论文标题
使用绝热量子计算对大型互连图和网络进行优化
Optimization on Large Interconnected Graphs and Networks Using Adiabatic Quantum Computation
论文作者
论文摘要
在本文中，我们证明可以创建一种绝热的量子计算算法，该算法求解无向图上任何两个顶点之间的最短路径，其中最多3V量子位，其中v是该图的顶点的数量。除了创建（V X V）邻接矩阵外，我们在不依赖任何经典算法的情况下这样做。本文的目的是证明可以使用可用的最大量子数和随机图生成器（例如Barabasi-Albert和Erdos-renyi方法）在绝热量子计算机上对大图进行建模，这些方法可以根据功率定律扩展。
In this paper, we demonstrate that it is possible to create an adiabatic quantum computing algorithm that solves the shortest path between any two vertices on an undirected graph with at most 3V qubits, where V is the number of vertices of the graph. We do so without relying on any classical algorithms, aside from creating a (V x V) adjacency matrix. The objective of this paper is to demonstrate the fact that it is possible to model large graphs on an adiabatic quantum computer using the maximum number of qubits available and random graph generators such as the Barabasi-Albert and the Erdos-Renyi methods which can scale based on a power law.
