This paper introduces non-commutative analogs of classical graph parameters and theorems, providing new bounds on quantum channel capacities and extending classical combinatorial concepts into the quantum domain.
Contribution
It develops non-commutative versions of key graph invariants and the Sandwich Theorem, offering improved bounds on quantum zero-error capacities.
Findings
01
Quantum versions of the vertex packing polytope and theta body are established.
02
A quantum Sandwich Theorem analogous to the classical one is proved.
03
New upper bounds on quantum channel capacities surpass previous results.
Abstract
We define non-commutative versions of the vertex packing polytope, the theta convex body and the fractional vertex packing polytope of a graph, and establish a quantum version of the Sandwich Theorem of Gr\"{o}tschel, Lov\'{a}sz and Schrijver. We define new non-commutative versions of the Lov\'{a}sz number of a graph which lead to an upper bound of the zero-error capacity of the corresponding quantum channel that can be genuinely better than the one established previously by Duan, Severini and Winter. We define non-commutative counterparts of widely used classical graph parameters and establish their interrelation.
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Full text
Sandwich theorems and capacity bounds for non-commutative graphs
G. Boreland
Mathematical Sciences Research Centre,
Queen’s University Belfast, Belfast BT7 1NN, United Kingdom
Mathematical Sciences Research Centre,
Queen’s University Belfast, Belfast BT7 1NN, United Kingdom,
and
School of Mathematical Sciences, Nankai University, 300071 Tianjin, China
We define non-commutative versions of the vertex packing polytope, the theta convex body and the
fractional vertex packing polytope of a graph, and
establish a quantum version of the Sandwich Theorem of Grötschel, Lovász and Schrijver.
We define new non-commutative versions of the Lovász number of a graph which
lead to an upper bound of the zero-error
capacity of the corresponding quantum channel that can be genuinely better than the one established
by Duan, Severini and Winter in [5].
We define
non-commutative counterparts of widely used classical graph parameters and establish their interrelation.
The use of graphs in the study of information theoretic questions has origins in Shannon’s seminal paper [18],
where he laid the foundations of zero-error information theory.
With a given information channel N, Shannon associated a graph GN, called the
confusability graph of the channel, and showed that the zero-error transmission properties of N
are captured in their entirety by GN. In particular, he defined the
zero-error capacityc0(N) of the channel N
as an asymptotic parameter involving the independence numbers of
the strong powers of GN.
While the information theoretic importance of c0(N) is easy to appreciate, its computation remains
a difficult problem, due to the high computational complexity of the independence number.
An upper bound for c0(N), computable in polynomial time, was introduced by Lovász in [14].
The parameter θ(G) of a given graph G, defined therein, satisfies the Sandwich Theorem
[TABLE]
here α(G) is the independence number of G,
while χf(Gc) is the fractional chromatic number of its complement Gc.
The Sandwich Theorem thus provides a simultaneous bound for the outer parameters, which have high computational complexity,
and plays an important role in combinatorial optimisation [7].
A stronger and more powerful version of the Sandwich Theorem was established in [6] (see also [10]),
where convex bodies arising from vertex packings of a graph G were introduced
– these are the vertex packing polytope vp(G), the fractional vertex packing polytope fvp(G) and the
theta body thab(G) – and shown to satisfy the inclusions
[TABLE]
Inequalities (1) are then obtained by optimising the trace functional over the chain (2).
Its terms are particular examples of convex corners, that is, hereditary closed convex subsets of R+d
[4, 7].
The importance of the inclusions (2) comes from the significance of considering
weighted versions of the trace functional in optimisation problems for graphs [10].
Quantum information analogues of the aforementioned objects and results were initiated in [5], where
the authors defined a suitable version of the confusability graph of a quantum channel Φ as
an operator subsystem (that is, a selfadjoint subspace containing the identity matrix) S
of the domain Md of Φ, and showed that it captures the zero-error properties of Φ.
In particular, they defined the (classical) zero-error capacity of the channel Φ and showed that
it depends solely on the operator system S.
A classical graph G gives rise in a canonical fashion to an operator system that remembers G
[16]. This justifies calling arbitrary operator systems in Mdnon-commutative graphs,
and pursuing their study as a non-commutative version of graph theory.
Advances in this direction were recently made in [13], where classical parameters such as the
intersection number, the minimum semi-definite rank and the orthogonal rank of the
complement were lifted to the non-commutative setting and given
a quantum informational interpretation,
and in [21], where a version of the Ramsey Theorem was established for operator systems.
A quantum version of the Lovász number was defined in [5], and shown to be an upper bound of the
zero-error capacity of quantum channels, computable via semi-definite programming.
The purpose of this paper is two-fold. Firstly, we initiate the study of non-commutative convex corners, establish
a quantum version of the Sandwich Theorem (2) and define a
new non-commutative version of the classical Lovász number that is an upper bound of the zero-error
capacity of the corresponding quantum channel and which can be genuinely better than the one established in [5].
Secondly, we continue the development of non-commutative graph theory by defining
non-commutative counterparts of widely used classical graph parameters and establishing their interrelation.
In more detail, the paper is organised as follows.
After some initial definitions and preliminary observations in Section 2, we
introduce in Section 3non-commutative convex corners, focusing on three convex corners
associated with a non-commutative graph S⊆Md:
the abelian projection cornerap(S), which we show to be a quantisation of the vertex packing polytope,
and the anti-blockers cp(S)♯ and fp(S)♯ of the clique and full projection cornerscp(S) and fp(S),
which turn out to be
distinct quantisations of the fractional vertex packing polytope. We establish a first chain of inclusions between these
convex corners, introduce several new non-commutative graph parameters that generalise the clique and the
fractional clique numbers of a graph and of its complement, and evaluate these parameters in some special
cases.
In Section 4, we introduce a non-commutative version th(S) of the theta-body of a graph
and establish the chain of inclusions
[TABLE]
as a quantum version of (2).
Optimising the trace functional over (3) leads to a quantisation θ(S) of the classical
Lovász number, different from the one
introduced in [5], and to a numerical version of the inequalities (1).
We do not know whether θ is submultiplicative for the tensor product, and hence whether
it is an upper bound of the zero-error capacity.
This motivates the development in Section 5, where we introduce
yet another non-commutative version θ^(S) of the Lovász number.
We show that θ^(S) is an upper bound of the zero-error capacity of S,
which can be genuinely better than the non-commitative Lovász number of [5].
In fact, we show that θ^(S) is a genuine improvement of the
complexity bound β(S) found in [13].
Our results imply that the multiple characterisations [14] of the Lovász number of a graph lead to
(at least two) distinct parameters in the non-commutative case.
In Section 6 we establish some further properties of the
parameters introduced in the previous sections, the most important of which is
the continuity of the maps S→th(S) and S→θ(S).
While we do not know whether θ=θ^, we show that these two parameters
take the minimal value 1 only in the case of the complete non-commutative graph.
We prove the stability of the parameters θ and θ^ under amplification, which
constitutes another important difference between them and the parameter introduced in [5].
We finish the paper with a short section containing some open problems.
2. Definitions and basic properties
In this section, we set notation, recall some background from [5]
and introduce various concepts that will be used in the sequel.
Given a subset S of a vector (resp. topological) space V, we denote by conv(S)
(resp. S) the convex hull (resp. the closure) of S.
We denote by R+d the set of all vectors in Rd with non-negative entries.
Let H be a Hilbert space of finite dimension d, which will be fixed throughout the paper
unless stated otherwise. We denote by
L(H) the algebra of all linear transformations on H, equipped with the operator norm ∥⋅∥.
We denote by I (or Id) the identity operator on H.
Given an orthonormal basis of H, we make the canonical identification L(H)≡Md.
We will often write Md in the place of L(H) even if we have not fixed a specific basis.
We denote by Tr the trace functional on L(H); if A=(ai,j)i,j=1d∈L(H) then
Tr(A)=∑i=1dai,i.
We let At be the transpose of the matrix A∈Md.
We use ⟨⋅,⋅⟩ to denote both vector space duality and inner products, which we assume to be
linear on the first variable.
Note that the dual space of Md can be canonically identified with Md via the pairing
⟨A,B⟩=Tr(AB).
We equip Md with the Hilbert-Schmidt inner product (A,B)→Tr(B∗A), A,B∈Md.
As usual, given a subspace F of a Hilbert space, F⊥ denotes its orthogonal complement.
If ξ,η∈H, we write ξη∗ for the rank one operator on H given by (ξη∗)(ζ)=⟨ζ,η⟩ξ.
A subspace S⊆L(H) is called an operator system if I∈S and
A∗∈S whenever A∈S. In this case, we say that S is a non-commutative graph onH.
We denote by S+ the cone of all positive operators in S.
It is clear that if S⊆L(H) is an operator system and m∈N
then the space Mm(S) of all m by m matrices with entries in S is an operator system
in L(Hm), where Hm is the direct sum of m copies of H.
Let G=(X,E) be an undirected graph without loops, with vertex set X of cardinality d and edge set E.
We denote by Gc the graph complement of G, that is, Gc=(X,E~) where,
for x=y, we have that {x,y}∈E~ if and only if {x,y}∈E.
We write x∼y if {x,y}∈E and x≃y if x∼y or x=y.
