

























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              Cayley-Hamilton tells you that the characteristic polynomial of your linear operator annihilates it. Hence, what you must write is $(lambda_1I-T)^m=0_operatornameEnd(V)$. Now, consider any $vin V$. We have $$0=0_operatornameEnd(V)(v)=(lambda_1I-T)^m(v)$$
              Hence, by the definition you gave of $K_lambda_1$, we may conclude that $vin K_lambda_1$.






              share|cite|improve this answer























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                up vote
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                down vote









                Cayley-Hamilton tells you that the characteristic polynomial of your linear operator annihilates it. Hence, what you must write is $(lambda_1I-T)^m=0_operatornameEnd(V)$. Now, consider any $vin V$. We have $$0=0_operatornameEnd(V)(v)=(lambda_1I-T)^m(v)$$
                Hence, by the definition you gave of $K_lambda_1$, we may conclude that $vin K_lambda_1$.






                share|cite|improve this answer













                Cayley-Hamilton tells you that the characteristic polynomial of your linear operator annihilates it. Hence, what you must write is $(lambda_1I-T)^m=0_operatornameEnd(V)$. Now, consider any $vin V$. We have $$0=0_operatornameEnd(V)(v)=(lambda_1I-T)^m(v)$$
                Hence, by the definition you gave of $K_lambda_1$, we may conclude that $vin K_lambda_1$.







                share|cite|improve this answer













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                answered 13 hours ago









                Suzet

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