Is the trace of inverse matrix convex?

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Hi I would like to know whether the trace of the inverse of a symmetric positive definite matrix $\mathrm{trace}(S^{-1})$ is convex.

Actually I know that the trace of a symmetric positive definite matrix $S\in M_{m,m}$ is convex since we can find $B\in M_{n,m}$ such that $S=B^T\times B$ then we can write the trace as the sum of scalar quadratic forms, i.e. $\mathrm{trace}(S)=\mathrm{trace}(B^T\times B)=\sum_{j=1}^mb_j^T\times b_j$ where $b_j$ is the $j^{th}$ column of $B$.

for instance if we have $trace([\begin{array}{cc} 1 & 2 \\ 3 & 4 \\ \end{array}] \times [\begin{array}{cc} 1 & 3 \\ 2 & 4 \\ \end{array}])= [\begin{array}{cc} 1 & 2 \\ \end{array}]\times [\begin{array}{c} 1 \\ 2 \\ \end{array}]+ [\begin{array}{cc} 3 & 4 \\ \end{array}]\times [\begin{array}{c} 3 \\ 4 \\ \end{array}]=30$

And so I wonder if $\mathrm{trace}(S^{-1})$ is convex too..

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Yes, it is. Consider $S(t) = A + t B$ where $A$ is symmetric positive definite and $B$ is symmetric. It is enough to show that $$\left.\dfrac{d^2}{d t^2} \text{Tr}(S(t)^{-1})\right|_{t=0} \ge 0$$ Now $$ S(t)^{-1} = (A (I + t A^{-1} B))^{-1} = A^{-1} - t A^{-1} B A^{-1} + t^2 A^{-1} B A^{-1} B A^{-1} + \ldots$$ so $$ \left. \dfrac{d^2}{\partial t^2} \text{Tr}(S(t)^{-1}) \right|_{t=0} = 2 \text{Tr}(A^{-1} B A^{-1} B A^{-1})$$ But $A^{-1} B A^{-1} B A^{-1} = C A^{-1} C^T$ where $C = A^{-1} B$ and $A^{-1}$ is positive definite, so $C A^{-1} C^T$ is positive semidefinite, and therefore $\text{Tr}(CA^{-1} C^T) \ge 0$.

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We can prove that $Tr\{X^{-1}\}$ is convex function by considering an arbitrary line, $X = Z + tV$, where $V \in S^n$ and $Z \in S^n_{++}$. Let $g(t) = f(Z+tV)$ for all $t \in \mathbb R$ such that $Z+tV \in S^n_{++}$. If (for all $X \in S^n_{++}$ and all $V \in S_n$) $g$ is convex then $f$ is convex. Consider \begin{align} g(t) &= Tr\{X^{-1}\} = Tr\{(Z+tV)^{-1}\}\\ & = Tr\{Z^{-1/2}(I+tZ^{-1/2}VZ^{-1/2})^{-1})Z^{-1/2}\} \\ & = Tr\{Z^{-1}(I+tZ^{-1/2}VZ^{-1/2})^{-1})\} \qquad \qquad \because \; Tr\{BA\} = Tr\{AB\} \\ \end{align} Since, $(Z^{-1/2}VZ^{-1/2})^T = Z^{-1/2}VZ^{-1/2}$ as $Z,V \in S^n$. We can write, $ Z^{-1/2}VZ^{-1/2} = Q\Sigma Q^T$, where $Q$ is orthogonal matrix and $\Sigma$ is a diagonal matrix with eigen values $\lambda_i$'s $ Z^{-1/2}VZ^{-1/2}$ of as diagonal entries. Hence,

\begin{align} g(t) & = Tr\{Z^{-1}(I+tQ\Sigma Q^T)^{-1}\} \quad \because \; Tr\{BA\} = Tr\{AB\} \\ & = Tr\{Z^{-1}(Q(I+t\Sigma) Q^{T})^{-1}\} \\ & = Tr\{Z^{-1}Q(I+t\Sigma)^{-1}Q^{T}\} \quad \because \; (ABC)^{-1} = C^{-1}B^{-1}A^{-1} \ and \ Q^{-1} = Q^T \\ & = Tr\{Q^{T}Z^{-1}Q(I+t\Sigma)^{-1}\} \\ & = \sum_{i=1}^n (Q^TZ^{-1}Q)_{ii} \frac{1}{1+t\lambda_i}\\ \implies g''(t) &= \sum_{i=1}^n (Q^TZ^{-1}Q)_{ii} \frac{2\lambda_i^2}{(1+t\lambda_i)^3} \end{align} As, $(1+t\lambda_i)>0$ and $Q^TZ^{-1}Q$ is symmetric and positive definite matrix ($\because Z^{-1} \in S^n_{++} $) resulting in the diagonal entries of $Q^TZ^{-1}Q$ being positive values. Hence $g''(t)>0$ is always true. This concludes that $f$ is convex.