3
$\begingroup$

Let $V$ be a finite dimensional complex Hilbert space. Let $L(V)$ denote the collection of all linear operators from $V$ to $V$. An operator $\mathcal{E}:L(V)\rightarrow L(V)$ is said to be positive if whenever $A\geq 0$, we have $\mathcal{E}(A)\geq 0$ as well. We say that $\mathcal{E}$ is completely positive if $\mathcal{E}\otimes 1_{L(W)}:L(V\otimes W)\rightarrow L(V\otimes W)$ is positive for each finite dimensional complex Hilbert space $W$. A linear mapping $\mathcal{E}:L(V)\rightarrow L(V)$ is said to be trace preserving if $\text{Tr}(\mathcal{E}(A))=\text{Tr}(A)$ whenever $A\in L(V)$. A channel is a completely positive trace preserving map $\mathcal{E}:L(V)\rightarrow L(V)$. A unital channel is a channel where $\mathcal{E}(1_V)=1_V$.

If $A_1,\dots,A_r\in L(V)$, then define a mapping $\Phi(A_1,\dots,A_r):L(V)\rightarrow L(V)$ by $\Phi(A_1,\dots,A_r)(X)=A_1XA_1^*+\dots A_rXA_r^*$. Then the mapping $\Phi(A_1,\dots,A_r)$ is a completely positive mapping, and every completely positive mapping $\mathcal{E}:L(V)\rightarrow L(V)$ is of this form.

Define $$\rho_{2}(A_1,\dots,A_r)=\rho(\Phi(A_1,\dots,A_r))^{1/2}.$$

The Cauchy-Schwarz inequality holds for $\rho_{2}$: $$\rho(A_1\otimes B_1+\dots+A_r\otimes B_r)\leq\rho_2(A_1,\dots,A_r)\rho_2(B_1,\dots,B_r).$$

Define $$\rho_{2,d}(A_1,\dots,A_r)$$ $$=\sup\{\frac{\rho(A_1\otimes X_1+\dots+A_r\otimes X_r)}{\rho_{2}(X_1,\dots,X_r)}\mid X_1,\dots,X_r\in M_d(\mathbb{C}),\rho_{2}(X_1,\dots,X_r)\neq 0\}.$$ Observe that $\rho_{2,d}(A_1,\dots,A_r)\leq\rho_{2,g}(A_1,\dots,A_r)\leq\rho_2(A_1,\dots,A_r)$ whenever $d\leq g$, and $\rho_{2,d}(A_1,\dots,A_r)=\rho_2(A_1,\dots,A_r)$ whenever $d\geq\dim(V).$

Theorem: $\Phi(A_1,\dots,A_r)=\Phi(B_1,\dots,B_r)$ if and only if there is an $r\times r$ unitary matrix $(u_{i,j})_{i,j}$ where $B_{i}=\sum_{j=1}^{r}u_{i,j}A_{j}$ for $1\leq i\leq r$.

The $\leftarrow$ direction is easy to prove, and a proof of the direction $\rightarrow$ can be found in the book The Theory of Quantum Information by John Watrous.

Lemma: Suppose that $A_1,\dots,A_r,B_1,\dots,B_r,X_1,\dots,X_r,Y_1,\dots,Y_r$ are matrices over the same field and whose dimensions are proper so that $A_1\otimes X_1+\dots A_r\otimes X_r,B_1\otimes Y_1+\dots B_r\otimes Y_r$ both make sense and have the same dimension. Suppose that $(u_{i,j})_{i,j},(v_{i,j})_{i,j}$ are $r\times r$-matrices over the field $K$ and $(u_{i,j})_{i,j}^{-1}=(v_{i,j})_{i,j}^{T}$. Furthermore, suppose that $A_i=\sum_{j=1}^{r}u_{i,j}B_j,X_i=\sum_{j=1}^{r}v_{i,j}Y_j$ for $1\leq i\leq r$. Then $$A_1\otimes X_1+\dots A_r\otimes X_r=B_1\otimes Y_1+\dots B_r\otimes Y_r.$$

I was able to prove the following fact (it is not too hard to verify that this fact is correct using computer calculations).

