Proof of normal matrix criterion

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SUMMARY

A matrix A is classified as normal if and only if the equation trace(A*A) = |t1|2 + ... + |tn|2 holds true, where t1, ..., tn are the characteristic roots of A. The proof involves transforming A into Schur form using a unitary matrix Q and an upper triangular matrix T, leading to the conclusion that if A is not normal, the off-diagonal entries of T must equal zero, thus making T a diagonal matrix. Consequently, A is confirmed to be normal.

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TTob
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I need to proof:
A in normal matrix if and only if [tex]trace(A^*A)=|t_1|^2+...|t_n|^2[/tex]
where [tex]t_1,...,t_n[/tex] are the characteristic roots of A.

I have a problem only with the second direction:
[tex]trace(A^*A)=|t_1|^2+...|t_n|^2[/tex] --> A is normal.

can you help me ?
 
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Presumably A is a complex matrix, so we can put it into Schur form, i.e. we can find a unitary matrix Q and an upper triangular matrix T such that A=Q-1TQ. Notice that trace(A*A)=trace(T*T). So if A is not normal, then <blank>.
 
thanks.

note [tex]T=[\alpha_{ij}][/tex]
so [tex]trace(T^*T)=trace(A^*A)=|t_1|^2+...|t_n|^2[/tex]
hence
[tex]\sum_{\substack{<br /> 0\leq\i\leq n \\<br /> 0\leq\j\leq n<br /> }} |\alpha_{ij}|^2<br /> =|t_1|^2+...|t_n|^2[/tex]
because of the eigenvalues are the diagonal entries of T we have
[tex]\sum_{\substack{<br /> 0\leq\i\leq n \\<br /> 0\leq\j\leq n \\<br /> j\ne i<br /> }} |\alpha_{ij}|^2<br /> =0[/tex]
hence for [tex]i\ne j[/tex] we have [tex]\alpha_{ij}=0[/tex]

so T is diagonal matrix. A=Q^-1TQ and hence A is normal.
 

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