Identifying X with [d]:={1,…,d}, we let (ex)x∈X be the canonical orthonormal basis of
H≅Cd, and set
[TABLE]
Let DX be the diagonal matrix algebra
corresponding to the basis (ex)x∈X and
Δ:Md→DX be the conditional expectation.
(We sometimes write Dd in the place of DX.)
For a subset F⊆X, we let χF be the characteristic function of F
and set PF=∑x∈Fexex∗.
We have that SG is an operator system and a DX-bimodule in the sense that
BTA∈SG whenever T∈SG and A,B∈DX.
Operator systems of the form SG for some graph G will be called
graph operator systems; it is straightforward to see that these are precisely the
operator systems acting on H that are DX-bimodules.
Let S and T be operator systems. A linear map φ:S→T
is called unital if φ(I)=I, and completely positive if
φ(m)(Mm(S)+)⊆Mm(T)+ for every m∈N,
where φ(m):Mm(S)→Mm(T) is the map given by φ(m)((ai,j))=(φ(ai,j)).
The map φ is called a complete order isomorphism if φ is completely positive,
bijective and φ−1 is completely positive.
It was shown in [16] that, if G1 and G2 are graphs then
SG1 is unitally
completely order isomorphic to SG2 precisely when G1 is graph isomorphic to G2.
The concept in (i) of the following definition was introduced in [5].
Definition 2.1**.**
Let H be a finite dimensional Hilbert space and S⊆L(H) be an operator system.
A set {ξi}i=1m⊆H of mutually orthogonal unit vectors is called
(i) S-independent
if {ξiξj∗:i=j}⊆S⊥;
(ii)
S-clique
if {ξiξj∗:i=j}⊆S.
Definition 2.2**.**
Let H be a finite dimensional Hilbert space and
S⊆L(H) be an operator system. A projection P∈L(H) will be called
(i) S-abelian
if PSP is contained in an abelian C-subalgebra of L(H);*
(ii) S-full if L(PH)⊕0P⊥⊆S.
(iii) S-clique if its range is the span of an S-clique.
We denote the set of all S-abelian (resp. S-full, S-clique) projections by
Pa(S) (resp. Pf(S), Pc(S)).
**Remarks. (i) **
The condition L(PH)⊕0P⊥⊆S will often be written
simply L(PH)⊆S.
If a projection P is S-full then P∈S.
**(ii) **
Every S-full projection is S-clique. The converse does not hold true
even in the case where S is a graph operator system.
For example, let G be the full bipartite graph between sets X and Y
(so that V(G)=X∪Y, with X and Y disjoint), where ∣X∣>1.
Let v=∣X∣1χX and w=∣Y∣1χY, viewed as (unit) vectors in C∣V(G)∣.
Then {v,w} is an SG-clique, but the projection onto span{v,w} is not S-full since
no two vertices in X are adjacent.
Part (i) of the next proposition was communicated to us by Vern I. Paulsen.
Proposition 2.3**.**
Let H be a finite dimensional Hilbert space and S⊆L(H) be an operator system.
(i) A projection P∈L(H) is S-abelian if and only if
there exists an orthonormal basis of PH that is an S-independent set.
(ii) A projection P∈S is S-full if and only if every orthonormal basis of PH is an S-clique.
Proof.
(i)
Suppose that the orthonormal set {ξi}i=1m⊆H
is S-independent and let P be the projection onto its span.
If T∈S and i=j then T⊥ξiξj∗ and thus
[TABLE]
hence, PTP is contained in the abelian algebra span{ξiξi∗:i=1,…,m}.
Conversely, assume that P is S-abelian, and let D⊆L(PH) be a maximal
abelian C*-subalgebra such that PSP⊆D. Let (ξi)i=1m be a
family of mutually orthogonal unit vectors whose span is P
such that span{ξiξi∗:i=1,…,m}⊆D.
Since (ξiξj∗)i,j is a linearly independent family, (4) shows that
⟨Tξj,ξi⟩=0 whenever i=j; thus,
the set {ξi}i=1m is S-independent.
(ii)
Suppose that every orthonormal basis of PH is an S-clique.
Fix an S-clique {ξi}i=1k that spans PH,
and i,j with 1≤i=j≤k.
Then ξiξj∗∈S.
Since ξi+ξj⊥ξi−ξj, we have
[TABLE]
Thus, ξiξi∗−ξjξj∗∈S.
It follows that
[TABLE]
and so ξ1ξ1∗∈S.
By symmetry, ξiξi∗∈S for all i∈[k].
Since the family {ξi}i=1k is an S-clique,
we conclude that L(PH)=span{ξiξj∗:i,j∈[k]}⊆S,
and so P is S-full.
Conversely, suppose that P is S-full, that is, L(PH)⊆S.
If {ξi}i=1k is an orthonormal basis of PH then
clearly ξiξj∗∈L(PH) and hence ξiξj∗∈S, for all i=j.
Thus, {ξi}i=1k is an S-clique.
∎
We next consider a natural candidate for a graph complement in the non-commutative case.
Definition 2.4**.**
Let S be a non-commutative graph. The complementSc of S is
the operator system Sc=S⊥+CI.
Remark 2.5**.**
If S is a non-commutative graph then S=Scc.
Proof.
Clearly,
[TABLE]
The equality follows from the fact that the left and the right hand side in
(5) have the same dimension.
∎
Proposition 2.6**.**
Let H be a finite dimensional Hilbert space and S⊆L(H) be an operator system.
(i) A subset {ξi}i=1k⊆H is S-independent if and only if it is an Sc-clique.
(ii) A subset {ξi}i=1k⊆H is an S-clique if and only if it is Sc-independent.
Thus, a projection P is S-abelian if and only if P is Sc-clique.
Proof.
Suppose that the set {ξi}i=1k⊆H is S-independent; thus,
{ξiξj∗:i=j}⊆S⊥. Since
S⊥⊆Sc, we conclude that
{ξi}i=1k is an Sc-clique.
Suppose that {ξi}i=1k is an S-clique.
Then ξiξj∗⊥S⊥ whenever i=j.
Trivially, ξiξj∗⊥CI whenever i=j; thus,
ξiξj∗⊥(S⊥+CI) whenever i=j, and so
the set {ξi}i=1k is Sc-independent.
(i) Suppose that {ξi}i=1k is an Sc-clique. By the previous paragraph,
{ξi}i=1k is Scc-independent. By Remark 2.5,
{ξi}i=1k is S-independent.
(ii) Suppose that {ξi}i=1k is an Sc-independent set.
By the first paragraph, {ξi}i=1k is an Scc-clique.
By Remark 2.5, {ξi}i=1k is an S-clique.
The remaining claims follow from Proposition 2.3.
∎
Remark 2.7**.**
Let H be a finite dimensional Hilbert space and S⊆L(H) be an operator system.
The sets Pa(S), Pf(S) and Pc(S) are closed.
**
Proof.
Suppose that (Pn)n∈N is a sequence of S-full projections with limn→∞Pn=P.
For every A∈L(H) with A=PAP we have A=limn→∞PnAPn;
since PnAPn∈S for each n and S is closed, we have that A∈S.
Thus, Pf(S) is closed.
Assume that
(Pn)n∈N is a convergent sequence of S-abelian projections with limit P.
For all A,B∈S, we have
[TABLE]
It follows that Pa(S) is closed; by Proposition 2.6, Pc(S) is closed,
and the proof is complete.
∎
3. The first sandwich theorem
In this section, we prove the first of our sandwich theorems. For clarity, the section is split in three subsections.
3.1. Convex corners from non-commutative graphs
Part (ii) of the following definition contains a classical notion arising in Graph Theory [4],
while part (i) introduces a suitable non-commutative version that will play a central role subsequently.
Definition 3.1**.**
(i) Let H be a Hilbert space of dimension d.
A convex corner in L(H) (or in Md)
is a non-empty closed convex subset A of L(H)+ such that
[TABLE]
(ii) If d∈N,
a diagonal convex corner in Md is
a non-empty closed convex subset C of Dd+, such that
[TABLE]
Conditions (6) and (7) will be referred to as hereditarity.
If A is a non-empty subset of L(H)+, let
[TABLE]
and call A♯ the anti-blocker of A.
Similarly [4], if C is a non-empty subset of Dd+,
let
[TABLE]
and call C♭ the diagonal anti-blocker of C.
The following facts are immediate.
Remark 3.2**.**
Let A⊆Md+ (resp. C⊆Dd+) be a non-empty set. Then
(i) the set A♯ (resp. C♭) is a convex corner (resp. a diagonal convex corner) in Md;
(ii) A♯♯♯=A♯ and C♭♭♭=C♭.
**
Let H be a finite dimensional Hilbert space.
For a subset C⊆L(H), we let
[TABLE]
Proposition 3.3**.**
Let P⊆L(H)+ be a non-empty bounded set and A=her(conv(P)).
(i) The set A is a convex corner. Moreover, A♯=P♯.
(ii) Assume that P is a closed set of projections such that if P∈P and P′ is a projection with
P′≤P then P′∈P. If Q is a projection with Q∈A then Q∈P.
Proof.
(i) It is clear that A is hereditary.
