
In networks, the Markov clustering (MCL) algorithm is one of the most efficient approaches in detecting clustered structures. The MCL algorithm takes as input a stochastic matrix, which depends on the adjacency matrix of the graph network under consideration. Quantum clustering algorithms are proven to be superefficient over the classical ones. Motivated by the idea of a potential clustering algorithm based on quantum Markov chains, we prove a clustering property for quantum Markov chains (QMCs) on Cayley trees associated with open quantum random walks (OQRW).
Citation: Luigi Accardi, Amenallah Andolsi, Farrukh Mukhamedov, Mohamed Rhaima, Abdessatar Souissi. Clustering quantum Markov chains on trees associated with open quantum random walks[J]. AIMS Mathematics, 2023, 8(10): 23003-23015. doi: 10.3934/math.20231170
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In networks, the Markov clustering (MCL) algorithm is one of the most efficient approaches in detecting clustered structures. The MCL algorithm takes as input a stochastic matrix, which depends on the adjacency matrix of the graph network under consideration. Quantum clustering algorithms are proven to be superefficient over the classical ones. Motivated by the idea of a potential clustering algorithm based on quantum Markov chains, we prove a clustering property for quantum Markov chains (QMCs) on Cayley trees associated with open quantum random walks (OQRW).
Markov chains and random walks find widespread applications in several areas. Markov chains-based algorithms play crucial in unsupervised Machine learning and networks, such as the Markov clustering algorithm [41,42], which is proven to be one of the most powerful approaches for detecting clustered structures. Quantum Markov Chains (QMCs) [1] have been introduced long ago [2,6] and found important applications in physics [7,14,15,16,40]. QMCs on trees [4,5,22,23,30,36,38] have been studied in connection with statistical mechanical models [3,24,27,36]. In particular, quantum phase transitions were investigated for Pauli type models [19,20,21]. A variety of aspects of quantum Markov states on trees have been investigated [26,27,28,29].
Over the last few decades, quantum random walks [8] have been the subject of a significant amount of research due to their utility in a variety of domains, such as quantum information and networks [33,34]. In [8], OQRWs have been introduced in the unitary case. In [9], Attal et al. extended this approach and also considered OQRWs on graphs. The inclusion of OQRWs in the general frame of QMCs has been established in [12,18] and then extended to QMCs on trees [31,32]. Stopping rules and recurrence for QMCs were introduced in [37]. In addition, in recent works [31,32], QMCs on trees have been associated with OQRWs. This led to further applications, such as quantum phase transitions and recurrence of QMCs on trees [11,37].
In quantum statistical mechanics, the clustering property for a state indicates the absence of long-range order [17,35]. In [30], we investigate the clustering property for a class of QMCs on the Comb graph. In [20,39], it was shown that a QMC associated with an XY-Ising model on the Cayley tree satisfy the clustering property. In the present paper, we show that the QMC associated with the disordered phase of a quantum system based on OQRW does not satisfy the clustering property. To the best of our knowledge, non-clustering QMCs on tree have not been addressed previously in the literature. Further relevant problems can be investigated, such as the types of von Neumann algebras associated with the QMCs under consideration, such as [25]. The obtained results can have important and promising implications in Markov models in data science.
The paper is organized as follows: Section 2 is devoted to some preliminaries on trees. In Section 3, we introduce QMCs associated with OQRW on trees. Section 4 is dedicated to the main result of the paper.
