Quantum Annealing for Telecoms Optimisation

电信网络优化的目标是为所有客户提供良好的服务质量，防止网络拥塞，减少能源和资源部署的浪费，以最佳方式使用现有资源，并帮助有效地规划新的部署。然而，网络提供商寻求优化的许多问题是计算困难的问题，这些问题没有已知的算法来有效地解决网络规模的问题。事实上，它是不可能提供真正的优化许多大型网络问题，即使依靠经典的启发式方法，它往往是不听话的优化大型问题。网络优化的核心问题包括一些典型问题，如图着色和Steiner树。量子退火是一种优化方法，它利用量子效应（如隧道效应）来找到优化问题的解决方案。在将网络问题映射到量子退火器方面，已有一些工作，但需要做更多的工作来确定量子优势可能存在的地方。在这个项目中，学生将开发在D-Wave量子退火处理器上运行的算法，最终目标是找到网络优化问题的有效解决方案。

The goals of telecoms network optimisation are to provide a good quality of service to all customers, preventing network congestion, reducing wastage of energy and resource deployment, using the existing resources in an optimal way and helping to plan new deployment effectively. However, many of the problems that network providers seek to optimise are computationally hard problems that have no known algorithms for efficient solution that scale favourably with network size. In fact it is not possible to provide true optimisations for many large network problems, and even if relying on classical heuristic methods it is often not tractable to optimise large problems. The fundamental problems at the heart of network optimisation include canonical problems such as graph colouring and the Steiner tree.Quantum annealing is a method of optimisation that exploits quantum effects such as tunnelling to find the solution to an optimisation problem. There is some existing work on the mapping of network problems to quantum annealers but much more work is needed to establish where a quantum advantage may exist. In this project the student will develop algorithms to run on the D-Wave quantum annealing processor, with the ultimate goal of finding efficient solutions to the network optimisation problem.