Theorem: If $\Phi(A_1,\dots,A_r)=\Phi(B_1,\dots,B_r)$, then $\rho_{2,d}(A_1,\dots,A_r)=\rho_{2,d}(B_1,\dots,B_r)$.

Proof: If $\Phi(A_1,\dots,A_r)=\Phi(B_1,\dots,B_r)$, then there is a unitary map $(u_{i,j})_{i,j}$ where $A_i=\sum_{j=1}^{r}u_{i,j}\cdot B_j$ for $1\leq i\leq r$. Therefore, set $(v_{i,j})_{i,j}=((u_{i,j})_{i,j}^{-1})^{T}$. Then whenever $X_1,\dots,X_r\in M_n(\mathbb{C})$, and $Y_i=\sum_{j=1}^{r}v_{i,j}X_{j}$, we have $\rho_{2}(X_1,\dots,X_r)=\rho_{2}(Y_1,\dots,Y_r)$, and $\rho(A_1\otimes X_1+\dots+A_r\otimes X_r)=\rho(B_1\otimes Y_1+\dots+B_r\otimes Y_r)$. Therefore, $$\frac{\rho(A_1\otimes X_1+\dots+A_r\otimes X_r)}{\rho_2(X_1,\dots,X_r)}=\frac{\rho(B_1\otimes Y_1+\dots+B_r\otimes Y_r)}{\rho_2(Y_1,\dots,Y_r)}$$ whenever $\rho_2(Y_1,\dots,Y_r)\neq 0$, so $\rho_{2,d}(B_1,\dots,B_r)\leq\rho_{2,d}(A_1,\dots,A_r)$. The reverse inequality is established in a similar manner. Q.E.D.

Therefore, if $\mathcal{E}:L(V)\rightarrow L(V)$ is a completely positive mapping, then we can define $\rho_{2,d}(\mathcal{E})$ by letting $\rho_{2,d}(\mathcal{E})=\rho_{2,d}(A_1,\dots,A_r)^{2}$ where $\mathcal{E}=\Phi(A_1,\dots,A_r)$.

If $d\geq\dim(V)$, then $\rho_{2,d}(\mathcal{E})=\rho(\mathcal{E})$.

If $1\leq d<\dim(V)$, then is there a characterization of $\rho_{2,d}(\mathcal{E})$ that does not require us to decompose $\mathcal{E}$ as $\Phi(A_1,\dots,A_r)$? Is there such a characterization of $\rho_{2,d}(\mathcal{E})$ in the special case when $\mathcal{E}$ is a channel? What about when $\mathcal{E}$ is a unital channel or a mixed unitary channel? Can $\rho_{2,d}(\mathcal{E})$ be generalized to the case when $\mathcal{E}$ is no longer necessarily completely positive?

It would be great if there were a quantum algorithm that often efficiently computes $\rho_{2,d}(\mathcal{E})$ when there is a quantum computer that sends the mixed state $D$ to the mixed state $\mathcal{E}(D)$, but perhaps this is too much to ask for.

Added 5/27/2022

Suppose that $(e_{a}\mid a\in\Sigma)$ is an orthonormal basis for $W$. Let $A:V\rightarrow V\otimes W$ be a linear operator. Suppose that $A=\sum_{a\in\Sigma}A_a\otimes e_a$. Then the mapping $\mathcal{E}_A:L(V)\rightarrow L(V)$ defined by letting $\mathcal{E}_A(X)=\text{Tr}_W(AXA^*)$ ($\text{Tr}_W$ denotes the partial trace) is a completely positive mapping, and $\text{Tr}_W(AXA^*)=\sum_{a\in\Sigma}A_aXA_a^*$, so every completely positive mapping is of the form $\mathcal{E}_A$ for some $A$.