Let Γk+=(V,E) be semi-infinite Cayley tree of order k. Denote o∈V the root of the tree. Two vertices x and y are called nearest-neighbors if there exists an edge joining them, we denote x∼y. Let u and v be two different vertices, we call edge-path with length n∈N joining u to v a finite list of vertices u1,u2,⋯,un such that u∼u1∼u2∼⋯∼un=v. It is well known that, a tree can be characterized through the property that any two distinct vertices are joined by means of a unique edge-path. The distance on the tree d(u,v) between u and v is the length of the unique edge-path joining them. The hierarchical structure of Γk+ allows to define the levels
Wm:={u∈V:d(u,o)=m}. |
On the levels, a coordinate structure is assigned as follows. For m∈N and x∈Wm is identified to a n-uplet x≡(ℓ1,…,ℓm), where ℓj∈{1,…,k}, 1≤j≤m. The coordinate structure is illustrated in Figure 1 in the case of the Cayley tree of order two. In the above notations, we write
Wm={(ℓ1,ℓ2,⋯,ℓm);ℓj=1,2,⋯,k}. |
Define
Λn=n⋃j=0Wj;Λ[m,n]=n⋃j=mWj. |
For ℓ1,ℓ2.…,ℓn∈{1,2,…,k} and u=(ℓ1,ℓ2,…,ℓn)∈Wn there exists a unique path joining it to the root o given as follows:
o∼u1=(ℓ1)∼u2=(ℓ1,ℓ2)∼⋯∼un−1=(ℓ1,ℓ2,⋯,ℓn−1)∼u. |
Let u′=(ℓ′1,ℓ′2,…,ℓ′m)∈Wm, the shift αu on the tree is defined as
αu(u′)=(ℓ1,ℓ2,⋯,ℓn,ℓ′1,ℓ′2,⋯ℓ′m)∈Wn+m. |
In particular, αu(o)=u. For each u∈Wn, we define its set of direct successors by
S(u)={v∈Wn+1:u∼v}={(u,1),(u,2),⋯,(u,k)}. | (2.1) |
Put
Vu={v=u∘u′:u′∈V}. | (2.2) |
Recall that a graph isomorphism [13] is an edge-preserving bijection from a graph G1=(V1,E1) onto a graph G2=(V2,E2) such that:
- α is a bijective map from V1 onto V2;
- for every x,y∈V1 one has x∼y if and only if α(x)∼α(y).
The sub-tree Γk+,u=(Vu,Eu), whose vertex set is Vu, is isomorphic to Γk+. For each n∈N, we define
Wu; n={v∈Vu:d(u,v)=n}=αu(Wn),Λu; n=n⋃j=0Wu; j=αu(Λn). |
The map αu is a graph isomorphism from Γk+=(V,E) onto Γk+,u=(Vu,Eu), we denote its inverse isomorphism by α−1u.
To each vertex x∈V, we assign the C∗–algebra of observables Ax=A with unit 1Ix. For any finite region V′⊂V, we consider the local algebra AV′=⨂x∈V′Ax. In particular, for each n, one defines AΛn=⨂u∈ΛnAu. One has the embedding
AΛn≡AΛn⊗1IWn+1⊂AΛn+1, |
where for each finite region V′⊂V, one has 1IV′=⨂u∈V′1Iu. We obtain the following local algebra associated with the increasing set {AΛn}n≥0
AV,loc=↑⋃n∈NAΛn, |
and its C∗-closure [10] is the following quasi-local algebra
AV=¯AV,locC∗. |
For a∈A and x∈V, we denote a(x)=a⊗1IV∖{x}, where a appears at the component Au of the infinite tensor product AV. Notice that, the graph isomorphism αu defines a ∗−isomorphism ˜αu from AV into AVu satisfying
˜αu(⨂x∈Λnax)=⨂y∈Λu;na(y)α−1u(y), | (2.3) |
where for each y∈Λu;n by α−1u(y) we mean the element x∈Λn satisfying αu(x)=y.
Let C⊂B be two C∗-algebras. We call transition expectation (TE), any completely positive identity preserving (CP1) from B into C. Let C⊆B⊆A be unitary C∗–algebras. Recall that:
● A quasi-conditional expectation (QCE) is a CP1 linear map E:A→B such that
E(ca)=cE(a),∀a∈A,∀c∈C. |
● A TE is any CP1 linear map between two unitary C∗-algebras.
The set of states on a C∗–algebra A will be denoted by S(A).
