Abstract
Quantum walks on graphs have shown prioritized benefits and applications in wide areas. In some scenarios, however, it may be more natural and accurate to mandate high-order relationships for hypergraphs, due to the density of information stored inherently. Therefore, we can explore the potential of quantum walks on hypergraphs. In this paper, by presenting the one-to-one correspondence between regular uniform hypergraphs and bipartite graphs, we construct a model for quantum walks on bipartite graphs of regular uniform hypergraphs with Szegedy’s quantum walks, which gives rise to a quadratic speed-up. Furthermore, we deliver spectral properties of the transition matrix, given that the cardinalities of the two disjoint sets are different in the bipartite graph. Our model provides the foundation for building quantum algorithms on the strength of quantum walks on hypergraphs, such as quantum walks search, quantized Google’s PageRank, and quantum machine learning.
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Introduction
As a quantum-mechanical analogs of classical random walks, quantum walks have become increasingly popular in recent years, and have played a fundamental and important role in quantum computing. Owing to quantum superpositions and interference effects, quantum walks have been effectively used to simulate quantum phenomena1, and realize universal quantum computation2,3, as well as develop extensively quantum algorithms4. A wide variety of discrete quantum walk models have been successively proposed. The first quantization model of a classical random walk, which is the coined discrete-time model and which is performed on a line, was proposed by Aharonov5 in the early 1990s. Aharonov later studied its generalization for regular graphs in ref.6. Szegedy7 proposed a quantum walks model that quantizes the random walks, and its evolution operator is driven by two reflection operators on a bipartite graph. Moreover, in discrete models, the most-studied topology on which quantum walks are performed and their properties studied are a restricted family of graphs, including line8,9, cycle10,11, hypercube12,13, and general graphs14,15,16,17. Indeed, most of the existing quantum walk algorithms are superior to their classical counterparts at executing certain computational tasks, e.g., element distinctness18,19, triangle finding20,21, verifying matrix products22, searching for a marked element16,23, quantized Google’s PageRank24 and graph isomorphism25,26. In addition to above scientific documents, there are many good introductions and reviews written by Kempe27, Kendon28,29, Venegas-Andraca30, and Wang31 relevant to deepening into the physical, mathematical and algorithmic properties of quantum walks.
In mass scenarios, a graph-based representation is incomplete, since graph edges can only represent pairwise relations between nodes. However, hypergraphs are a natural extension of graphs that allow modeling of higher-order relations in data. Because the mode of representation is even nearer to the human visual grouping system, hypergraphs are more available and effective than graphs for solving many problems in several applications. Owing to Zhou’s random walks on hypergraphs for studying spectral clustering and semi-supervised ranking32, hypergraphs have made recent headlines in computer vision33,34, information retrieval35,36,37, and categorical data clustering38. Many interesting and promising findings were covered in random walks on hypergraphs, and quantum walks provide a method to explore all possible paths in a parallel way, due to constructive quantum interference along the paths. Therefore, paying attention to quantum walks on hypergraphs is a natural choice.
Inspired by these latter developments, we focus on discrete-time quantum walks on regular uniform hypergraphs. In ref.39, Konno defined a two-partition quantum walk and the quantum walk on hypergraph, also he showed that the quantum walk on hypergraph is also a two partition quantum walk. In this paper, by analyzing the mathematical formalism of hypergraphs and three existing discrete-time quantum walks40 (coined quantum walks, Szegedy’s quantum walks, and staggered quantum walks), we find that discrete-time quantum walks on regular uniform hypergraphs can be transformed into Szegedy’s quantum walks on bipartite graphs that are used to model the original hypergraphs. Furthermore, the mapping is one to one. That is, we can study Szegedy’s quantum walks on bipartite graphs instead of the corresponding quantum walks on regular uniform hypergraphs. In ref.7 Szegedy proved that his schema brings about a quadratic speed-up. Hence, we construct a model for quantum walks on bipartite graphs of regular uniform hypergraphs with Szegedy’s quantum walks. In the model, the evolution operator of an extended Szegedy’s walks depends directly on the transition probability matrix of the Markov chain associated with the hypergraphs.
In more detail, we first introduce the classical random walks on hypergraphs, in order to get the vertex-edge transition matrix and the edge-vertex transition matrix. We then define a bipartite graph that is used to model the original hypergraph. Lastly, we construct quantum operators on the bipartite graph using extended Szegedy’s quantum walks, which is the quantum analogue of a classical Markov chain. In this work, we deal with the case that the cardinalities of the two disjoint sets can be different from each other in the bipartite graph. In addition, we deliver a slightly different version of the spectral properties of the transition matrix, which is the essence of the quantum walks. As a result, our work generalizes quantum walks on regular uniform hypergraphs by extending the classical Markov chain, due to Szegedy’s quantum walks.