Since conv(P) is convex, A is convex. Suppose that (Tn)n∈N⊆A
and Tn→n→∞T. Let Cn∈conv(P) be such that Tn≤Cn, n∈N.
Since conv(P) is compact, (Cn)n∈N has a cluster point, say C, in conv(P).
But then T≤C and hence A is closed.
Since P⊆A, we have that A♯⊆P♯.
The reverse inclusion follows from basic properties of the trace functional.
(ii) Let T∈conv(P) be such that Q≤T. Then Q≤QTQ and hence
1=∥Q∥≤∥QTQ∥≤∥T∥≤1, showing that ∥QTQ∥=1. Thus, QTQ≤Q and hence
Q=QTQ∈conv(QPQ). Since Q is an extreme point of
the unit ball of L(H)+, we have that Q∈QPQ=QPQ=QPQ.
Let P∈P be such that Q=QPQ. We have that P=Q+P′ for some projection P′≤Q⊥.
In particular, Q≤P and since the set P is hereditary, we conclude that Q∈P.
∎
Let S⊆L(H) be an operator system. Set
•
\mathop{\rm ap}(\mathcal{S})=\mathop{\rm her}\left(\overline{\mathop{\rm conv}}\left\{P:P\mbox{ an \mathcal{S}-abelian projection}\right\}\right);
•
\mathop{\rm cp}(\mathcal{S})=\mathop{\rm her}\left(\overline{\mathop{\rm conv}}\left\{P:P\mbox{ an \mathcal{S}-clique projection}\right\}\right);
•
\mathop{\rm fp}(\mathcal{S})=\mathop{\rm her}\left(\overline{\mathop{\rm conv}}\left\{P:P\mbox{ an \mathcal{S}-full projection}\right\}\right).
We call ap(S) (resp. cp(S), fp(S)) the abelian
(resp. clique, full) projection convex corner of S. By
Proposition 3.3, these are indeed convex corners while, by
Proposition 2.6, ap(S)=cp(Sc).
Remark 3.4**.**
(i)
For any non-commutative graph S⊆L(H), every rank one projection on H
is S-abelian and S-clique. Thus,
ap(S) and cp(S) always contain the convex corner {T∈L(H)+:Tr(T)≤1}.
On the other hand, fp(S) may be zero, e.g. in the case
where S=span{I,E1,2,E1,3,E2,1,E3,1}⊆M3.
(ii)
By Remark (ii) after Definition 2.2, fp(S)⊆cp(S).
Strict inclusion may occur even in the case where fp(S)={0}, for example,
if S=span{E1,2,E2,1,I2}⊆M2.
**
Let G=(X,E) be a graph on d vertices. Recall that a subset S⊆X
is called independent (resp. a clique) if whenever x,y∈S and x=y, we have that x∼y
(resp. x∼y).
The vertex packing polytope [6] of G is the set
[TABLE]
while the fractional vertex packing polytope [6] of G is the set
[TABLE]
These sets are diagonal convex corners in Md, if
we identify an arbitrary element v=(vi)i=1d of Rd with the matrix
with entries v1,…,vd down the diagonal and zeros elsewhere (see [10]).
We next show that ap(S) is a suitable non-commutative version of vp(G),
while cp(S)♯ and fp(S)♯ are suitable non-commutative versions of fvp(G).
Theorem 3.5**.**
Let G=(X,E) be a graph on d vertices. Then
(i) Δ(ap(SG))=DX∩ap(SG)=vp(G);
(ii) Δ(cp(SG))=DX∩cp(SG)=vp(Gc);
(iii) Δ(fp(SG))=DX∩fp(SG)=vp(Gc).
Proof.
(i) Let S be an independent set in G.
Then exey∗∈SG⊥ for x,y∈S with x=y, and
hence ∑x∈Sexex∗ is an SG-abelian projection in DX.
Since DX∩(ap(SG)) is a convex set, this implies
vp(G)⊆DX∩ap(SG)⊆Δ(ap(SG)).
It remains to show that Δ(ap(SG))⊆vp(G).
Let {v1,…,vm} be an SG-independent set; clearly, m≤d.
Suppose that m=d; then I∈ap(SG) and hence ap(SG)={T∈Md+:∥T∥=1}.
Note that
SG⊆span{vivi∗:i∈[m]}.
In particular, exex∗∈span{vivi∗:i∈[m]} for every x∈X,
and this easily implies that {vi}i=1m={ζxex}x∈X, for some
unimodular constants ζx∈C, x∈X. It follows that G is the empty graph and hence
vp(G)={A∈Dd+:∥A∥≤1}.
It is now clear that Δ(ap(SG))⊆vp(G).
Suppose that m<d and set P=∑i=1mvivi∗.
Write
vi=∑x∈Xλx(i)ex and ax(i)=λx(i)2, i∈[m], x∈X.
Let i=j; then
vivj∗=∑x,yλx(i)λy(j)exey∗∈SG⊥.
Thus,
[TABLE]
Now
[TABLE]
and so
[TABLE]
Note that ∑x∈Xax(i)=⟨vi,vi⟩=1, i=1,…,m.
Since Δ(P)≤I, we have ∑i=1max(i)≤1, x∈X.
For each x∈X, let
rx=1−∑i=1max(i); thus, rx≥0.
Set
[TABLE]
and let M=(mi,x)i,x; thus, M∈Md.
Observe that the matrix M is doubly stochastic. Indeed,
if 1≤i≤m then ∑x∈Xmi,x=∑x∈Xax(i)=1.
On the other hand,
d−∑x∈Xrx=∑i=1m∑x∈Xax(i)=m and hence, if
m+1≤i≤d we have ∑x∈Xmi,x=∑x∈Xd−mrx=1.
Finally, if x∈X then ∑i=1dmi,x=∑i=1dax(i)+rx=1.
By the Birkhoff-von Neumann theorem,
there exist l∈N, γk>0
and permutation matrices P(k)=(pi,x(k))i,x∈Md, k∈[l],
such that ∑k=1lγk=1 and
Suppose that i,j∈[m] and x,y∈X are such that
(i,x)=(j,y) and pi,x(k)=pj,y(k)=1.
Since P(k) is a permutation matrix, i=j and x=y.
By (11),
ax(i)=0 and ay(j)=0; by (8), x and y are (distinct and) non-adjacent vertices in G.
Thus, each Qk is a projection in vp(G) and (12) implies that
Δ(P)∈vp(G).
It follows that Δ(T)∈vp(G) whenever T∈conv{P:P\mboxisSG\mbox−abelian}.
Since vp(G) is closed, Δ(T)∈vp(G) whenever
T∈conv{P:P\mboxisSG\mbox−abelian};
since vp(G) is hereditary, Δ(T)∈vp(G) whenever T∈ap(SG),
and the proof of (i) is complete.
(ii)-(iii)
Let K be an independent set in Gc, that is, a clique in G.
Then exey∗∈SG for all x,y∈K and so
∑x∈Kexex∗ is an SG-full projection.
Together with Remark 3.4, this implies
[TABLE]
and
[TABLE]
It remains to show that Δ(cp(SG))⊆vp(Gc).
Let {v1,…,vm} be an SG-clique.
Suppose that m=d.
Since SG⊥⊆span{vivi∗:i∈[m]}, we have that
SG⊥ is a commutative family of operators.
This easily implies that G is the complete graph; thus,
cp(SG)={T∈Md:0≤T≤I},
vp(Gc)={T∈Dd:0≤T≤I},
and Δ(cp(SG))=vp(Gc).
Assume that m<d and let
P=∑i=1mvivi∗ be the corresponding SG-clique projection.
Writing vi=∑x∈Xλx(i)ex,
similarly to the proof of (i), we see that
if i=j and λx(i)λy(j)=0 then
x≃y in G.
Following the proof of (i) we now obtain
that Δ(P)∈vp(Gc), and consequently that
Δ(cp(SG))⊆vp(Gc), completing the proof.
∎
Lemma 3.6**.**
Let A be a diagonal convex corner, and B be a convex corner, in Md, such that
[TABLE]
Then
A♭=Dd∩B♯=Δ(B♯).
Proof.
If (13) holds then A⊆B and so B♯⊆A♯.
Thus, Dd∩B♯⊆Dd∩A♯=A♭.
For the reverse inclusion, let T∈A♭ and N∈B.
By (13), Δ(N)∈A.
Hence
[TABLE]
and so
T∈B♯∩Dd.
Thus, A♭⊆Dd∩B♯.
Trivially, Dd∩B♯⊆Δ(B♯).
Fix M∈Δ(B♯) and N∈B, and let R∈B♯ be such that
M=Δ(R).
By (13), Δ(N)∈B and hence
[TABLE]
giving M∈B♯∩Dd.
Thus Δ(B♯)⊆Dd∩B♯ and the proof is complete.
∎
Corollary 3.7**.**
Let G=(X,E) be a graph on d vertices. Then
(i) Δ(ap(SG)♯)=DX∩ap(SG)♯=vp(G)♭;
(ii) Δ(cp(SG)♯)=DX∩cp(SG)♯=fvp(G);
(iii) Δ(fp(SG)♯)=DX∩fp(SG)♯=fvp(G).
Proof.
Immediate from Lemma 3.6, Theorem 3.5 and the fact that fvp(G)=vp(Gc)♭.
