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

该提案旨在解决使用量子计算进行大规模真实的洪水建模研究的挑战。重点是利用量子计算，通过利用量子算法的力量来指明通往此类研究的道路。洪水建模涉及求解浅水方程（SWE），该方程描述了各种情况下的水流，如溃坝、风暴潮或河流洪水波。然而，在大面积和高分辨率上运行复杂模型的模拟的计算成本带来了限制。一种方法是简化模型，但这会损害准确性和有效性。该提案建议采用量子计算来解决这一计算挑战，方法是采用量子物理信息神经网络（QPINN）算法。该算法结合了经典的数据处理与量子处理使用变分量子电路（VQC）。数据被编码到VQC的量子门参数中，并且随着算法的进展，这些参数被调整以提高目标函数预测的准确性。该算法的可微性在噪声中间尺度量子（NISQ）时代特别有价值。该项目将由欧洲著名的量子软件初创公司Multiverse Computing领导，合作伙伴包括Oxford Quantum Circuits（OQC）和Moody's Analytics。多元宇宙计算将处理问题的技术制定和算法开发。量子硬件提供商OQC将提供必要的量子计算资源。全球风险评估公司Moody's Analytics将贡献行业专业知识、数据需求和对计算效率的见解。总之，该提案旨在利用量子计算，特别是QPINN算法，来解决大规模洪水建模研究中的计算挑战。通过利用量子算法的力量，并结合多元宇宙计算，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，更有效的洪水风险评估和管理铺平道路。

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.