Quantum Accelerated Solver

Quantum Accelerated Solver

Project Overview

Year

About

Quantum Accelerated Solver uses tensor-network algorithms to dramatically reduce the computational cost of simulating complex systems in fields such as aerospace, finance, and climate modelling. Running on existing high-performance computers, it compresses simulations while maintaining accuracy and lays the groundwork for future quantum acceleration. Compatible with standard CFD inputs, the framework delivers rapid, transparent results with engineering-grade error estimates. This approach enables faster design cycles, saves energy, and opens new simulation regimes previously deemed intractable

Team

Hai-Yen Van

Hai-Yen Van

Tomohiro Hashizume

Tomohiro Hashizume

Mario Guillaume Cecile

Mario Guillaume Cecile

Dr. Dieter Jaksch

Dr. Dieter Jaksch

Supervising Professor

Nis-Luca Van Hülst

Nis-Luca Van Hülst

Nis-Luca van Hülst is a PhD candidate in Physics at the University of Hamburg. He and his University of Hamburg team won the 2024 Airbus-BMW Group Quantum Computing Challenge (Quantum Solvers track). His research develops quantum and quantum-inspired solutions for computational fluid dynamics, assessing their accuracy, scaling, and memory requirements across different physical regimes and non-trivial geometries. He uses these results to quantify the quantum resources needed to achieve a practical advantage over classical methods.

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