Aegiq is developing quantum-ready computational fluid dynamics (CFD) methods that use tensor network techniques to improve the efficiency of high-fidelity fluid simulations.
The company combined its tensor-network-based CFD approach with NVIDIA cuQuantum tools, demonstrating logarithmic runtime scaling and generating meshes with more than one billion nodes on an NVIDIA L40S GPU.
Aegiq’s methods are designed to run on current GPU hardware while remaining compatible with future fault-tolerant quantum computers.
The material in this article is taken directly from content published on Aegiq’s website and reflects the company’s description of its research and development efforts.
Computational fluid dynamics has become one of the essential tools of modern engineering and science. It shapes the design of aircraft and jet engines, informs the aerodynamics of cars and ships, and underpins the numerical models used to forecast weather and understand climate. In each of these domains, the ambition is the same: to predict the behaviour of complex fluids accurately enough to make better decisions before anything is built, launched, manufactured, or deployed.