∎
3.2. Non-commutative graph parameters
In this subsection, we introduce various parameters of non-commutative graphs
and point out their relation with classical graph parameters.
If A⊆Md is a bounded set, let
[TABLE]
Remark 3.8**.**
If P⊆Md is a bounded set and
A=her(conv(P)) then
θ(A)=θ(P).
**
Proof.
It is clear that θ(A)=Tr(A) for some A∈conv(P).
Since the trace is affine and continuous,
by Bauer’s Maximum Principle (see [1, 7.69]), A can be chosen to be an extreme point
of conv(P).
By Milman’s Theorem, A∈P; thus θ(A)=θ(P).
∎
Let H be a d-dimensional Hilbert space and S⊆L(H) be an operator system.
We set
ωf(S)=θ(ap(S)♯) – the
fractional clique number of S;
(v)
κ(S)=θ(cp(S)♯) – the
complementary fractional clique number of S;
(vi)
φ(S)=θ(fp(S)♯) – the
complementary fractional full number of S;
(vii)
χ(S)=min{k∈N:\mboxthereexistS\mbox−abelianprojectionsP1,…,Pk\mboxwith∑l=1kPl=I}
– the chromatic number of S [17].
It follows from Remark 3.8 that the parameters α, ω and ω~
take non-negative integer values. In fact, by Remark 2.7,
α(S) (resp. ω(S)) coincides with the maximum size of an
S-independent set (resp. an S-clique).
A subspace J⊆L(H) will be called an operator anti-system if
there exists an operator system S such that J=S⊥.
(Note that such subspaces were called trace-free non-commutative graphs in [19].)
Let J⊆L(H) be an operator anti-system. Recall [12] that a
strong independent set for J is an orthonormal set {v1,…,vm} of vectors in H
such that vivj∗⊥J for all i,j=1,…,m.
It is clear that a subset {v1,…,vm} is a strong independent set for J if and only if
the projection onto its span is J⊥-full.
The strong chromatic numberχ^(J) of an operator anti-system J [12]
is defined to be the smallest positive integer k for which there exists an orthonormal basis of H
that can be partitioned into k strong independent sets.
We now recall some classical graph parameters. Let G=(X,E) be a graph on d vertices.
(i)
The independence numberα(G) of G is the size of a maximal independent set in G;
(ii)
The clique numberω(G) of G is the size of a maximal clique of G;
(iii)
The chromatic numberχ(G) of G is the smallest number of
independent sets in G with union X;
(iv)
The fractional clique numberωf(G) of G is given by
[TABLE]
**Remark. ** Let S⊆Md be an operator system.
By Proposition 3.3 (i),
[TABLE]
Thus, the fractional clique number ωf(G) of a graph G is given
analogously to ωf(SG), but restricting the matrices A in (15)
to be diagonal, and the projections P to arise from independent sets of G.
In fact, we have the following result, which is a direct consequence of Theorem 3.5 and Corollary 3.7.
Note that part (i) was noted in [5]; we include it here for completeness.
Corollary 3.9**.**
Let G=(X,E) be a graph on d vertices. Then
(i) α(G)=α(SG);
(ii) ω(G)=ω(SG)=ω~(SG);
(iii) ωf(G)=ωf(SG);
(iv) ωf(Gc)=κ(SG)=φ(SG).
Remark 3.10**.**
Let G be a graph. It was shown in [17] that χ(G)=χ(SG),
and in [12] that
χ^(SG⊥)=χ(Gc).
We complement these statements by the following proposition.
**
Let
Sn=span{eiej∗,Id:i=j}⊆Mn.
(Note that Sn=SEnc, where En is the empty graph on n vertices.)
In [13] it was shown that α(S2)=1 while, in [12, Examples 4, 22] – that
χ(Sn)=χ^(Sn⊥)=n.
Here we extend these results by considering tensor products of operator systems of this type
and identifying the values of some of the parameters introduced earlier.
For n1,n2,…,nm∈N, let
[TABLE]
Lemma 3.11**.**
Let u,v∈Cn1n2…nm be orthogonal vectors.
(i) If uv∗∈Sn1,…,nm⊥ then uv∗=0;
(ii) If uu∗,uv∗∈Sn1,…,nm then uv∗=0.
Proof.
(i)
Suppose that uv∗∈Sn1,…,nm⊥.
Let m=1 and write
u=(ui)i=1n1 and v=(vi)i=1n1. We have that
uivˉj=0 whenever i=j and
∑i=1n1uivˉi=0.
These conditions easily imply that u=0 or v=0.
Proceeding by induction, suppose that the statement holds for some m.
Note that
[TABLE]
Thus,
Sn1,…,nm+1⊥ consists of all block matrices of the form
[TABLE]
where
[TABLE]
and
[TABLE]
Write
u=u1⋮un1 and v=v1⋮vn1,
where ui,vi∈Cn2…nm+1, i∈[n1].
We have uv∗=(uivj∗)i,j=1n1 with uivj∗∈Mn2…nm+1.
Assume that ui=0 for some i∈[n1].
By (16) and the induction assumption, vj=0 whenever j=i.
Now, by (17) and the induction assumption, vi=0; thus, v=0.
(ii)
Suppose that u is a unit vector such that uu∗,uv∗∈Sn1,…,nm.
Write
[TABLE]
We will show that
[TABLE]
and v=0.
Letting m=1 and writing
u=(ui)i=1n1 and v=(vi)i=1n1, we have that
∣ui∣2=n11 for all i∈[n1].
In addition,
uivˉi=ujvˉj for all i,j. Since ⟨u,v⟩=0,
we have that uivˉi=0 for all i∈[n1]. This shows that vi=0 for all i∈[n1], that is, v=0.
Proceeding by induction, suppose that the statement holds for some m
and write
u=u1⋮un1 and v=v1⋮vn1,
where ui,vi∈Cn2…nm+1, i∈[n1].
We have that uiui∗=ujuj∗ for all i,j∈[n1].
Thus, ∥ui∥2=n11 for all i∈[n1].
The inductive assumption implies that ∣ui1,…,im+1∣2=n1…nm+11 for all
(i1,…,im+1)∈[n1]×⋯[nm+1].
On the other hand,
uivi∗=ujvj∗ for all i,j∈[n1] and hence ⟨ui,vi⟩=0 for all i∈[n1].
By the inductive assumption, vi=0 for all i∈[n1].
∎
ω(Sn1,n2,…,nm)≥min{n1,…,nm}* and ω(Sn1)=n1.*
Proof.
(i) and (ii) are immediate from Lemma 3.11, (iii) is immediate from (i), and (v) from (ii).
(iv) By (i), I∈ap(Sn1,n2,…,nm)♯, and hence ωf(Sn1,n2,…,nm)=n1…nm.
The fact that χ(Sn1,n2,…,nm)=n1…nm follows from Corollary 3.14
and the fact that the value of χ(S) does not exceed the dimension on which S acts.
(vi)
Set d=n1…nm for brevity.
By (ii), I∈fp(Sn1,…,nm)♯; thus, φ(Sn1,…,nm)≥d.
Fix a primitive d-th root of unity ζ.
For k∈[d], let uk=d1(ζki)i=1d; thus, uk is a unit vector in Cd.
By the proof of Lemma 3.11, ukuk∗∈fp(Sn1,…,nm).
Thus,
[TABLE]
It follows that if T∈fp(Sn1,…,nm)♯ then Tr(T)≤d, and hence
φ(Sn1,…,nm)=d.
(vii) Assume, without loss of generality, that n1=min{n1,…,nm}
and let fk:[n1]→[nk] be an injective map, k=2,…,m.
Then {ei1,f2(i1),…,fm(i1):i1∈[n1]} is an Sn1,…,nm-clique
and hence ω(Sn1,n2,…,nm)≥n1.
On the other hand, ω(Sn1)≤n1 and the proof is complete.
∎
3.3. Inclusions between convex corners
We now prove our first sandwich theorem and list some of its consequences.
Theorem 3.13**.**
Let S be a non-commutative graph. Then
[TABLE]
Proof.
The second inclusion follows from Remark 3.4 (ii).
Let {ξi}i=1k (resp.
{ηp}p=1m) be an S-independent set
(resp. an S-clique) and P (resp. Q) be the projection onto its span.
It suffices to show that Tr(PQ)≤1.
We have that
[TABLE]
Thus,
[TABLE]
For each i∈[k], let
[TABLE]
and
[TABLE]
We distinguish three cases:
Case 1.α=∅.
Then β(i)=[m] for every i∈[k]. It follows that Q⊥P and hence Tr(PQ)=0≤1.
Case 2.∣α∣=1, say α={i0}.
Then
[TABLE]
because the family {ηp}p=1m is orthonormal and ∥ξi0∥=1.
Case 3.∣α∣>1.
By (19), for every pair (i,j)∈[k]×[k] with i=j, we have
[TABLE]
and hence
[TABLE]
Suppose that
∣β(i)c×β(j)c∣>1 for some i,j with i=j.
Then there are p,p′ such that p=p′ and
[TABLE]
contradicting (20).
Thus, ∣β(i)c×β(j)c∣≤1 for all pairs (i,j) with i=j.
It follows that ∣β(i)c∣=1 for every i∈α.