Furthermore, if $B\in L(U,W\otimes U)$, and $B=\sum_{b\in\Sigma}e_b\otimes B_b$, then $$\text{Tr}_W(A\otimes B^*)=\sum_{a\in\Sigma}A_a\otimes B_b^*.$$

Therefore, $$\rho_{2,d}(\mathcal{E})^{1/2}= \sup\{\frac{\rho(\text{Tr}_W(A\otimes B^*))}{\rho(\mathcal{E}_{B})^{1/2}}\mid B\in L(U,W\otimes U)\}$$ whenever $\dim(U)=d$. This characterization of $\rho_{2,d}(\mathcal{E})^{1/2}$ depends on the choice of $A$ and is not much different than the other definition of $\rho_{2,d}(\mathcal{E})^{1/2}$. It is known that if $\mathcal{E}_{A_1}=\mathcal{E}_{A_2}$, then $A_1=(1_{V}\otimes O)A_2$ for some unitary map $O\in L(W)$.

$\endgroup$
1
  • $\begingroup$ I apologize if I'm missing something obvious, but can you clarify what exactly $d$ is? I feel like it should be something like a dimension of an ancilla space, but I can't quite pin it down since I don't see it actually in the definition of $\rho_{2,d}$ anywhere. Is $d = n$? $\endgroup$ Commented May 26, 2022 at 1:49

1 Answer 1

1
$\begingroup$

Yes. We can characterize $\rho_{2,d}(\mathcal{E})$ whenever $\mathcal{E}$ is completely positive without needing to first decompose $\mathcal{E}$ as $\Phi(A)$ or $\Phi(A_1,\dots,A_r).$ As a consequence, we can define $\rho_{2,d}(\mathcal{E})$ for all linear operators $\mathcal{E}:L(V)\rightarrow L(V)$, but if $\mathcal{E}$ is not completely positive, then $\rho_{2,d}(\mathcal{E})$ is usually infinite, so $\rho_{2,d}(\mathcal{E})$ it not well behaved when we do not assume that $\mathcal{E}$ is completely positive.

Let $U_1,U_2,V_1,V_2,U_1^\sharp,U_2^\sharp,V_1^\sharp,V_2^\sharp,U,V$ be finite dimensional complex inner product spaces.

If $A_1,\dots,A_r:U_2\rightarrow V_2,B_1,\dots,B_r:U_1\rightarrow V_1$ are linear, then define a mapping $\Gamma(A_1,\dots,A_r;B_1,\dots,B_r):L(U_1,U_2)\rightarrow L(V_1,V_2)$ by letting $$\Gamma(A_1,\dots,A_r;B_1,\dots,B_r)(X)=\sum_{k=1}^rA_kXB_k^*.$$

Suppose now that $A_1,\dots,A_r:U_2\rightarrow V_2,B_1,\dots,B_r:U_1\rightarrow V_1$. Let $S:L(U_2,V_2)\rightarrow L(U_2^\sharp,V_2^\sharp)$ be linear and let $T:L(U_1,V_1)\rightarrow L(U_1^\sharp,V_1^\sharp)$ also be linear. Then define $\mho(\Gamma(A_1,\dots,A_r;B_1,\dots,B_r),S,T):L(U_1^\sharp,U_2^\sharp)\rightarrow L(V_1^\sharp,V_2^\sharp)$ by letting $$\mho(\Gamma(A_1,\dots,A_r;B_1,\dots,B_r),S,T)=\Gamma(S(A_1),\dots,S(A_r);T(B_1),\dots,T(B_r)).$$ The mapping $\mho$ is well-defined; i.e. it depends on $\Gamma(A_1,\dots,A_r;B_1,\dots,B_r)$ rather than the particular choice of $A_1,\dots,A_r;B_1,\dots,B_r$.

$\rho_{2,d}(\mathcal{E})$ is the maximum value of $$\frac{\rho(\mho(\mathcal{E},1_{L(V)},T))^2}{\rho(\mho(\mathcal{E},T,T))}$$ where $T:L(V)\rightarrow L(U)$ is a linear operator and $\dim(U)=d$, and this definition generalizes to all linear operators $\mathcal{E}:L(V)\rightarrow L(V)$ when we replace the word 'maximum' with 'supremum'.