For a given TE EWn from AΛ[n,n+1] into AWn, the map
EΛn=idAΛn−1⊗EWn | (2.4) |
is a TE w.r.t. the triplet AΛn−1⊂AΛn⊂AΛn+1. The hierarchical structure of the Cayley tree manifests in the fact that
Wn+1=⨆u∈WnS(u). |
This allows to consider local TE Eu from A{u}∪S(u) into Au. Then the map
En:=⨂u∈WnEu |
defines a TE from AΛ[n,n+1] into AWn.
Definition 2.1. [6] A (backward) QMC on AV is defined to be a triplet (ϕo,(En)n≥0,(hn)n), where
● ϕo∈S(Ao) is an initial state,
● for each n, En is a TE from AΛ[n,n+1] into AWn,
● for each n, hn∈AWn,+ is a positive boundary condition,
such that for each a∈AV the limit
φ(a):=limn→∞ϕ0∘EΛ0∘EΛ1∘⋯∘EΛn(h1/2n+1ah1/2n+1), | (2.5) |
exists in the weak-*-topology and defines a state φ on AV, which will be also referred as QMC.
Definition 2.2. [38] The triplet φ≡(ϕo,(EΛn)n≥0,(hn)n) is called a tree-homogeneous QMC (THQMC) if there exists a TE E:A{o}∪S(o)→Ao such that for each n
EΛn=idAΛn−1]⊗⨂u∈Wnαu∘E∘α−1u | (2.6) |
where idAΛn−1 is the identity map on AΛn−1 and
hn = ⨂u∈Wnαu(h) | (2.7) |
for some boundary condition h∈Ao;+.
In the sequel, for the sake of simplicity we denote a(u):=αu(a) for each a∈A and u∈V.
Theorem 2.1. Let ϕo be a state on Ao and E:AΛ1→Ao a TE. For h∈A+, if
ϕo(h(o))=1, | (2.8) |
E(1I(o)⊗h(1)⊗h(2)⋯⊗h(k))=h(o), | (2.9) |
then (ϕo,E,h) is a THQMC on the algebra AV.
Let H and K be two separable Hilbert spaces. Let B(H) (respectively B(K)) be the algebra of all bounded operators over H (respectively K) with identity 1IH (respectively 1IK). Let {|i⟩:i∈Λ} be an orthonormal basis of K, where Λ is a connected graph. The algebra of observables at a given site u∈V is Au=B(H)⊗B(K)≡B(H⊗K) with identity 1Iu=1IH⊗1IK. In the notations of the previous section, for eacha∈B(H)⊗B(K) we denote αu(a)=a(u)∈Au. For each (i,j)∈Λ2, the quantum transition from the state |j⟩ into the state |i⟩ is implemented by an operator Bij∈B(H) such that
∑i∈ΛBi∗jBij=1IH. | (3.1) |
Consider a density operator ρ∈B(H⊗K), of the form
ρ=∑i∈Λρi⊗|i⟩⟨i|,ρi∈B(H)+∖{0}, |
where B(H)+ is the cone of positive operators over H.
For each u∈V, we set
Mij=Bij⊗|i⟩⟨j|∈B(H)⊗B(K). | (3.2) |
Put
Aij:=1Tr(ρj)1/2ρ1/2j⊗|i⟩⟨j|,withi,j∈Λ, | (3.3) |
Kij:=Mi∗j(u)⊗⨂v∈S(u)Aij(v)∈A{u}∪S(u), | (3.4) |
where b(x)=αx(b) for every b∈B(H⊗K) and x∈V.