Write β(i)c={pi}, i∈α.
Then (pi,pj)∈β(i)c×β(j)c for all i,j∈α with i=j.
In view of (20), pi=pj for all i,j∈α.
Let p0 be the common value of pi, i∈α;
then
[TABLE]
because the family {ξi}i=1k is orthonormal and ∥ηp0∥=1.
∎
Corollary 3.14**.**
Let S be a non-commutative graph. Then
[TABLE]
[TABLE]
and
[TABLE]
Proof.
By Proposition 2.6, ap(S)=cp(Sc) and hence α(S)=ω(Sc)
and ωf(Sc)=κ(S).
By Theorem 3.13, α(S)≤κ(S)≤φ(S).
Suppose that there exist S-full projections P1,…,Pk with I=∑i=1kPi.
If T∈fp(S)♯ then
[TABLE]
thus, φ(S)≤χ^(S⊥).
By Remark 3.4 (ii), ω~(S)≤ω(S).
By Theorem 3.13, cp(S)⊆cp(S)♯♯⊆ap(S)♯ and
hence ω(S)≤ωf(S).
An argument, similar to one in the previous paragraph shows that ωf(S)≤χ(S).
Replacing S with Sc, we get κ(S)≤χ(Sc).
By Proposition 2.6 and
Remark (ii) after Definition 2.2, χ(Sc)≤χ^(S⊥). Replacing S with Sc
and using Remark 2.5 we have
χ(S)≤χ^(S∩{I}⊥), and the proof is complete.
∎
**Remarks. (i) **
By Corollary 3.9 and Remark 3.10,
the first and the last inequalities in (21),
the second and the third inequalities in (22),
and the first inequality in (23)
can be strict even in the case where S is a graph operator system.
Let T be a non-commutative graph for which fp(T)={0} (see
Remark 3.4 (i)).
We have that φ(T)=χ^(T⊥)=∞ and ω~(T)=0;
thus, by Remark 3.4 (i), the middle inequality in (21), the first inequality in (22)
and the second inequality in (23) can be strict.
In addition, χ^(Tc∩{I}⊥)=∞,
and hence the last inequality in (22) can be strict.
**(ii) **
The inclusions in Theorem 3.13 can be strict.
For the first inclusion this follows for instance from
the fact that α(S) can be strictly smaller than κ(S)
(see (i)).
For the second inclusion, this follows from Remark 3.4 and the fact that, for a convex corner
A, we have the identity A=A♯♯.
This non-trivial fact will be established in subsequent work [2].
**(iii) **
In view of the proof of Corollary 3.14,
the parameter φ(S) can be thought of as a fractional version of the
strong chromatic number χ^(S⊥).
4. The Lovász corner
Let G=(X,E) be a graph on d vertices.
A family (ax)x∈X of unit vectors in
a finite dimensional complex Hilbert space is called an orthogonal labelling (o.l.) of G
if
[TABLE]
Let
[TABLE]
viewed as a subset of DX.
Let
thab(G)=P0(G)♭,
and
[TABLE]
be the Lovász number of G [14].
We note that Lovász worked with real Hilbert spaces, but inspection of the proofs shows that the
results in [6, 10, 14] are true for complex Hilbert spaces as well.
In its strong form [6] (see also [10]), the Sandwich Theorem states that
[TABLE]
The aim of this section is to introduce a non-commutative version of thab(G)
and to establish a chain of inclusions, analogous to (24).
4.1. Definition and consistency
Let H and K be finite dimensional Hilbert spaces
and
Φ:L(H)→L(K) be a completely positive map.
Then there exist operators
Ap:H→K, p=1,…,m, such that
[TABLE]
the form (25) is called a Kraus representation of Φ, and Ap, p=1,…,m
– Kraus operators of the representation.
The operator system
[TABLE]
is called the non-commutative graph ofΦ, and can be shown to be independent of
the Kraus representation (25) of Φ (see [5] and [20, Corollary 2.23]).
We let
Φ∗:L(K)→L(H) be the adjoint of Φ, that is, the linear map given by
[TABLE]
The completely positive map Φ is called a quantum channel (q.c.)
if it is trace preserving; this is equivalent to the condition
∑p=1mAp∗Ap=I.
Let S⊆L(H) be an operator system and
[TABLE]
Set
[TABLE]
and
[TABLE]
Lemma 4.1**.**
Let H be a finite dimensional Hilbert space and S⊆L(H) be an operator system.
Then th(S) is a convex corner and
th(S)=P(S)♯.
Proof.
For T∈L(H)+, we have
[TABLE]
Thus, th(S)=P(S)♯ and hence, by Remark 3.2 (i),
th(S) is a convex corner.
∎
For a non-commutative graph S, we set
[TABLE]
and call θ(S) the Lovász number of S.
Let G=(X,E) be a graph.
We will call a family (Px)x∈X of projections acting on a finite dimensional Hilbert space
a projective orthogonal labelling (p.o.l.) of G if
[TABLE]
Let
[TABLE]
Note that, if (ax)x∈X is an orthogonal labelling of G then
the family (axax∗)x∈X is a projective orthogonal labelling of G.
It follows that
[TABLE]
Lemma 4.2**.**
Let G=(X,E) be a graph on d vertices. Then P(Gc)⊆P(G)♭.
Proof.
Let (Px)x∈X (resp. (Qx)x∈X) be a projective orthogonal labelling of G (resp. Gc)
acting on a Hilbert space K1 (resp. K2),
and let ρ (resp. σ) be a state on K1 (resp. K2).
We have that
[TABLE]
It follows that the operator ∑x∈XPx⊗Qx is a contraction, and thus
[TABLE]
∎
Lemma 4.3**.**
Let G=(X,E) be a graph on d vertices.
Then P0(G)⊆P(SG).
Proof.
Let (ax)x∈X⊆Ck be an orthogonal labelling of G
and Φ:Md→Mk be the quantum channel defined by
[TABLE]
If x≃y then (exax∗)(ayey∗)=⟨ay,ax⟩exey∗=0,
and hence SΦ⊆SG.
Given a unit vector c∈Ck, we have that
Φ∗(cc∗)=(∣⟨ax,c⟩∣2)x∈X, and the proof is complete.
∎
Lemma 4.4**.**
Let G=(X,E) be a graph on d vertices. Then
[TABLE]
Proof.
Let Φ:Md→Mk be a quantum channel with SΦ⊆SG.
Write
[TABLE]
where Ap:Cd→Ck are linear operators such that
Ap∗Aq∈SG for all p,q∈[m] and ∑p=1mAp∗Ap=I.
Let ap,x=Apex, p∈[m], x∈X. Note that ap,x∈Ck and set
Zx=∑p=1map,xap,x∗; thus, Zx∈Mk, x∈X.
Let Px be the projection onto the span of {ap,x:p∈[m]} and observe that
[TABLE]
Suppose that x,y∈X, x≃y. Then
[TABLE]
It follows that the family (Px)x∈X is a projective orthogonal labelling of G.
On the other hand,
Clearly, DX∩th(SG)⊆Δ(th(SG)).
Let T∈th(SG) and suppose that Φ:Md→Mk is a quantum channel with SΦ⊆SG.
Let
[TABLE]
be a Kraus representation of Φ.
Set Ap,x=Ap(exex∗), and note that, since SG is a DX-bimodule, we have that
Ap,x∗Aq,y=(exex∗)Ap∗Aq(eyey∗)∈SG.
In addition,
[TABLE]
Thus, the map
Ψ:Md→Mk, given by
[TABLE]
is a quantum channel with SΨ⊆SG.
Hence
[TABLE]
It follows that Δ(T)∈th(SG).
By Lemmas 4.1 and 4.3, th(SG)⊆P0(G)♯.
It now follows that Δ(T)∈thab(G).
The proof is complete.
∎
In view of Theorem 4.5, th(S) can be thought of as a
non-commutative version of thab(G).
Corollary 4.6**.**
Let G=(X,E) be a graph on d vertices. Then θ(G)=θ(SG).
Proof.
By Theorem 4.5, thab(G)⊆th(SG), and hence θ(G)≤θ(SG).
Since th(SG) is compact, there exists T∈th(SG) such that Tr(T)=θ(SG).
By Theorem 4.5, Δ(T)∈thab(G), and hence
Tr(T)=Tr(Δ(T))≤θ(G).
∎
4.2. The second sandwich theorem
We now establish a chain of inclusions generalising the Sandwich Theorem (24) to the non-commutative setting.
Theorem 4.7**.**
Let H be a finite dimensional Hilbert space and S⊆L(H) be an operator system.
Then
[TABLE]
Proof.
Let P be an S-abelian projection, and suppose that
{ξi}i=1k is an S-independent set of (unit) vectors that spans PH.
Fix Φ∈C(S) with Kraus operators A1,…,Am, and let i,j∈[k] with i=j.
Then
[TABLE]
since SΦ⊆S while ξiξj∗∈S⊥.
Since Φ(ξiξi∗) and Φ(ξjξj∗) are positive operators, we conclude that there exist
mutually orthogonal projections Q1,…,Qk such that
Φ(ξiξi∗)=QiΦ(ξiξi∗)Qi for each i∈[k].