Suppose now that $\mathcal{E}=\Gamma(A_1,\dots,A_r;B_1,\dots,B_r)$ where $A_1,\dots,A_r,B_1,\dots,B_r$ are linearly independent and $\Phi(A_1,\dots,A_r)$ is not nilpotent. Let $T:L(V)\rightarrow L(V)$ be a linear mapping where $T(A_j)=A_j,T(B_j)=\alpha\cdot A_j$ for $1\leq j\leq r$.

Then $\mho(\mathcal{E},1_{L(V)},T)=\mho(\mathcal{E},T,T)=\alpha\cdot\Phi(A_1,\dots,A_r)$.

Therefore, $$\rho_{2,d}(\mathcal{E})\geq\frac{\rho(\alpha\cdot\Phi(A_1,\dots,A_r))^2}{\rho(\alpha\cdot\Phi(A_1,\dots,A_r))}=\alpha\cdot\rho(\Phi(A_1,\dots,A_r)).$$ Since $\alpha$ can be made arbitrarily large, we have $\rho_{2,d}(\mathcal{E})=\infty$ in this case.

A modest generalization: added 8/15/2022

There is another way to generalize $\rho_{2,d}(\mathcal{E})$ to some operators that are not completely positive, but this generalization is based on a conjecture.

Conjecture: Suppose that $\mathcal{E}:L(V)\rightarrow L(V)$ is completely positive and $\alpha\geq 0$. Then $\rho_{2,d}(\mathcal{E}+\alpha\cdot 1_{L(V)})=\rho_{2,d}(\mathcal{E})+\alpha$.

From this conjecture, we can define $\rho_{2,d}(\mathcal{E})$ whenever there is some $\alpha\geq 0$ where $\mathcal{E}+\alpha\cdot 1_{L(V)}$ is completely positive by letting $\rho_{2,d}(\mathcal{E})=\rho_{2,d}(\mathcal{E}+\alpha\cdot 1_{L(V)})-\alpha$. Here, we can have negative values of $\rho_{2,d}(\mathcal{E})$, so $\rho_{2,d}$ more closely resembles the maximum value of a Hermitian operator than the spectral radius.

Projective mappings: added 3/21/2023

Define $\rho_{2,d}^P(A_1,\dots,A_r)$ to be the supremum of all values of the form $$\frac{\rho(A_1\otimes\overline{RA_1S}+\dots+A_r\otimes\overline{RA_rS})}{\rho(RA_1S\otimes\overline{RA_1S}+\dots+RA_rS\otimes\overline{RA_rS})^{1/2}}$$ where $R\in M_{d,n}(\mathbb{C}),S\in M_{n,d}(\mathbb{C})$. I conjecture that $\rho_{2,d}^P(A_1,\dots,A_r)=\rho_{2,d}(A_1,\dots,A_r)$ (computer calculations support this conjecture at least sometimes), but it seems like $\rho_{2,d}^P(A_1,\dots,A_r)$ is easier to work with than $\rho_{2,d}(A_1,\dots,A_r)$.

If $S:U\rightarrow V,R:V\rightarrow U$ are linear maps, then define a mapping $T_{R,S}:L(V)\rightarrow L(U)$ by setting $T_{R,S}(A)=RAS$ for $A\in L(V)$.

$$\mho(\Gamma(A_1,\dots,A_r;B_1,\dots,B_r),T_{R,S},T_{R,S})(X)$$

$$=\Gamma(T_{R,S}(A_1),\dots,T_{R,S}(A_r);T_{R,S}(B_1),\dots,T_{R,S}(B_r))(X)$$

$$=\Gamma(RA_1S,\dots,RA_rS;RB_1S,\dots,RB_rS)(X)=\sum_{k=1}^{r}RA_kSX(RB_kS)^*$$ $$=\sum_{k=1}^rRA_kSXS^*B^*_kR^* =R\big(\Gamma(A_1,\dots,A_r;B_1,\dots,B_r)(SXS^*)\big)R^*.$$