The paper is organized as follows. There three subsection in Sec. Results. In Sec. Results: Random walks on hypergraphs, we briefly introduce random walks on hypergraphs needed to present the quantum version of it. In Sec. Results: Quantum walks on hypergraphs, we construct a method for quantizing Markov chain to create discrete-time quantum walks on regular uniform hypergraphs. In Sec. Results: Spectral analysis of quantum walks on hypergraphs, we analyze the eigen-decomposition of the operator. Sec. Discussion is devoted to conclusions.
Results
Random walks on hypergraphs
Let HG = (V, E) denote a hypergraph, where V is the vertex set of the hypergraph and \(E\subset {2}^{V}\)\{{}} is the set of hyperedges. Let V = {v1, v2, …, v n } and E = {e1, e2, …, e m }. where n = |V| is used to denote the number of vertices in the hypergraph and m = |E| the number of hyperedges. Given a hypergraph, define its incidence matrix \(H\in {R}^{n\times m}\) as follows:
Then, the vertex and hyperedge degrees are defined as follows:
where E(v) is the set of hyperedges incident to v. A hypergraph is d – regular if all its vertices have the same degree. Also, a hypergraph is k – uniform if all its hyperedges have the same cardinality. In this paper, we will restrict our reach to quantum walks on d – regular and k – uniform hypergraphs from now on, denoting them as HGk,d.
A random walk on a hypergraph HG = (V, E) is a Markov chain on the state space V with its transition matrix P. The particle can move from vertex v i to vertex v j if there is a hyperedge containing both vertices. According to ref.32, a random walk on a hypergraph is seen as a two-step process. First, the particle chooses a hyperedge e incident with the current vertex v. Then, the particle picks a destination vertex u within the chosen hyperedge satisfying the following: v, u ∈ e. Therefore, the probability of moving from vertex v i to v j is:
or, more accurately, the equation can be written as
Let P VE denote the vertex-edge transition matrix
and P EV the edge-vertex transition matrix
with transition probability
where D v and D e are the diagonal matrices of the degrees of the vertices and edges, respectively. Naturally, we can indicate P in matrix form, as
Quantum walks on hypergraphs
In this section, we design quantum walks on regular uniform hypergraphs by means of Szegedy’s quantum walks. We first convert the hypergraph into its associated bipartite graph, which can be used to model the hypergraph. We then define quantum operators on the bipartite graph using Szegedy’s quantum walks, which are a quantization of random walks.
Derving Bipartite graphs from hypergraphs
Proposition 1
Any regular uniform hypergraph HGk,d can be represented usefully by a bipartite graph BGn,m: the vertices V and the edges E of the hypergraph are the partitions of BG, and (v i , e j ) are connected with an edge if and only if vertex v i is contained in edge e j in HG.
Proof.
Hypergraph can be described by binary edge-node incidence matrix H with elements (1). To the incidence matrix of a regular uniform hypergraph HGk,d corresponds a bipartite incidence graph \(B(H)=G(V\cup E,{E}_{B})\) which is defined as follows. The vertices V and the edges E of the hypergraph are the partitions of BG, and \(({v}_{i},{e}_{j})\in {E}_{B}\) iff h ij = 1. It is evident that B is bipartite, and the biadjacency matrix describing B(H) is the following (n + m) × (n + m) matrix:
Under this correspondence, the biadjacency matrices of bipartite graphs are exactly the incidence matrices of the corresponding hypergraphs.
A similar reinterpretation of adjacency matrices may be used to show a one-to-one correspondence between regular uniform hypergraphs and bipartite graphs. That is, discrete-time quantum walks on regular uniform hypergraphs can be transformed into quantum walks on bipartite graphs that are used to model the original hypergraphs. The transformation process is outlined in detail below. If there is a hyperedge e k containing both vertices v i and v j in the original hypergraph HG = (V, E), convert it into two edges (v i , e k ) and (e k , v j ) in the bipartite graph.
As a concrete example, we consider a 3 – uniform and 2 – regular hypergraph with the vertexes set V = {v1, v2, v3, v4, v5, v6} and the set of hyperedges E = {e1, e2, e3, e4}. Then, a bipartite graph BG6,4 with partite sets V = {v1, v2, v3, v4, v5, v6} and E = {e1, e2, e3, e4} can represent the hypergraph HG3,2, which is depicted in Fig. 1.