Since ∥ξi∥=1 and Φ is trace preserving,
Tr(Φ(ξiξi∗))=1;
in particular, ∥Φ(ξiξi∗)∥≤1.
It now follows that
[TABLE]
that is, P∈th(S).
Since ap(S) is generated, as a convex corner, by the S-abelian projections,
using Lemma 4.1, we conclude that ap(S)⊆th(S).
Now suppose that Q is an S-full projection. Let
(ηj)j=1k be an orthonormal basis for the range of Q; then ηiηj∗∈S for all i,j∈[k].
Let η be a unit vector with η=Qη and
Φ:L(H)→L(H) be the quantum channel given by
[TABLE]
For any T∈L(H) we have
[TABLE]
thus,
[TABLE]
Note that
[TABLE]
and that
[TABLE]
It follows that SΦ⊆S.
Now (32) implies that Q∈P(S).
Since Q is an arbitrary S-full projection, by Lemma 4.1,
th(S)=P(S)♯⊆fp(S)♯.
∎
The classical Lovász Sandwich Theorem
states that the chain of inequalities
[TABLE]
holds for a graph G (see [10]).
The next corollary, which is immediate from Theorem 4.7, provides a non-commutative version.
Corollary 4.8**.**
If S is a non-commutative graph then
α(S)≤θ(S)≤φ(S).
5. Another quantisation of θ(G)
Let Φ:Md→Mk be a quantum channel.
The one-shot classical Shannon capacity of Φ was introduced in [5]
as the maximal number of pure states that can be transmitted via Φ so that their
images are perfectly distinguishable. As was pointed out in [5],
it coincides with the independence number α(S) of the non-commutative confusability graph S
of Φ.
The classical Shannon capacity [5] of Φ
is, on the other hand, defined by setting
[TABLE]
where S⊗n=ntimesS⊗⋯⊗S.
We note that it depends only on S; thus, one may talk without ambiguity about the
Shannon capacity of a non-commutative graph S and denote it by c0(S).
In the case S is the operator system of a graph G, we have that c0(S) coincides with the
Shannon capacity c0(G) of G.
The Lovász number of G is in this case an upper bound of c0(G).
We do not know if the inequality c0(S)≤θ(S) holds for general non-commutative graphs S.
However, θ(G)
has several equivalent expressions [6, 10, 14]; in particular,
we have that
[TABLE]
We will now consider a non-commutative version of the latter expression and show that it leads to a parameter
that bounds from above the Shannon capacity of the corresponding non-commutative graph.
Namely, for a non-commutative graph S, we set
[TABLE]
Theorem 5.1**.**
Let H be a finite dimensional Hilbert space and S⊆L(H) be an operator system.
Then
(ii) θ(S)−1=inf{sup{∥Φ(ρ)∥:Φ∈C(S)}:ρ\mboxastateonH}.
Proof.
(i)
For an operator A∈L(H)+, write λmin(A) for the smallest eigenvalue of A.
Using the von Neumann minimax theorem, we have
[TABLE]
[TABLE]
(ii)
Since the operator Tr(T)1T is a state for each non-zero T∈Md+, we have
[TABLE]
∎
**Remark. **
By compactness, the infimum appearing in part (i) of Theorem 5.1 is a minimum;
it is not however clear whether the supremum in this expression is attained.
Recall [13] that the quantum subcomplexityβ(S) of a non-commutative graph
S⊆L(H) is defined by letting
[TABLE]
Theorem 5.2**.**
Let H be a Hilbert space with dim(H)=d and S⊆L(H) be an operator system.
Then
[TABLE]
Proof.
The first inequality follows from Theorem 5.1 (ii) by taking ρ=d1Id.
The second inequality is immediate from Theorem 5.1.
If Φ:L(H)→Mk is a quantum
channel in C(S) then, letting σ=k1Ik we have
Φ∗(σ)−1=k. Thus, θ^(S)≤β(S).
The last inequality, as pointed out in [13], follows by noting that the identity channel
belongs to C(S).
∎
Let (ax)x∈X⊆Ck be an orthogonal labelling of G
and Φ:Md→Mk be the quantum channel defined in the proof of Lemma 4.3.
Let c be a unit vector in Ck such that ⟨ax,c⟩=0 for all x∈X.
We have that
[TABLE]
Taking the infimum over all orthogonal representations of G and unit vectors c
and using (33),
we conclude that θ^(SG)≤θ(G). Together with (34), this completes the proof.
∎
**Remark. ** It follows from Proposition 5.3 that the second inequality
in Theorem 5.2 can be strict; indeed, β(S) is an integer while θ(S) can
be fractional (for example, if C5 is the 5-cycle then θ(C5)=5).
Proposition 5.4**.**
Let H1 and H2 be finite dimensional Hilbert spaces and
S1⊆L(H1) and S2⊆L(H2) be operator systems. Then
θ^(S1⊗S2)≤θ^(S1)θ^(S2).
Proof.
Let ϵ>0, let σi∈L(Hi)+ be an operator with Tr(σi)≤1
and Φi∗(σi) invertible,
and let
Φi:L(Hi)→L(Ki) be a quantum channel with SΦi⊆Si, i=1,2,
such that
[TABLE]
Then Φ1⊗Φ2:L(H1⊗H2)→L(K1⊗K2) is a quantum channel
with SΦ1⊗Φ2⊆S1⊗S2.
In addition,
(Φ1⊗Φ2)∗(σ1⊗σ2)=Φ1∗(σ1)⊗Φ2∗(σ2)
is invertible and
[TABLE]
The conclusion follows by letting ϵ→0.
∎
Corollary 4.8, Theorem 5.2 and Proposition 5.4 have the following immediate consequence.
In view of Theorem 5.2, it improves the bound on the Shannon capacity by
the parameter β, established in [13].
Corollary 5.5**.**
Let S be a non-commutative graph. Then c0(S)≤θ^(S).
Let ϑ(S) be the quantisation
of the Lovász number defined in [5], namely
[TABLE]
and ϑ~(S)=supm∈Nϑ(Mm(S)) be its complete version.
It was shown in [5] that ϑ~(S) is a bound on the Shannon capacity of S.
The next examples imply that θ^ can be genuinely better than ϑ~.
**Examples. (i) **
Let d∈N. Suppose that Φ is a quantum channel with (non-zero) Kraus operators A1,…,Am
and confusability graph CId. Then Ai∗Ai=λiI for some λi>0, and hence
the operator Vi:=λi1Ai is an isometry.
Thus,
[TABLE]
Therefore, Id∈th(CId) and hence θ(CId)≥d. Together with Theorem 5.2
this shows that θ(CId)=θ^(CId)=d.
Note, on the other hand, that ϑ~(CId)=d2 [5, (7)],
showing that the ratio ϑ~(S)θ^(S),
where S is a non-commutative graph, can be arbitrarily small.
(ii)
Let Sd=span{Id,eiej∗:i=j}⊆Md.
It was shown in [13, Theorem V.2] that
β(Sd⊗Sd2)≤d2; on the other hand, [5] easily implies
that ϑ(Sd⊗Sd2)≥d3 (see [13, Theorem V.2]).
It follows that the ratio
ϑ(S)θ^(S),
where S is a non-commutative graph, can also be arbitrarily small.
6. Further properties
In this section, we study the dependence of some of the parameters we introduced on the
operator system. Our main focus is on θ,
but we also point out some auxiliary results for the other parameters.
6.1. Monotonicity
Let S⊆L(H) and T⊆L(K) be non-commutative graphs.
A homomorphism from S into T [19]
is a quantum channel Γ:L(H)→L(K) that has a Kraus representation
Γ(S)=∑i=1mAiSAi∗, such that
[TABLE]
If there exists a homomorphism from S into T, we write S→T.
It was shown in [19] that if G and H are graphs then SG→SH if and only if
there exists a graph homomorphism from G to H.
Proposition 6.1**.**
Let S and T be non-commutative graphs. If S→T then θ(S)≤θ(T)
and θ^(S)≤θ^(T).
Proof.
Let Γ be a homomorphism from S into T.
If Ψ∈C(T) then Ψ∘Γ∈C(S).
Letting S∈th(S) be such that Tr(S)=θ(S) we have
that Γ(S)∈L(K)+ and
(Ψ∘Γ)(S)≤I, showing that Γ(S)∈th(T).
Thus, θ(T)≥Tr(Γ(S))=θ(S).
In addition,
Let H be a finite dimensional Hilbert space,
S⊆L(H) be an operator system and m∈N.
Then Mm(S)→S and S→Mm(S).
Proof.
For i∈[m],
let Vi:H→Hm be the operator given by Vi(ξ)=(ξk)k=1m, where ξi=ξ and
ξk=0 if k=i.
Then ∑i=1mViVi∗=I, and hence the map Γ:L(Hm)→L(H) given by
Γ(S)=∑i=1mVi∗SVi, is a quantum channel.
Clearly, ViSVj∗⊆Mm(S) for all i,j∈[m]; in other words, Mm(S)→S.
Let Λ:L(H)→L(Hm) be the channel given by Λ(S)=m1S⊗Im;
thus, Λ(S)=m1∑i=1mViSVi∗, S∈L(H).
Moreover, Vi∗Mm(S)Vj=S for all i,j∈[m].
