An inequality related to matrix norms and the trace distance of two matrices

linear algebramatrices

Suppose that $U_1,U_2$ are unitary matrices. A paper here (page 4) I am reading gives the following set of inequalities (using Dirac notation here for vectors representing pure quantum states, aka. tensor products of vectors in $\mathbb{C}^2$ with length $1$).

$$
\|U_1 – U_2\| \geq \|U_1 |\psi \rangle – U_2 |\psi \rangle\| \geq \frac {1}{2}\operatorname{Trace}\left |U_1 |\psi \rangle \langle \psi| U_1^{\dagger} – U_2 |\psi \rangle \langle \psi| U_2^{\dagger}\right| \\
= D (U_1 |\psi \rangle \langle \psi| U_1^{\dagger} – U_2 |\psi \rangle \langle \psi| U_2^{\dagger}),$$

where $D$ is the trace distance.

The norm used is not stated. Here are some things I know related to these inequalities:

1) Unitary matrices preserve the length of vectors

2) If $|| A||$ is a matrix norm induced by a vector norm, then for $||x||=1$, $||A|| \geq ||Ax||$, which would explain the first inequality. I'm not sure what is happening in the second inequality. Insights appreciated.

Best Answer

The chain of inequalities makes sense if we add in the following.

Claim: For any unit vectors $x,y$, we have $$ \|x - y\| \geq \frac 12 \operatorname{Tr}|xx^* - yy^*|. $$

Proof: Noting that $x$ and $y$ are unit vectors, we compute $$ \|x - y\|^2 = (x-y)^*(x-y) = x^*x - x^*y - y^*x + y^*y \\ = 1 - \langle x, y\rangle - \langle y,x \rangle + 1 = 2(1 - \operatorname{Re}\langle x,y \rangle) $$ So, we have $\|x - y\| = \sqrt{2}\sqrt{1 - \operatorname{Re}\langle x,y \rangle}$.

On the other hand, $A = (xx^* - yy^*)$ is a rank-2 Hermitian matrix with trace zero, which means that it has non-zero eigenvalues $\pm \lambda$ for some $\lambda>0$. We compute $$ \begin{align*} 2\lambda^2 &= \lambda^2 + (-\lambda)^2 = \operatorname{Tr}(A^2) = \operatorname{Tr}[(xx^* - yy^*)^2] \\ & = \operatorname{Tr}[xx^*xx^* - xx^*yy^* - yy^*xx^* + yy^*yy^*] \\ & = \operatorname{Tr}[x^*xx^*x - x^*yy^*x - y^*xx^*y + y^*yy^*y] \\ &= \langle x,x\rangle^2 - 2|\langle x,y\rangle|^2 + \langle y,y \rangle^2 \\ & = 2 - 2|\langle x,y\rangle|^2 \end{align*} $$ We thereby conclude that $\lambda = \sqrt{1 - |\langle x,y \rangle|}$. Thus, we compute $$ \frac 12 \operatorname{Tr}|xx^* - yy^*| = \frac 12 (2 \lambda) = \sqrt{1 - |\langle x,y \rangle|}. $$

Thus, it suffices to show that $$ \sqrt{2}\sqrt{1 - \operatorname{Re}\langle x,y \rangle} \geq \sqrt{1 - |\langle x,y \rangle|}. $$ Indeed, we have $$ \sqrt{2}\sqrt{1 - \operatorname{Re}\langle x,y \rangle} \geq \sqrt{1 - |\langle x,y \rangle|} \iff\\ 2(1 - \operatorname{Re}\langle x,y \rangle) \geq 1 - |\langle x, y \rangle| \iff \\ 1 + |\langle x, y \rangle| \geq 2 \operatorname{Re}\langle x,y \rangle \iff\\ \frac{1 + |\langle x, y \rangle|}{2} \geq \operatorname{Re}\langle x,y \rangle. $$ The last inequality can be shown to hold as follows: by Cauchy Schwarz, $|\langle x, y \rangle| < 1$. So, $$ \frac{1 + |\langle x, y \rangle|}{2} \geq |\langle x,y \rangle| = \sqrt{(\operatorname{Re}\langle x,y \rangle)^2 + (\operatorname{Im} \langle x,y\rangle)^2} \\ \qquad \qquad \quad\geq \sqrt{(\operatorname{Re}\langle x,y \rangle)^2} = |\operatorname{Re}\langle x,y \rangle| \geq \operatorname{Re}\langle x,y \rangle. $$