Theorem 1
Let HG = (V, E) be a hypergraph, and we have
Proof.
Let \(B(H)=G(V\cup E,{E}_{B})\) be the incidence graph of HG = (V, E). We sum the degrees in the part E and in the part V in B(H). Since the sums of the degrees in these two parts are equal, we obtain the result.
In particular, if the hypergraph is d – regular and k – uniform, we obtain nd = mk.
Szegedy quantum walks on the bipartite graphs
Since we have transformed the hypergraph HGk,d into its bipartite graph BGn,m, we now describe Szegedy quantum walks that take place on the obtained bipartite graph BGn,m by extending the class of possible Markov chains. The quantum walks on the hypergraph HG start by considering an associated Hilbert space that is a linear subspace of the vector \({H}^{{n}^{2}m}={H}_{v}^{n}\otimes {H}_{e}^{m}\otimes {H}_{v}^{n}\), where n = |V|, m = |E|. The computational basis of \({H}^{{n}^{2}m}\) is \(\{|{v}_{i},e,{v}_{j}\rangle :e\in E,{v}_{i},{v}_{j}\in V,{v}_{i},{v}_{j}\in e\}\). In addition, quantum walks on the bipartite graph BGn,m with biadjacent matrix (12) have an associated Hilbert space \({H}_{A}={H}_{v}^{n}\otimes {H}_{e}^{m}\) and \({H}_{B}={H}_{e}^{m}\otimes {H}_{v}^{n}\).
To identify quantum analogues of Markov chains - that is, the classical random walks with probability matrices (7) and (8) with entries of (9) and (10) - we define the vertex-edge transition operators: \(A:{H}^{n}\to {H}^{nd}\) and edge-vertex transition operators: \(B:{H}^{m}\to {H}^{mk}\) as follows:
where
The transition operators are defined on the Hilbert space H A and H B separately, where the computational basis of Hnd is \(\{|v,e\rangle :v\in V,e\in E\}\) and the computational basis of Hmk is \(\{|e,v\rangle :e\in E,v\in V\}\). The states \(|{\alpha }_{v}\rangle \) and \(|{\beta }_{e}\rangle \) as superpositions that start from vertex v to hyperedge e and from hyperedge e to vertex v, respectively. Obviously, the dimensions of A and B are nd × n and mk × m, respectively. Note that nd = mk from theorem 1. Using (16) and (17) along with (9) and (10), we obtain the following properties:
as well as
One can easily verify that \(|{\alpha }_{v}\rangle \) and \(|{\beta }_{e}\rangle \) are unit vectors due to the stochasticity of P VE and P EV . Distinctly, these equations imply that the action of A preserves the norm of the vectors. The same is true regarding B.
We now immediately define the projectors Π A and Π B as follows:
Using Eqs (22) and (23), it is easy to see that Π A projects onto subspace H A spanned by \(\{|{\alpha }_{v}\rangle :v\in V\}\), and Π B projects onto subspace H B spanned by \(\{|{\beta }_{e}\rangle :e\in E\}\). After obtaining the projectors, we can define the associated reflection operators, which are
where I nd = I mk is the identity operator.
Note that the reflection operators R A and R B are unitary, we can get the following Proposition.
Proposition 2
R A is a reflection operator about the space H A . Similarly, R B is a reflection operator about the space H B .
Proof.
We prove that R A is a reflection operator about the space H A . The other claim is analogous.
Definition 1
(Quantization of M.C. P)
A single step of the quantum walks is given by the unitary evolution operator W based on the transition matrix P. In the bipartite graph, an application of W corresponds to two quantum steps of the walk from v to e and from e to v. At time t, the whole operator of the quantum walks is Wt.
Spectral analysis of quantum walks on hypergraphs
In many classical algorithms, the eigen-spectrum of the transition matrix P plays a critical role in the analysis of Markov chains. In a similar way, we now proceed to study the quantitative spectrum of the quantum walks unitary operator W.
Szegedy proved a spectral theorem for quantum walks, W = ref2ref1, in ref.7. In this section, we deliver a slightly different version in that the cardinality of set X may be different from the cardinality of set Y in the bipartite graph. In order to analyze the spectrum, we need to study the spectral properties of an n × m matrix D, which indeed establishes a relation between the classical Markov chains and the quantum walks. This matrix is defined as follows:
Definition 2
(Discriminant Matrix) The discriminant matrix for W is
It also follows from the definition that \(D=\sqrt{{P}_{VE}\circ {P}_{EV}}\) with entries
Suppose that the discriminant matrix D has the singular value decomposition \(D=U{\rm{\Sigma }}{V}^{T}={\sum }_{i}\,{\sigma }_{i}{\mu }_{i}{\nu }_{i}^{T}\). The left singular vectors \(|{\mu }_{k}\rangle \) satisfy
and the right singular vectors
with σ k the singular value.