It follows that S→Mm(S).
∎
Corollary 6.3**.**
Let H be a finite dimensional Hilbert space and S⊆L(H) be an operator system.
Then θ(S)=θ(Mm(S)) and θ^(S)=θ^(Mm(S)) for every m∈N.
Remark.
Let H (resp. K) be a finite dimensional Hilbert space and S⊆L(H)
(resp. T⊆L(K)) be an operator system. If S→T then α(S)≤α(T).
Indeed, suppose that Γ:L(H)→L(K) is a homomorphism from S to T
with Kraus operators A1,…,Am, and that {ξi}i=1k⊆H is an S-independent set.
Let V be the column isometry (Ai)i=1m; then {Vξi}i=1k is an Mm(T)-independent set,
and hence α(S)≤α(Mm(T)). The claim follows from the fact that
α(Mm(T))=α(T) [13, Remark IV.6 (i)].
By Corollary 3.14,
if Sc→Tc then ω(S)≤ω(T), and
ω(Mm(T))=ω(T) for any T.
6.2. Equivalent expressions and grading
Let H be a d-dimensional Hilbert space and S be a non-commutative graph acting on H.
We call a linear map Φ:Md→Mk a subchannel if it is completely positive and trace decreasing.
Note that Φ is a subchannel if and only if its dual Φ∗:Mk→Md
is subunital in the sense that Φ∗(I)≤I, if and only if the Kraus operators A1…,Am:Cd→Ck
satisfy the relation ∑i=1mAi∗Ai≤I.
Set
[TABLE]
Let
[TABLE]
[TABLE]
and θsub(S)=max{Tr(A):A∈thsub(S)}.
Set also
[TABLE]
Proposition 6.4**.**
Let H be a finite dimensional Hilbert space and S⊆L(H) be an operator system.
Then thsub(S)=th(S),
θsub(S)=θ(S) and θ^sub(S)=θ^(S).
Proof.
Set d=dim(H).
Since C(S)⊆Csub(S), we have that thsub(S)⊆th(S).
Suppose that T∈th(S) and let Φ∈Csub(S).
Write Φ(S)=∑i=1mAiSAi∗, S∈Md, where the operators A1,…,Am∈L(H,K)
for some (finite dimensional) Hilbert space K satisfy ∑i=1mAi∗Ai≤I.
Set B0=(I−∑i=1mAi∗Ai)1/2.
Let K~ be a Hilbert space containing K, V:H→K~ be an isometry with
range orthogonal to K, and A0=VB0. Considering the operators Ai as acting from H into K~,
we have that
[TABLE]
In addition, Ai∗A0=Ai∗VB0=0 and A0∗Ai=B0V∗Ai=0 for all i=1,…,m, while
A0∗A0=B02∈S. Thus, the mapping Φ~:L(H)→L(K~), given by
Φ~(S)=∑i=0mAiSAi∗, is a quantum channel.
By assumption,
Φ(T)≤Φ~(T)≤I, showing that T∈thsub(S).
It follows that
thsub(S)=th(S) and
θsub(S)=θ(S).
Since C(S)⊆Csub(S), we have that θ^sub(S)≤θ^(S).
For a completely positive trace decreasing map Φ, let
Fix ϵ>0 and choose Φ∈Csub(S) such that
η(Φ)>θ^sub(S)−1−ϵ.
Let A1,…,Am be Kraus operators for Φ.
Fix positive real numbers p1,…,pl such that ∑r=1lpr=1 and
pr≤η(Φ), r=1,…,l, and
a state ρ on H.
Let K1,…,Kl be Hilbert spaces of dimension d,
K~=⊕r=1lKr and Vr:H→Kr be a unitary operator, r=1,…,l.
With B0 as in the first paragraph, write Br=VrB0, r=1,…,l, and let
Φ^:L(H)→L(K⊕K~) be given by
[TABLE]
where the operators Ai and Br are considered as acting from H into K⊕K~.
A straightforward verification shows that Φ^ is a quantum channel in C(S).
Moreover,
[TABLE]
for every state σ, and hence
η(Φ^)=η(Φ).
After letting ϵ→0, we conclude that θ^(S)≤θ^sub(S).
∎
Let θk(S)=θ(thk(S))
and θ^k(S) be defined as θ^(S)
but using quantum channels in Ck(S).
It is clear that Ck(S)⊆Ck+1(S), thk+1(S)⊆thk(S),
[TABLE]
and that
θ^(S)=limk→∞θ^k(S).
Since th(S)=∩k∈Nthk(S), we have that
th(S)=limk∈Nthk(S) and, by Lemma 6.8,
θ(S)=limk→∞θk(S).
We will shortly see that the sequence (θk(S))k∈N stabilises.
Lemma 6.5**.**
Let S be a non-commutative graph in Md,
k∈N, and Φ∈Ck(S).
Assume that Φ=tΦ1+(1−t)Φ2, where Φ1,Φ2:Md→Mk are quantum channels and t∈(0,1).
Then Φ1,Φ2∈Ck(S).
Proof.
Suppose that {Ai}i=1m and {Bp}p=1l are families of Kraus operators for Φ1 and Φ2,
respectively. Then {tAi,1−tBp:i∈[m],p∈[l]} is a family of Kraus operators for Φ.
Since SΦ is independent of the Kraus representation of Φ, we have, in particular, that
Ai∗Aj∈S and Bp∗Bq∈S for all i,j∈[m] and all p,q∈[l].
Thus, SΦ1⊆S and SΦ2⊆S.
∎
If k∈N, let Ek be the set of all extreme points in the convex set
of all quantum channels from Md to Mk.
Proposition 6.6**.**
Let S be a non-commutative graph in Md and k≥d2.
Then
[TABLE]
Thus, th(S)=thd2(S) and θ(S)=θd2(S).
Proof.
Suppose that T∈Md+ has the property that
[TABLE]
If Φ∈Ck(S), write Φ=∑p=1ltpΦp as a convex combination,
where Φp∈Ek, p=1,…,l.
By Lemma 6.5, Φp∈Ck(S). By assumption (36),
[TABLE]
Thus,
[TABLE]
Fix T∈thd2(S), and
suppose that Ψ∈Ck(S)∩Ek. By [3, Theorem 5],
there exists a Kraus representation
Ψ(S)=∑i=1mAiSAi∗, S∈Md, such that the set {Ai∗Aj:i,j∈[m]} is linearly independent.
Thus, m≤d. Let P be the projection in Mk onto the span of the ranges of the operators
A1,…,Am; then rank(P)≤d2, and therefore Ψ can be considered as a quantum channel
into Md2. By assumption, Ψ(T)≤I.
By (37), T∈thk(S).
Thus, thd2(S)⊆thk(S), and since
thk(S)⊆thd2(S) trivially, we conclude that
thd2(S)=thk(S). Thus,
th(S)=thd2(S) and θ(S)=θd2(S).
∎
(i)⇒(ii)
Suppose that θ^(S)>1.
Let δ∈(0,d1) be such that θ^(S)−1<1−δ.
By Theorem 5.1, for each Φ∈C(S) there exists a state
τ with ∥Φ(τ)∥<1−δ.
Note that σ:=d−11(I−τ) is a state and
d1Id=d1τ+(1−d1)σ.
Thus,
[TABLE]
Setting T=d−δ1Id, we have that T≥0 and ∥Φ(T)∥≤1 for all Φ∈C(S);
thus, T∈th(S)
and so θ(S)≥Tr(T)=d−δd>1.
(iii)⇒(i) is straightforward.
(i)⇒(iii)
Set k=d2.
Following the proof of Theorem 5.1 (ii), one can see that
[TABLE]
For each quantum channel Φ:Md→Mk and each state ρ, we have
∥Φ(ρ)∥−1≥1; thus,
(39) and Proposition 6.6 imply that
[TABLE]
By Lemma 6.10 below, there exists Φ∈Ck(S) such that
Φ(d1Id)=1.
It follows that there exists a unit vector u∈Cd such that Φ(d1Id)=uu∗.
The fact that the state uu∗ is pure now implies that Φ(σ)=uu∗ for every pure state, and hence for every
state σ, on Cd.
Thus, Φ(T)=∑i=1d(uei∗)T(eiu∗), T∈Md, and so
SΦ=Md; since Φ∈Ck(S),
we have that S=Md.
∎
**Remark **
Let S⊆Md be a non-commutative graph.
In view of Theorem 4.7 and
the fact that cp(S)♯⊆fp(S)♯, it is natural to ask if
the stronger inclusion th(S)⊆cp(S)♯ holds.
The answer to this question is negative; indeed,
{e1,e2} is a clique for S2 and thus I∈cp(S2). Hence
cp(S2)♯⊆{T∈M2+:Tr(T)≤1}.
On the other hand, e1e1∗ and e2e2∗ are S2-abelian projections and so,
by Theorem 3.13, cp(S2)♯={T∈M2+:Tr(T)≤1}.
It follows that κ(S2)=1.
On the other hand, by Proposition 6.7, θ(S2)>1.
It follows that th(S2)⊆cp(S2)♯.
6.3. Continuity
In this subsection, we establish some continuity properties and exhibit a bound on the output system
required for computing θ(S).
We use a classical concept of convergence due to Kuratowski.
