TITLE: When the sum of positive definite matrices converges, does the sum of the norm of the associate matrices converges?
QUESTION [10 upvotes]: Suppose $A_k>0$ (which means they are positive definitive square $n\times n$-matrices with $n>1$).
If $\sum_{k=1}^\infty A_k$ exists, then
$\sum_{k=1}^\infty \|A_k\| < +\infty$,
Where $\|A\|=\sup_{\|x\|\leq 1}\langle Ax,x\rangle$.
Is this true? (I am not able to give any counterexample.)
Thank you!

REPLY [18 votes]: Yes. The norm of a positive definite matrix does not exceed its trace, and the sum of traces is finite, since the sum of diagonal elements is finite for each of $n$ places.

REPLY [11 votes]: You can bound $\|A_k\| \leq C(n)\max_{i,j} |(A_k)_{ij}|$ for some function of the dimension only $C(n)$, because all norms are equivalent in finite dimension. If I am not mistaken $C(n)=\sqrt{n}$, but it doesn't really matter here.
This maximum is attained on a (positive) diagonal entry, because of positive definiteness. 
Then you have $$\sum_k \|A_k\| \leq C(n) \sum_k \max_i (A_k)_{ii} \leq C(n)\sum_k \sum_i (A_k)_{ii} = C(n) \sum_i (\sum_k (A_k)_{ii}),$$ which is finite because $\sum_k (A_k)_{ii}$ is finite for each $i$.