Theorem 2
For any σ k the singular value of D, 0 ≤ σ k ≤ 1.
Proof.
First, let Dk = σ k k. Then we obtain
Thus, |σ k | ≤ 1. Since 〈k, DTDk〉 ≥ 0 for all k, we have 0 ≤ σ k . Therefore, 0 ≤ σ k ≤ 1.
Observing theorem 2, we can write the singular value σ k as cos θ k , where θ k is the principal angle between subspace H A and H B . In the earlier years, Björck and Golub41 deducted the relationship between the singular value decomposition and the principal angle θ k between subspace H A and H B . That is, cos(θ k ) = σ k .
In the remainder of this section, we will explore the eigen-decomposition of the operator W, which can be calculated from the singular value decomposition of D.
First, we turn to the dimensionality of the spaces. Suppose that n ≥ m. We learned earlier that nd is the dimension of edge Hilbert space about the bipartite graph BGn,m, and the discriminant matrix D has m singular values, only some of which are non-zero. Space H A spanned by \(\{|{\alpha }_{v}\rangle :v\in V\}\), and space H B spanned by \(\{|{\beta }_{e}\rangle :e\in E\}\), are n – dimension and m – dimension subspaces of Hnd, respectively. Let H AB be the space spanned by \(\{|{\alpha }_{v}\rangle :v\in V\}\) and \(\{|{\beta }_{e}\rangle :e\in E\}\), and the dimension of H AB is rank(H AB ). Therefore, the dimension of space \({({H}_{A}\cup {H}_{B})}^{\perp }\) is given by nd – rank(H AB ), there are 2m eigenvectors in the space \({H}_{A}\cap {H}_{B}\), and rank(H AB ) – 2m remaining vectors in the space \({H}_{A}\cup {H}_{B}-{H}_{A}\cap {H}_{A}\).
Using A to left-multiply (30) and B to left-multiply (31), We have
As we mentioned before, the action of A and B preserve the norm of the vectors, and \(|{\nu }_{k}\rangle \) and \(|{\mu }_{k}\rangle \) are unit vectors, so \(A|{\mu }_{k}\rangle \) and \(B|{\nu }_{k}\rangle \) also are unit vectors.
Proposition 3
On space \({({H}_{A}\cup {H}_{B})}^{\perp }\), W acts as the identity.
Proof.
Suppose a vector \(v\in {({H}_{A}\cup {H}_{B})}^{\perp }\). Then v lies in the space orthogonal to both H A and H B . Since R i reflects a vector orthogonal to H i , then v is reflected by both R A and R B . Then applying a walk operator W does not change v. Hence \(W|v\rangle =|v\rangle \), and the subspace spanned by such v is an invariant subspace.
Observing Proposition 3, we only need to analyze the behavior of W in \({H}_{A}\cup {H}_{B}\).
Theorem 3
The subspace \(span\{A|{\mu }_{k}\rangle ,B|{\nu }_{k}\rangle \}\) is invariant under the action W.
Proof.
Suppose we have \(|v\rangle \in {H}_{v}^{n}\) and \(|w\rangle \in {H}_{e}^{m}\), then we want to analyze the action of R B on \(A|v\rangle \) and the action of R A on \(B|w\rangle \). (Since \(A|v\rangle \in {H}_{A}\), the action of R A on \(A|v\rangle \) is identity). Since we have
where the first term of the last line lies in H B and the second term in H A , and similarly
Hence, we only need to consider the action of W on \(A|{\mu }_{k}\rangle \) and \(B|{\nu }_{k}\rangle \}\) and that \(A|{\mu }_{k}\rangle \) is invariant by R A and \(B|{\nu }_{k}\rangle \}\) is invariant by R B .
The first term in the last line is the component of \(A|{\mu }_{k}\rangle \) that is along \(B|{\nu }_{k}\rangle \}\) and the second term is the component of \(A|{\mu }_{k}\rangle \) that is orthogonal to \(B|{\nu }_{k}\rangle \}\). So, on \(A|{\mu }_{k}\rangle \), R A is a reflection about \(A|{\mu }_{k}\rangle \) (identity in this case), and R B is a reflection about \(B|{\nu }_{k}\rangle \}\) (because of the orthogonal component) in the subspace. Similarly, on \(B|{\nu }_{k}\rangle \}\), R A is a reflection about \(A|{\mu }_{k}\rangle \) (because of the orthogonal component), and R B is a reflection about \(B|{\nu }_{k}\rangle \}\) (identity) in the subspace.