Similarly,

$$\mho(\Gamma(A_1,\dots,A_r;B_1,\dots,B_r),1_{L(V)},T_{R,S})(X) =\Gamma(A_1,\dots,A_r;RB_1S,\dots,RB_rS)(X)$$

$$=\sum_{k=1}^rA_kX(RB_kS)^*=\sum_{k=1}^rA_kXS^*B_k^*R^* =\big(\Gamma(A_1,\dots,A_r;B_1,\dots,B_r)(XS^*)\big)R^*.$$

Therefore, $\mho(\mathcal{E},T_{R,S},T_{R,S})(X)=R\big(\mathcal{E}(SXS^*)\big)R^*$ and $\mho(\mathcal{E},1_{L(V)},T_{R,S})(X)=\big(\mathcal{E}(XS^*)\big)R^*$ whenever $\mathcal{E}:L(V)\rightarrow L(V)$ and $R,S,X$ are suitable linear operators. Therefore, if $\mathcal{E}:L(V)\rightarrow L(V)$, then define $\mho_{R,S}^-(\mathcal{E})(X)=\big(\mathcal{E}(XS^*)\big)R^*$ and $\mho_{R,S}^+(\mathcal{E})(X)=R\big(\mathcal{E}(SXS^*)\big)R^*$.

$\rho_{2,d}^P(A_1,\dots,A_r)$ is the supremum of all values of the form $$\frac{\rho(\mho_{R,S}^-(\Phi(A_1,\dots,A_r)))}{\rho(\mho_{R,S}^+(\Phi(A_1,\dots,A_r))^{1/2}}.$$ Therefore, we may define $\rho_{2,d}^P(\mathcal{E})$ for all completely positive operators $\mathcal{E}:L(V)\rightarrow L(V)$ by setting $\rho_{2,d}^P(\mathcal{E})=\rho_{2,d}^P(A_1,\dots,A_r)^2$ whenever $\mathcal{E}=\Phi(A_1,\dots,A_r)$. Then $\rho_{2,d}^P(\mathcal{E})$ is the supremum of all values of the form $\frac{\rho(\mho_{R,S}^-(\mathcal{E}))^2}{\rho(\mho_{R,S}^+(\mathcal{E}))}$ where $R\in L(U,V),S\in L(V,U)$ and $U$ is a complex inner product space $\dim(U)=d$. This definition of $\rho_{2,d}^P(\mathcal{E})$ makes sense even when $\mathcal{E}:L(V)\rightarrow L(V)$ and $V$ is an infinite dimensional complex Hilbert space (we will probably need to use Stinespring's dilation theorem to generalize $\rho_{2,d}$ to infinite dimensional spaces).

Example: $\rho_{2,d}^P(\mathcal{E})$ can be infinite for superoperators which are positive but not completely positive. For example, the transpose map $T:M_n(\mathbb{C})\rightarrow M_n(\mathbb{C})$ defined by $T(X)=X^T$ is positive but not completely positive whenever $n>1$, and we shall prove that $T$ is not completely positive by showing that $\rho_{2,d}^P(T)=\infty$. A straightforward calculation yields $\rho_{2,d}^P(T)=\sup_{R\in M_{d,n}(\mathbb{C}),S\in M_{n,d}(\mathbb{C})}\frac{\rho(SR)^2}{\rho(R\overline{S}\overline{R}S)}.$

If $R,S$ are rank-1 matrices, then we can set $R=uv^*,S=wx^*$ for vectors $u,v,w,x$. In this case, $\frac{\rho(SR)^2}{\rho(R\overline{S}\overline{R}S)}=|\frac{v^*w}{v^Tw}|^2$. If $v=w=[1,i]^T$, then $\frac{\rho(SR)^2}{\rho(R\overline{S}\overline{R}S)}=(2/0)^2=+\infty.$

It seems like a good way of showing that a superoperator $\mathcal{E}:L(V)\rightarrow L(V)$ is not completely positive is to show that $\rho_{2,d}^P(\mathcal{E})>\rho(\mathcal{E})$ by finding matrices $R,S$ where $\rho(\mho_{R,S}^-(\mathcal{E}))^2>\rho(\mho_{R,S}^+(\mathcal{E}))\cdot\rho(\mathcal{E})$.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.