Exploiting Quantum Computing for Large-Scale Transport Models

** 问题：** 摩尔定律对经典计算所能实现的目标施加了一个基本的上限。这对许多应用程序产生了广泛的影响，这些应用程序被描述为NP难/棘手的问题，这些问题在经典硬件上根本无法解决。交通运输和能源行业是众多NP难题的发源地。计算速度是一个关键的客户问题，交通运输和能源行业都明显需要更快、更大的模型。**我们的项目：** 我们的项目通过开发和测试运输和能源优化问题的公式化来探索改变游戏规则的机会，以实现更快的计算，这些问题是与不同类型的量子硬件相关的二次无约束二进制优化（QUBO）问题和量子近似优化算法（QAOA）。我们的创新建立在小嵌入等技术的基础上，并使用英国和其他地方正在开发的尖端系统。

**THE PROBLEM:**Moore's Law imposes a fundamental ceiling on what can be achieved by classical computing. This has an extensive impact on numerous applications, described as NP-hard/intractable problems, which simply cannot be feasibly solved on classical hardware. The transportation and energy sectors are home to numerous NP-hard problems.Computation speed is a critical customer issue with demonstrable demand for faster, larger models across both the transportation and energy sector.**OUR PROJECT:**Our project explores game-changing opportunities for faster computation by developing and testing the formulation of transport and energy optimisation problems as Quadratic Unconstrained Binary Optimization (QUBO) problems and Quantum Approximate Optimization Algorithms (QAOA) relevant to different types of quantum hardware.Our innovation builds on techniques such as minor embedding and uses cutting-edge systems being developed in the UK and elsewhere.