A new quantum algorithm ran a 15-step nonlinear fluid simulation around a solid obstacle on real quantum hardware, the most physically complex publicly documented demonstration of its kind. The technique reduces qubit requirements and circuit depth, bringing industrial CFD applications closer to viability.
Finnish simulation company. they will know and quantum middleware developer Haiqu have demonstrated what they describe as the most physically complex quantum computing Fluid dynamics simulation run to date on real hardware.
The two companies ran a 15-step nonlinear fluid simulation around a solid obstacle—fluid flowing around a shape—the kind of problem relevant to aircraft wing design or vehicle aerodynamics—on IBM’s Heron R3 quantum computer, using a new algorithm they developed together called One-Step Simplified Lattice Boltzmann Method (OSSLBM).
Computational fluid dynamics, or CFD, is one of the most resource-intensive branches of engineering simulation. Modeling how fluids behave around complex shapes requires enormous classical computing power, and the demands grow nonlinearly as simulations become more detailed.
Quantum Computing has long been theorized as a potential path toward simulations beyond classical limits, but translating that potential into practice has been limited by the sheer number of qubits and the circuit depth—the length of quantum computing—necessary to run even moderately complex scenarios without the calculation being overwhelmed by errors.
The OSSLBM algorithm addresses this directly. Based on the Quantum Lattice Boltzmann Method (QLBM), an established approach for mapping classical fluid equations in quantum computing, the new framework reduces the computational overhead of each step, allowing a longer multi-step simulation to remain within what current quantum hardware can reliably execute.
HaiquThe middleware layer was critical to this: it reduced circuit depth, developed new algorithmic subroutines, and applied specific error reduction techniques that allowed the system to complete a workflow that would otherwise have been beyond the reach of current devices.
The importance of the result lies in the obstacle. Previous demonstrations of quantum CFD have largely focused on simpler linear scenarios, fluid behavior without the complications of interacting with a solid boundary.
Modeling how a fluid moves around an object is a prerequisite for any significant industrial application. Professor Oleksandr Kyriienko, Professor of Quantum Technologies at the University of Sheffield, described the work as “an interesting and timely contribution to quantum CFD” And he adds that more research of this type is needed to achieve industrially relevant quantum solutions.
Quanscient and Haiqu have been collaborating on quantum CFD since at least 2024, when they were finalists in Airbus and BMW’s Quantum Mobility Challenge, and have previously demonstrated their work on IonQ hardware through Amazon Braket. Industrial applications are still years away; The current work is a research milestone establishing that the approach is feasible on current hardware at this level of complexity.