Next we shall create eigenvectors for W with the corresponding eigenvalues. Suppose that
and
Simply plugging (39) into formulas (38), we obtain the following equation:
Then, left-multiplying (39) by W, we have
Comparing formulas (40) and (41), we can obtain the following equations:
Concerning unit vectors \(A|{\mu }_{k}\rangle \) and \(B|{\nu }_{k}\rangle \), we consider two cases with respect to non-collinearity and collinearity, as follows.
Case 1.
First, we consider that \(A|{\mu }_{k}\rangle \) and \(B|{\nu }_{k}\rangle \) are linearly independent.
Using σ k = cos θ k , we obtain
through a series of algebraic operations. Furthermore, we have the corresponding eigenvectors
Case 2.
Then, we consider that \(A|{\mu }_{k}\rangle \) and \(B|{\nu }_{k}\rangle \) are collinear. However, since \(A|{\mu }_{k}\rangle \) is invariant under the action of Π A , \(B|{\nu }_{k}\rangle \) also is; and vice versa, since \(B|{\nu }_{k}\rangle \) is invariant under Π B , and \(A|{\mu }_{k}\rangle \) also is. Therefore, \(A|{\mu }_{k}\rangle \) and \(B|{\nu }_{k}\rangle \) are invariant under the action of W, and \(A|{\mu }_{k}\rangle \) are eigenvectors of W with eigenvalue 1.
As a consequence, we obtain the following theorem:
Theorem 4
Let W be the unitary evolution operator on BGn,m. Then W has eigenvalues 1 and −1 in the one-dimensional subspaces, and eigenvalues \({\lambda }_{k}={e}^{\pm 2i{\theta }_{k}}\) \((0 < {\theta }_{k} < \frac{\pi }{2})\) where (k = 1, 2, …, m) and the eigenvectors \(|k\rangle =\frac{A\,|\,{\mu }_{k}\rangle -{e}^{\pm i{\theta }_{k}}B|{\nu }_{k}\rangle }{\sqrt{2}\,\sin \,{\theta }_{k}}\) in the two-dimensional subspaces Table 1.
Discussion
Quantum walks are one of the elementary techniques of developing quantum algorithms. The development of successful quantum walks on graphs-based algorithms have boosted such areas as element distinctness, searching for a marked element, and graph isomorphism. In addition, the utility of walking on hypergraphs has been probed deeply in several contexts, including natural language parsing, social networks database design, or image segmentation, and so on. Therefore, we put our attention on quantum walks on hypergraphs considering its promising power of inherent parallel computation.
In this paper, we developed a new schema for discrete-time quantum walks on regular uniform hypergraphs using extended Szegedy’s walks that naturally quantize classical random walks and yield quadratic speed-up compared to the hitting time of classical random walks. We found the one-to-one correspondence between regular uniform hypergraphs and bipartite graphs. Through the correspondence, we convert the regular uniform hypergraph into its associated bipartite graph on which extended Szegedy’s walks take place. In addition, we dealt with the case that the cardinality of the two disjoint sets may be different from each other in the bipartite graphs. Furthermore, we delivered spectral properties of the transition matrix, which is the essence of quantum walks, and which has prepared for followup studies.
Our work presents a model for quantum walks on regular uniform hypergraphs, and the model opens the door to quantum walks on hypergraphs. We hope our model can inspire more fruitful results in quantum walks on hypergraphs. Our model provides the foundation for building up quantum algorithms on the strength of quantum walks on hypergraphs. Moreover, the algorithms of quantum walks on hypergraphs will be useful in quantum computation such as quantum walks search, quantized Google’s PageRank, and quantum machine learning, based on hypergraphs.
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Acknowledgements
I would like to thank Juan Xu, Yuan Su and Iwao Sato for helpful discussions. This work was supported by the Funding of National Natural Science Foundation of China (Grants No. 61571226 and No. 61701229), and the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20170802).
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Ying Liu initiated the idea and designed the modle; Ying Liu, Jiabin Yuan, Bojia Duan and Dan Li provided the theoretical proposal and analysis. All authors reviewed the manuscript.
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Liu, Y., Yuan, J., Duan, B. et al. Quantum walks on regular uniform hypergraphs. Sci Rep 8, 9548 (2018). https://doi.org/10.1038/s41598-018-27825-z
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DOI: https://doi.org/10.1038/s41598-018-27825-z
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