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，减少能源浪费和资源部署，以最佳方式利用现有资源，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都是计算困难的问题，这些问题没有已知的有效解决方案的算法，可以随网络规模进行良好的扩展。事实上，要为许多大型网络问题提供真正的优化是不可能的，即使依靠经典的启发式方法，也往往不容易优化大型问题。网络优化的核心基本问题包括图着色和斯坦纳树等典型问题。量子退火法是一种利用隧道效应等量子效应来找到优化问题的解决方案的优化方法。目前已经有一些关于网络问题到量子退火炉的映射的工作，但要确定哪里可能存在量子优势，还需要做更多的工作。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.