Public Funding for Multiverse Computing Ltd

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.

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.