tracial state of a orthogonal projection












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Suppose $Ain M_n(mathbb{C})$,$A$ has eigenvalues$lambda_1,cdots,lambda_n$,$P$ is the orthogonal projection from $mathbb{C}^n$ onto the span of eigenvectors associated with $lambda_1,cdots,lambda_n$,how to computer the tracial state of $P$.I saw a reference book,it writes:$tr_n(P)=frac{1}{n}$(cardinality of $lambda_1,cdots,lambda_n)$.I feel a little confused.










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    $begingroup$


    Suppose $Ain M_n(mathbb{C})$,$A$ has eigenvalues$lambda_1,cdots,lambda_n$,$P$ is the orthogonal projection from $mathbb{C}^n$ onto the span of eigenvectors associated with $lambda_1,cdots,lambda_n$,how to computer the tracial state of $P$.I saw a reference book,it writes:$tr_n(P)=frac{1}{n}$(cardinality of $lambda_1,cdots,lambda_n)$.I feel a little confused.










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      1








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      $begingroup$


      Suppose $Ain M_n(mathbb{C})$,$A$ has eigenvalues$lambda_1,cdots,lambda_n$,$P$ is the orthogonal projection from $mathbb{C}^n$ onto the span of eigenvectors associated with $lambda_1,cdots,lambda_n$,how to computer the tracial state of $P$.I saw a reference book,it writes:$tr_n(P)=frac{1}{n}$(cardinality of $lambda_1,cdots,lambda_n)$.I feel a little confused.










      share|cite|improve this question









      $endgroup$




      Suppose $Ain M_n(mathbb{C})$,$A$ has eigenvalues$lambda_1,cdots,lambda_n$,$P$ is the orthogonal projection from $mathbb{C}^n$ onto the span of eigenvectors associated with $lambda_1,cdots,lambda_n$,how to computer the tracial state of $P$.I saw a reference book,it writes:$tr_n(P)=frac{1}{n}$(cardinality of $lambda_1,cdots,lambda_n)$.I feel a little confused.







      operator-theory matrix-calculus operator-algebras c-star-algebras trace






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      asked Dec 5 '18 at 15:19









      mathrookiemathrookie

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          There is no general answer to this. If $lambda_1,ldots,lambda_n$ are distinct, then the eigenvectors of $A$ span $mathbb C^n$ and so $P=I$. If $A=lambda P$, then $operatorname{tr}_n(P)=k/n$, where $k$ is the rank of $P$.



          So all possible values $1/n,2/n,ldots,1$ are possible.






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            $begingroup$

            There is no general answer to this. If $lambda_1,ldots,lambda_n$ are distinct, then the eigenvectors of $A$ span $mathbb C^n$ and so $P=I$. If $A=lambda P$, then $operatorname{tr}_n(P)=k/n$, where $k$ is the rank of $P$.



            So all possible values $1/n,2/n,ldots,1$ are possible.






            share|cite|improve this answer









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              0












              $begingroup$

              There is no general answer to this. If $lambda_1,ldots,lambda_n$ are distinct, then the eigenvectors of $A$ span $mathbb C^n$ and so $P=I$. If $A=lambda P$, then $operatorname{tr}_n(P)=k/n$, where $k$ is the rank of $P$.



              So all possible values $1/n,2/n,ldots,1$ are possible.






              share|cite|improve this answer









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                0












                0








                0





                $begingroup$

                There is no general answer to this. If $lambda_1,ldots,lambda_n$ are distinct, then the eigenvectors of $A$ span $mathbb C^n$ and so $P=I$. If $A=lambda P$, then $operatorname{tr}_n(P)=k/n$, where $k$ is the rank of $P$.



                So all possible values $1/n,2/n,ldots,1$ are possible.






                share|cite|improve this answer









                $endgroup$



                There is no general answer to this. If $lambda_1,ldots,lambda_n$ are distinct, then the eigenvectors of $A$ span $mathbb C^n$ and so $P=I$. If $A=lambda P$, then $operatorname{tr}_n(P)=k/n$, where $k$ is the rank of $P$.



                So all possible values $1/n,2/n,ldots,1$ are possible.







                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered Dec 5 '18 at 17:29









                Martin ArgeramiMartin Argerami

                124k1177176




                124k1177176






























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