Let
E(a)=Tru](∑(i,j)∈Λ2Kija∑(i′,j′)∈Λ2Ki′∗j′), |
where Tru] is the partial trace defined by linear extension of
Tru](au⊗a(u,1)⊗⋯⊗a(u,k))=Tr(a(u,1))⋯Tr(a(u,k))⋅au. |
For a=au⊗au,1⊗⋯⊗au,k one shows that
E(a)=∑(i,j,j′)∈Λ3Mi∗j(u)auMij′(u)(k∏ℓ=1φj,j′(au,ℓ)), | (3.5) |
where
φjj′(b):=1Tr(ρj)1/2Tr(ρj′)1/2Tr(ρ1/2jρ1/2j′⊗|j′⟩⟨j|b),∀b∈B(H)⊗B(K). | (3.6) |
Theorem 3.1. With the above notations, if ωo∈Ao;+ is an initial state and h∈Ao;+ is a boundary condition such that
Tr(ωoho)=1, | (3.7) |
∑i,j,j′∈ΛMi∗jMij′k∏ℓ=1φj,j′(h(u,ℓ))=hu. | (3.8) |
Then the triplet (ωo,(Eu)u∈V,(hu)u∈V) defines a quantum Markov chain φ on the algebra AV. Moreover, for each a=⨂u∈Λnau∈AΛn one has
φ(a)=∑j,j′∈ΛTr(ωoMjj′(ao))∏u∈Λ[1,n]ψj,j′(au)∏v∈Λn+1φj,j′(h(v)), | (3.9) |
where Eu is given by (3.5), the functional φjj is given by (3.6), and
Mjj′(⋅)=∑i∈ΛMi∗j′⋅Mij, | (3.10) |
ψj,j′(b)=1Tr(ρj)1/2Tr(ρj′)1/2∑i∈ΛTr(Bij′ρ1/2j′ρ1/2jBij∗⊗|i⟩⟨i|b). | (3.11) |
Proof. See [31].
The forward Markov operator associated with the TE (3.5) is defined from Au into itself as follows
Px;f(ax):=Ex(ax⊗1Ix,1⊗⋯⊗1Ix,k) | (3.12) |
and for each ℓ∈{1,2,⋯,k}, the ℓth backward Markov operator is defined on Ax,ℓ into Ax by
Px,ℓ;b(ax,ℓ):=Ex(1Ix⊗1Ix,1⊗1Ix,ℓ−1⊗ax,ℓ⊗1Ix,ℓ+1⊗⋯⊗1Ix,k). | (3.13) |
In previous works [31,38], it was shown that the boundary condition h=1I corresponds to the QMC associated with the disordered phase of the system. One finds
Px;f(ax)=∑i,j,j′Mi∗jaxMij′(φjj′(1I))k=∑i,jMi∗jaxMij | (3.14) |
and
Px,ℓ;b(ax,ℓ)=∑i,j,j′Mi∗jMij′(φjj′(1I))k−1φjj′(ax,ℓ)(3.1)=∑j1IH⊗|j⟩⟨j|φjj(ax,ℓ). | (3.15) |
In this section, we restrict ourselves to the case h=1I. Indeed, thanks to (3.1) the boundary condition h=1I is solution of (3.8). The corresponding QMC evaluated on localized elements a=⨂x∈Λmax is given by
φ(a)=∑j∈ΛTr(ωoMjj(ao))∏u∈Λ[1,n]ψjj(au). | (4.1) |
Definition 4.1. A state ψ on AV is said to be clustering (mixing) if
limu∈V;|u|→∞φ(aαu(b))=φ(a)φ(b),∀(a,b)∈AV, | (4.2) |
where |u|=d(u,o).
Theorem 4.1. Let φ≡(ϕo,E,h=1I) then
(i) Let m≥0 be an integer, for every a,b∈AΛm,
limu;|u|→∞φ(aαu(b))=∑j∈Λϕo(Mjj(a0))∏x∈Λ[1,m]ψjj(ax)φjj(ˆb), | (4.3) |
where
ˆb:=Eo(bo⊗EW1(bW1⊗⋯EWm(bWm⊗1IWm+1))). | (4.4) |
(ii) The QMC φ given by (3.9) is clustering if and only if |Λ|=1.
