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Let $A,B \succeq 0$ be two positive semidefinite matrices. Can we get a closed form expression for the following quantity?

$$ \inf_{X \succ 0} \mathrm{tr}(XA) + \mathrm{tr}(X^{-1}B) $$

We assume all matrices involved are symmetric.

  • I think we might be able to show something in the symmetrical case (make all of $A,B,X$ symmetrical, I mean). Otherwise, I have no idea. – A. Pongrácz Aug 16 '18 at 21:45
  • @A.Pongrácz Although some authors don't require positive (semi)definite matrices to be symmetric (if real) or hermitian (if complex), I suspect we may assume that this is required here. – Robert Israel Aug 16 '18 at 21:49
  • Oh, in that case, there are suddenly a lot of toys to play with in the problem. – A. Pongrácz Aug 16 '18 at 21:53
  • A good candidate that can be achieved is $2 \sqrt{tr(A) tr(B)}$ – Marco Aug 16 '18 at 22:16
  • @Marco That’s also my guess... not sure if it is correct – O. Richard Aug 16 '18 at 22:18
  • Add the symmetric requirement. – O. Richard Aug 16 '18 at 22:19
  • The bound $2\sqrt{tr(A)tr(B)}$ is not optimal. When $A$ is diagonal and $B=I$, then smaller values of $tr(XA+X^{-1}B)$ are possible depending on the number of zero diagonal entries of $A$. For example if the only nonzero term of $A$ is the top-left entry and $B=I$, then the value $2\sqrt{a}$ can be obtained which is smaller than $2\sqrt{tr(A)tr(B)}=2\sqrt{an}$. – Marco Aug 16 '18 at 23:02
  • or a curious example where $A$ and $B$ are both diagonal but $AB=0$, then the infimum in this case is 0. So it seems that $2\sqrt{tr(AB)}$ is a better candidate. – Marco Aug 16 '18 at 23:18
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    ok my last guess for tonight: if $A$ and $B$ commute, then the infimum is given by $2 tr \sqrt{AB}$. – Marco Aug 16 '18 at 23:33
  • @Marco I tried to resort to the first order optimality condition. I think it is true if A and B commute. – O. Richard Aug 16 '18 at 23:38

2 Answers2

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We assume that $B$ symmetric $\geq 0$ and $A,X$ symmetric $>0$. Indeed, if $\det(A)=0,\det(B)\not= 0$, then the lower bound is not reached. For example, when $A=0$, the lower bound $0$ is "reached" for $X$ s.t. $||X||=\infty$.

$\textbf{Part 1}$. Consider the function $f:X>0\rightarrow tr(XA)+tr(X^{-1}B)$. The tangent space to $S_n^{++}$ is $S_n$, the vector space of symmetric matrices. Then

$Df_X:H\in S_n\rightarrow tr(HA)-tr(X^{-1}HX^{-1}B)=tr(H(A-X^{-1}BX^{-1}))$.

If $X$ reaches a local minimum of $f$, then $Df_X=0$, that is, $A-X^{-1}BX^{-1}$ is skew symmetric; that is equivalent to

$A=X^{-1}BX^{-1}$ or $(*)$ $XAX-B=0$.

The Riccati equation $(*)$ has a unique symmetric $\geq 0$ solution $X_0$; since the term of degree $1$ in $X$ does not exist, there is a closed form

$X_0=A^{-1/2}(A^{1/2}BA^{1/2})^{1/2}A^{-1/2}$.

Note that $f(X_0)=2tr((A^{1/2}BA^{1/2})^{1/2})$.

$\textbf{Part 2}$. $D^2f_X:(H,K)\in S_n\times S_n\rightarrow tr(X^{-1}KX^{-1}HX^{-1}B)+tr(X^{-1}HX^{-1}KX^{-1}B)$,

and $D^2f_X(H,H)=2tr((X^{-1}HX^{-1}HX^{-1})B)$.

The matrix $S=X^{-1}HX^{-1}HX^{-1}$ is symmetric $\geq 0$ because

$y^TSy=(HX^{-1}y)^TX^{-1}(HX^{-1}y)\geq 0$.