Let X be a topological space. For a sequence (Fn)n∈N of subsets of X,
set
[TABLE]
and
[TABLE]
We say that the sequence (Fn)n∈N converges to the subset F⊆X,
and write F=limn→∞Fn,
if F=liminfn∈NFn=limsupn∈NFn.
Lemma 6.8**.**
Let (An)n∈N be a sequence of convex corners in Md such that ∪n∈NAn is bounded.
Assume that limn→∞An=A for some convex corner A⊆Md.
Then θ(An)→n→∞θ(A).
Proof.
Suppose that a subsequence (θ(Anm))m∈N converges to δ.
Let Am∈Anm be such that θ(Anm)=Tr(Am), m∈N.
We may assume, without loss of generality, that Am→m→∞A for some A∈Md.
By assumption, A∈A and hence θ(A)≥Tr(A)=δ.
Thus, limsupn∈Nθ(An)≤θ(A).
Let A∈A be such that Tr(A)=θ(A). By assumption,
there exists a sequence (An)n∈N such that A=limn→∞An.
Then θ(A)=limn→∞Tr(An)≤liminfn∈Nθ(An).
∎
Lemma 6.9**.**
Let A,An⊆Mn+, n∈N, be non-empty sets
such that ∪n∈NAn is bounded
and limsupn∈NAn⊆A.
Then A♯⊆liminfn∈NAn♯.
Proof.
For a bounded set B⊆Md+ and an operator T∈Md+, let
[TABLE]
Suppose that T∈A♯ and that T∈liminfn∈NAn♯.
After passing to a subsequence if necessary, we assume that there exists δ>0 such that
[TABLE]
We consider two cases.
Case 1.liminfn∈NδAn(T)≤1.
In this case, there exists an increasing sequence (np)p∈N⊆N such that
δAnp(T)<1+p1, p∈N.
Thus, δAnp(p+1pT)<1,
and hence p+1pT∈Anp♯, p∈N.
Since p+1pT→p→∞T, this contradicts (40).
Case 2.liminfn∈NδAn(T)>1.
In this case, there exists c>1 and n0∈N such that δAn(T)≥c for all n≥n0.
Thus, there exists An∈An such that ⟨T,An⟩≥2c+1, n≥n0.
Let A be a cluster point of the sequence (An)n≥n0.
By assumption, A∈A. Thus
[TABLE]
a contradiction.
∎
In the sequel, we consider the operator systems in Md as closed subsets of the topological space Md.
Lemma 6.10**.**
Let H be a finite dimensional Hilbert space,
S,Sn⊆L(H), n∈N, be operator systems and k∈N.
If limsupn∈NSn⊆S then limsupn∈NCk(Sn)⊆Ck(S).
Proof.
Without loss of generality, assume that
(Φn)n∈N⊆Ck(Sn) is a sequence, and Φ is a quantum channel,
such that
Φn→k→∞Φ.
Let Φ~n (resp. Φ~) be the complementary channel
[9] of Φn
(resp. Φ), n∈N, acting from L(H) into L(K~), for some Hilbert space K~
that can be chosen to be independent of n.
By [5], SΦ=ran(Φ~∗) and SΦn=ran(Φ~n∗), n∈N.
By [11],
[TABLE]
Thus, if R∈L(K~) then Φ~∗(R)=limn→∞Φ~n∗(R).
Since Φn∈Ck(Sn) for each n,
we have Φ~∗(R)∈S and therefore SΦ⊆S.
∎
Theorem 6.11**.**
Let k∈N and
S,Sn, n∈N, be non-commutative graphs in Md such that
S=limn→∞Sn.
Then th(S)=limn→∞th(Sn) and θ(Sn)→n→∞θ(S).
Proof.
Set k=d2.
Suppose that Tn∈thk(Sn), n∈N, and Tn→T for some T∈Md.
Let Φ∈Ck(S)∩Ek, and write Φ(S)=∑i=1mAiSAi∗ in a Kraus representation
with m≤d.
Let V=(A1,…,Am) be the corresponding row operator and set
B=V∗V=(Ai∗Aj)i,j=1m; then B∈Mm(S)+.
Note that (Vt)∗Vt=I.
Since Mm(S)⊆liminfn→∞Mm(Sn), there exist Bn∈Mm(Sn), n∈N,
such that Bn→n→∞B. We can moreover assume that Bn=Bn∗, n∈N.
Since B≥0, there exists a sequence (δn)n∈N⊆R+ with δn→n→∞0
such that Bn+δnI≥0, n∈N. Thus, we may assume that Bn≥0, n∈N.
Since dm≤k, there exists an isometry W:Cmd→Ck
such that V=WB1/2. Let Vn=WBn1/2, n∈N.
Then Vn∗Vn=Bn, n∈N, and Vn→n→∞V.
Since ∥Vt∥=1, we have that ∥Vnt∥→n→∞1.
Letting V~n=∥Vnt∥1Vn, n∈N, we thus have
that V~n→n→∞V,
(V~nt)∗V~nt≤I
and V~n∗V~n∈Mm(Sn), n∈N.
Write V~n=(An,1,…,An,m), where An,i:Cd→Ck, i=1,…,m.
Then the map Φn:Md→Mk, given by Φn(S)=∑i=1mAn,iSAn,i∗, S∈Md,
is a subchannel.
Moreover, ∥Φn−Φ∥cb→n→∞0.
By Proposition 6.4, Φn(Tn)≤I, n∈N. After passing to a limit, we conclude that
Φ(T)≤I, and hence T∈thk(S). We thus showed that
limsupn∈Nthk(Sn)⊆thk(S).
Suppose that Φn∈Ck(Sn) and σn∈Mk+, Tr(σn)≤1,
are such that Φn∗(σn)→n→∞A, for some A∈Md+.
Assume, without loss of generality, that
Φn→n→∞Φ and σn→n→∞σ.
By Lemma 6.10, Φ∈Ck(S).
Moreover, Φn∗(σn)→Φ∗(σ).
We thus showed that limsupn∈NPk(Sn)⊆Pk(S).
Lemma 6.9 and identity (35)
imply that thk(S)⊆liminfn∈Nthk(Sn).
Proposition 6.6 now implies that th(S)=limn→∞th(Sn).
It is now straightforward to show that θ(Sn)→n→∞θ(S).
∎
In the next corollary, we denote by Md0 the real vector space of all
non-zero hermitian matrices of trace zero.
Corollary 6.12**.**
The function
Λ→θ({Λ}⊥) from Md0 into R+ is continuous
and has range [δ1,δ2] for some 1<δ1<δ2≤d.
Proof.
We can clearly assume that the operators Λ have norm one.
Suppose that Λn→n→∞Λ, and consider ΛnΛn∗ and ΛΛ∗
as projections on Md.
Then ΛnΛn∗→n→∞ΛΛ∗; thus,
(ΛnΛn∗)⊥→n→∞(ΛΛ∗)⊥ and, by
[8], limn→∞{Λn}⊥={Λ}⊥
as subspaces of Md.
By Theorem 6.11, θ({Λn}⊥)→n→∞θ({Λ}⊥).
Since the domain of the function under consideration is connected and compact, its range is a closed interval
[δ1,δ2].
The fact that δ1>1 follows from Proposition 6.7.
∎
7. Open questions
In this section, we discuss some open questions, arising naturally from the previous results.
Question 7.1**.**
Does the equality θ(S)=θ^(S) hold true for every non-commutative graph S?
This is perhaps the most fundamental open question about the parameters we have introduced.
In view of Theorem 5.1, such an equality amounts to
exchanging the order of the infimum and the supremum in its statement.
We note that standard minimax theorems
do not apply in any obvious way.
The question is related to the possibility to lift the duality theory implicit in Lovász original work [14]
and developed in [6] (see also [7] and [10]),
leading to several equivalent characterisations in the commutative case.
In particular, it would be of
interest to study weighted versions of the parameters θ and θ^,
and establish a non-commutative version of the classical result from [14]
stating that, for any graph G, we have thab(G)♭=thab(Gc).
Such an approach will be based on examining the following question:
Question 7.2**.**
Does the parameter θ^ arise from a convex corner?
We were able to establish the continuity of θ by exhibiting a bound on the
size of the output system.
We are not aware if a similar approach is possible for the case of θ^:
Question 7.3**.**
Given d∈N, does there exist k∈N (depending on d),
such that, for every non-commutative graph S⊆Md,
the parameter θ^(S) can be computed using channels Φ:Md→Mk?
Question 7.4**.**
Is the map S⟶θ^(S) continuous?
While we established the submultiplicativity of θ^, leading to a bound on the
Shannon capacity of a non-commutative graph, we do not know whether similar bounds can be
formulated in terms of other parameters. In particular, we ask:
Question 7.5**.**
Is the parameter φ submultiplicative?
In Proposition 3.12 we identified most of the introduced parameters in the case of
the non-commutative graph Sn. However, we do not know the value of the Lovász numbers for this
operator system (even in the case where n=2):
Question 7.6**.**
What are the values of θ(Sn) and θ^(Sn)?
Finally, it would be of interest to find a more precise version of Corollary 6.12:
Question 7.7**.**
What are the precise values of δ1 and δ2 in Corollary 6.12?
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