Proof. (i) Let u=(ℓ1,ℓ2,⋯,ℓn). Let a,b∈AV;loc. Without lose of generality, we can assume that a=⨂x∈Λmax,b=⨂x∈Λmbx∈AΛm. For F⊂Λm, we denote bF=⨂x∈Fbx, one can see that
αu(bWj)=⨂v∈Wu;jb(v)α−1u(v)=:⨂v∈Wu;jb′v=b′Wu;j. |
We find
αu(ˆb)=Eu(b(u)o⊗EWu;1(b(Wu;1)W1⊗⋯EWu;m(b(Wu;m)Wm⊗1IWm+1))). |
On the other hand, we have
EWn+m(b′Wu;m⊗1IWn+m∖Wu;m⊗1IWn+m)=⨂v∈Wu;mEv(b′v⊗1IS(v))⊗⨂w∈Wn+m∖Wu;mEw(1Iw∨S(w))(3.12)=⨂v∈Wu;mPv;f(b′v)⊗1IWn+m∖Wu;m. |
Then
EWn+m−1(b′Wu;m⊗1IWn+m−1∖Wu;m−1⊗EWn+m(b′Wu;m⊗1IWn+m∖Wu;m⊗1IWn+m))=EWn+m−1(b′Wu;m⊗1IWn+m−1∖Wu;m−1⊗⨂v∈Wu;mPv;f(b′v)⊗1IWn+m∖Wu;m)=⨂w∈Wu;m−1Ew(b′w⊗⨂v∈S(w)Pv;f(b′v))⊗1IWn+m−1∖Wu;m−1, |
iterating the above procedure, we get
EWn(b′u⊗EWn+1(b′Wu;1⊗⋯EWn+m(b′Wu;m⊗1IWn+m)⋯))(4.4)=ˆbu⊗1IWn∖{u}. |
Denote uj=(ℓ1,ℓ2,…,ℓj) for each j∈{1,2,⋯,n}. For cj∈Auj, we have
EWj−1(1IWj−1⊗cuj⊗1IWj∖{uj})(3.13)=Puj−1;ℓ;b(cuj)⊗1IWj−1∖{uj−1}. |
It follows that
φ(aαu(b))=ϕo(E0(ao⊗EW1(aW1⊗⋯EWm(aWm⊗EWm+1(1IWm+1⊗⋯EWn−1(1IWm−1⊗EWn(b′u⊗EWn+1(b′Wu;1⊗⋯EWn+m(b′Wu;m⊗1IWn+m)⋯)))⋯))⋯)))=ϕo(E0(ao⊗EW1(aW1⊗⋯EWm(aWm⊗EWm+1(1IWm+1⊗⋯EWn−1(1IWm−1⊗ˆbu⊗1IWn∖{u})⋯))⋯)))=ϕo(E0(ao⊗EW1(aW1⊗⋯EWm(aWm⊗EWm+1(1IWm+1⊗⋯EWn−2(1IWm−2⊗Pun−1;ℓn;b(ˆbu)⊗1IWn−1∖{un−1})⋯))⋯)))⋮=ϕo(E0(ao⊗EW1(aW1⊗⋯EWm(aWm⊗˜Punum+1;b(ˆbu)⊗1IWm+1∖{um+1})⋯))), |
where
˜Punum+1;b(c)=Pum+1;ℓm+2;bPum+2;ℓm+3;b⋯Pun−1;ℓn;b(c),c∈Au. |
For c∈Aui, we have
Pui;ℓi+1;bPui+1;ℓi+2;b(c)(3.15)=Pui;ℓi+1;b(∑j1IH⊗|j⟩⟨j|φjj(c))=∑j′1IH⊗|j′⟩⟨j′|φj′j′(∑j1IH⊗|j⟩⟨j|φjj(c))(3.6)=∑j,j′1IH⊗|j′⟩⟨j′|δj,j′φjj(c)=∑j1IH⊗|j⟩⟨j|φjj(c). |
This means that elements of the form c′=∑j1IH⊗|j⟩⟨j|φjj(ci) are invariant for the all the backward Markov operators Pui;ℓ;b. Then
˜Punum+1;b(ˆbu)=∑j1IH⊗|j⟩⟨j|φjj(ˆbu). |
Therefore, using (3.9) we find (4.3).
