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quant-ph2026
Quantum Algorithms for Computational Fluid Dynamics
Mario Guillaume Cecile, Nis-Luca van Hülst, Tomohiro Hashizume +19
We present a comprehensive review of quantum approaches for solving partial differential equations (PDEs) arising in computational fluid dynamics (CFD). We examine fully quantum ap…
quant-ph2026
How Hard Is Quantum Advantage? A Cloud Microphysics Stress Test for Variational Quantum Models
Felix Herbort, Ellen Sarauer, Daniel Ohl de Mello +7
Quantum machine learning (QML) could have the potential to leverage advantages of quantum over classical computing but still lacks strong evidence of actual improvements and scalab…
quant-ph2026
Operator learning for efficient quantum computation
Paul Over, Sergio Bengoechea, Leonardo Borello Busilacchi +3
An efficient implementation of quantum algorithms is often hindered by the lack of efficient primitives for operators and state preparation. This limits both the ability of near-te…