Quantum-Assisted Flood Modeling: Pioneering Large-Scale Analysis for Enhanced Risk Assessment

量子辅助洪水建模：开创性大规模分析以增强风险评估

• 批准号: 10083669
• 金额: $ 13.51万
• 依托单位: MULTIVERSE COMPUTING LTD
• 依托单位国家: 英国
• 项目类别: Small Business Research Initiative
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10083669
• 关键词: Quantum; Assisted; Flood; Modeling; Pioneering

The proposal aims to address the challenge of conducting large-scale real flood modeling studies using quantum computing. The focus is on utilising quantum computing to indicate a path towards such studies by leveraging the power of quantum algorithms. Flood modelling involves solving the Shallow Water Equations (SWE), which describe the flow of water in various scenarios such as dam breaks, storm surges, or river flood waves. However, the computational cost of running simulations with sophisticated models over large areas and high resolution poses limitations. One approach is to simplify the models, but this compromises accuracy and effectiveness. The proposal suggests employing quantum computing to tackle this computational challenge by employing a Quantum Physics-Informed Neural Network (QPINN) algorithm. The algorithm combines classical data processing with quantum processing using a Variational Quantum Circuit (VQC). The data is encoded into the quantum gate parameters of the VQC, and as the algorithm progresses, these parameters are adjusted to improve the accuracy of target function predictions. The algorithm's differentiability is particularly valuable in the Noisy Intermediate-Scale Quantum (NISQ) era. The project will be led by Multiverse Computing, a prominent quantum software start-up based in Europe, with partners Oxford Quantum Circuits (OQC) and Moody's Analytics. Multiverse Computing will handle the technical formulation of the problem and algorithm development. OQC, a quantum hardware provider, will supply the necessary quantum computing resources. Moody's Analytics, a global risk assessment firm, will contribute industry expertise, data requirements, and insights on computational efficiency. In summary, this proposal seeks to utilize quantum computing, specifically the QPINN algorithm, to address the computational challenges in large-scale flood modeling studies. By leveraging the power of quantum algorithms and combining the expertise of Multiverse Computing, Oxford Quantum Circuits, and Moody's Analytics, the project aims to pave the way for more accurate and efficient flood risk assessment and management.

该提案旨在应对使用量子计算进行大规模的真实洪水建模研究的挑战。重点是利用量子计算来指示通过利用量子算法的能力来指示此类研究的途径。洪水建模涉及解决浅水方程（SWE），这些水方程描述了在大坝中断，暴风雨或河流洪水等各种情况下的水流。但是，在大面积和高分辨率上使用复杂模型运行模拟的计算成本会带来限制。一种方法是简化模型，但这损害了准确性和有效性。该提案建议采用量子计算来通过采用量子物理知识的神经网络（QPINN）算法来应对这一计算挑战。该算法将经典数据处理与使用变分量子电路（VQC）结合了量子处理。数据被编码到VQC的量子门参数中，并且随着算法的进行，这些参数被调整以提高目标函数预测的准确性。该算法的可不同性在嘈杂的中间量子（NISQ）时代特别有价值。该项目将由Multiverse Computing（一家位于欧洲的著名量子软件初创企业）领导，合作伙伴牛津量子电路（OQC）和穆迪的分析。多元宇宙计算将处理问题和算法开发的技术公式。量子硬件提供商OQC将提供必要的量子计算资源。穆迪（Moody）的分析公司是一家全球风险评估公司，将贡献行业专业知识，数据需求以及计算效率的见解。总而言之，该提案试图利用量子计算，特别是QPINN算法来解决大规模洪水模型研究中的计算挑战。通过利用量子算法的力量，结合了多元宇宙计算，牛津量子电路和穆迪分析的专业知识，该项目旨在为更准确有效的洪水风险评估和管理铺平道路。