(ii) On the other hand, we have
φ(a)φ(b)=φ(a)ϕo(ˆb)=∑j∈Λϕo(Mjj(a0))∏x∈Λ[1,m]ψjj(ax)ϕo(ˆb). |
Fix j∈Λ. For a=(1IH⊗|j⟩⟨j|)(1), we get
φ(aαu(b))=φjj(ˆb);φ(a)=1. |
Therefore, the QMC φ satisfies (4.2) if and only if φjj=ϕo, ∀j∈Λ. If |Λ|>1, then for j≠j′ we have φjj(1IH⊗|j⟩⟨j|)=1≠0=φj′j′(1IH⊗|j⟩⟨j|). If Λ is reduced to a singleton {j0}, the state φ is a product state. It is enough to take ϕ0=φj0j0 to get the clustering property. This finishes the proof.
Remark 4.1. In (4.3), if a=1I we get
limu; |u|→∞φ(αu(b))=∑j∈Λϕo(1I⊗|j⟩⟨j|)φjj(ˆb)=:φ∞(ˆb), | (4.5) |
the limiting state φ∞ on A is equitably distributed between the state φjj with respect to the initial state ϕo.
From Theorem 4.1 the state φ is clustering if and only the OQRW is trivial and the walker occupies a single site Λ={i0}. In this case the QMC φ is a product state.
Example 4.1. Let H=K=C2 with canonical basis (|1⟩,|2⟩) and Λ={1,2}. The algebra of observable is A=M2(C)⊗M2(C)≡M4(C). The transitions of the OQRW are given by
B11=(α00β),B12=(0100),B21=(γ00δ),B22=(1000), |
where α,β,γ,δ∈C such that
|α|2+|γ|2=|β|2+|δ|2=1andαγ≠0. | (4.6) |
Put
ρ1=(1000),ρ2=(0001),σ=(100−1). |
The initial state is the normalized trace given by ϕo=14Tr. One has φjj(b)=Tr(ρj⊗|j⟩⟨j|b) for each j∈Λ.
Let a=b=σ⊗|2⟩⟨2|, from (3.5) we find
Eo(a⊗1I)=∑i,jMi∗jaMij=∑jB2∗jσB2j⊗|j⟩⟨j|=(|γ|200−|δ|2)⊗|1⟩⟨1|+(1000)⊗|2⟩⟨2|. |
Therefore
φ(a)=ϕ0(Eo(a))=14(|β|2+|γ|2). |
Since b∈Ao then from (4.4) we have ˆb=Eo(b⊗1I). It follows that
φ11(ˆb)=|γ|2;φ22(ˆb)=0. |
In addition
M11(a)=∑iMi∗1aMi1=B2 ∗1⊗|1⟩⟨1|aB11⊗|1⟩⟨1|+B1 ∗1⊗|1⟩⟨2|aB11⊗|2⟩⟨1|=(|γ|200−|δ|2)⊗|1⟩⟨1|. |
Then (4.3) implies that
limu;|u|→∞φ(aαu(b))=ϕo(M11(a))φ11(ˆb)=14|γ|2(|γ|2−|δ|2). |
Thus
φ(a)ϕ(b)=116(|β|2+|γ|2)2≠14|γ|2(|γ|2−|δ|2)=φ(aαu(b)). |
Therefore, the state φ does not satisfy the clustering property. Moreover, from (4.5) limiting state is given by
φ∞=122∑j=1φjj≠ϕo. |
If in addition |β|≠|γ|, then for u∈V∖Λ1, we have
φ(b)=14(|β|2+|γ|2)≠φ(αu(b))=φ∞(ˆb)=12|γ|2, |
then the QMC φ is not invariant under the translation τu.
In prior studies, significant characteristics of QMCs on trees, such as phase transition and recurrence, have been investigated. In the present paper, we examine the clustering property of a QMC approach on the Cayley tree associated OQRWs. This analysis reveals an additional ergodic property within the disordered phase of the quantum system under examination. Notably, our research shows promise in relation to the development of data clustering algorithms.
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
This research is funded by the "Researchers Supporting Project number (RSPD2023R683), King Saud University, Riyadh, Saudi Arabia".
The authors have no conflicts of interest to declare.
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