Beyond the Algorithm Challenge

Deloitte's Quantum Tensor Hydronauts (QT-Hydro) Team proposes a quantum-enhanced flood analysis approach using quantum reservoir computing (QRC) executed on both novel tensor-network simulations and neutral-atom hardware. Our methodology ingests SAR, optical, and elevation imagery, embeds them into high-dimensional quantum states via neutral-atom dynamics, and feeds the results to fast classical classifiers that label pixels as flooded or safe in near-real time. Three elements distinguish our solution: 1) Quantum reservoirs avoid barren-plateau training issues, producing stable models quickly; 2) A proprietary tensor-network engine scales quantum algorithms that can handle large problem sizes on GPUs; and 3) The modular architecture extends naturally to drought, heat-wave, and extraterrestrial weather analysis, broadening NASA’s Earth science reach. We will benchmark the largest problem sizes our simulator can solve against leading public tools and current neutral-atom devices, demonstrating immediate value and a clear path to even greater capacity as quantum hardware matures.