Then $D^2f_X(H,H)=2tr(SB)\geq 0$ and $f$ is convex (recall that $S_n^{++}$ is convex). Finally, $f(X_0)$ is the required minimum because (for a convex function $f$), $Df_{X_0}=0$ implies that $inf(f)=f(X_0)$.

  • Thanks a lot! Do you mind I ask another question: what is the derivative of $\mathrm{tr}((A^{1/2}BA^{1/2})^{1/2})$ w.r.t. $A$? – O. Richard Aug 17 '18 at 20:18
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    A closed-form solution for the Riccati equation. That piece had me stumped. Very nice. – greg Aug 17 '18 at 20:22
  • @O. Richard , there is no closed form for the derivative of $f(X_0)$ with respect to $A$; –  Aug 18 '18 at 13:19
  • @greg , thanks for the compliment. –  Aug 18 '18 at 13:20
  • @loupblanc Wow... could you elaborate? I asked the same question here https://math.stackexchange.com/questions/2886683/derivative-of-mathrmtra1-2ba1-21-2-w-r-t-a – O. Richard Aug 18 '18 at 13:40
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This is a partial answer only for commuting $A,B$. We claim that the infimum is attained by $2 tr \sqrt{AB}$. Since $A$ and $B$ are symmetric commuting matrices, we can assume without loss of generality that they are diagonal real matrices.

We prove our claim by induction on $n$. For $n=1$, the claim is easily checked. Suppose the claim is true for $n$ and suppose that $A$ and $B$ are diagonal $(n+1)\times (n+1)$ matrices with diagonal entries $a$ and $b$ at the bottom-right corners. We denote the top-left $n\times n$ blocks in $A$ and $B$ by $A'$ and $B'$.

Let $Z$ be an arbitrary positive definite $(n+1)\times (n+1)$ matrix. Write $Z$ and its inverse as $$Z=\begin{bmatrix} X & U \\ U^T & x \end{bmatrix},Z^{-1}=\begin{bmatrix}Y & V \\ V^T & y \end{bmatrix},$$ where $X$ and $Y$ are $n\times n$ positive definite matrices. Therefore, we have these equaitons: $$XY+UV^T=I,XV+yU=0,U^TY+xV^T=0,U^TV+xy=1.$$ From these equations and some algebra, we conclude that $$Y=X^{-1}+\dfrac{1}{y}VV^T,~x=\dfrac{1}{y}-\dfrac{1}{y}U^TV.$$ Since $X$ is positive definite, we have $$V^TXV \geq 0 \Rightarrow yV^TU=-V^TXV \leq 0.~~~~~~~~~~~~~~~(1)$$

Next, we compute $tr(ZA+Z^{-1}B)$ as follows: $$tr(ZA+Z^{-1}B)=tr(XA+YB)+xa+yb=tr(XA+(X^{-1}+\dfrac{1}{y}VV^T)B)+xa+yb$$ $$=tr(XA+X^{-1}B)+\dfrac{1}{y}tr(VV^TB)+(\dfrac{1}{y}-\dfrac{1}{y}U^TV)a+yb$$ $$=tr(XA+X^{-1}B)+ \dfrac{1}{y}a+yb +\dfrac{1}{y}tr(VV^TB) -\dfrac{a}{y}U^TV$$ $$\geq 2 tr\sqrt{A'B'}+2\sqrt{ab}+\dfrac{1}{y}tr(V^TBV) -\dfrac{a}{y}U^TV$$ $$\geq 2 tr \sqrt{AB},$$ since $tr(V^TBV)\geq 0$ and $yU^TV \leq 0$ by (1). Note that $x,y>0$ since diagonal entries of a symmetric positive definite matrix are all positive.

Also it is easy to see that the value $2 tr \sqrt{AB}$ can be attained by letting $X$ be a diagonal matrix with diagonal entries $x_i=\sqrt{b_i/a_i}$ if $a_i \neq 0$ and $x_i \rightarrow \infty$ otherwise.

Marco
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