Improved Resource State for Verifiable Blind Quantum Computation

Recent advances in theoretical and experimental quantum computing raise the problem of verifying the outcome of these quantum computations. The recent verification protocols using blind quantum computing are fruitful for addressing this problem. Unfortunately, all known schemes have relatively high overhead. Here we present a novel construction for the resource state of verifiable blind quantum computation. This approach achieves a better verifiability of 0.866 in the case of classical output. In addition, the number of required qubits is 2N+4cN, where N and c are the number of vertices and the maximal degree in the original computation graph, respectively. In other words, our overhead is less linear in the size of the computational scale. Finally, we utilize the method of repetition and fault-tolerant code to optimise the verifiability.

The Survey for Ontology Matching

An ontology enhances interoperability among applications via the Web. However, heterogeneity between ontologies blocks interoperability across ontologies via the Web. This paper introduces the classification of information used to matching ontologies, presents matching technologies in some aspects, and gives a brief outlook of these technologies, such as similarity flooding, coefficient computation, graph matching, machine learning, Bayesian decision theory, background knowledge discovering and exploiting. We believe this paper provides readers with a comprehensive understanding of ontology matching and points to various research topics about the specific roles of ontology matching.

VERTEX ISOPERIMETRIC PARAMETER OF A COMPUTATION GRAPH

Let G = (V,E) be a computation graph, which is a directed graph representing a straight line computation and S ⊂ V. We say a vertex v is an input vertex for S if there is an edge (v, u) such that v ∉ S and u ∈ S. We say a vertex u is an output vertex for S if there is an edge (u, v) such that u ∈ S and v ∉ S. A vertex is called a boundary vertex for a set S if it is either an input vertex or an output vertex for S. We consider the problem of determining the minimum value of boundary size of S over all sets of size M in an infinite directed grid. This problem is related to the vertex isoperimetric parameter of a graph, and is motivated by the need for deriving a lower bound for memory traffic for a computation graph representing a financial application. We first extend the notion of vertex isoperimetric parameter for undirected graphs to computation graphs, and then provide a complete solution for this problem for all M. In particular, we show that a set S of size M = 3k2 + 3k + 1 vertices of an infinite directed grid, the boundary size must be at least 6k + 3, and this is obtained when the vertices in S are arranged in a regular hexagonal shape with side k + 1.