A new quantum algorithm performed a 15-step simulation of a nonlinear fluid around a solid barrier in a real quantum machine, the most physically complex publicly documented demonstration of its kind. The technique reduces qubit requirements and circuit depth, bringing industrial CFD applications closer to feasibility.
Finnish simulation company They will know and quantum middleware developer Haigu have demonstrated what they describe most physically complex quantum computing fluid dynamics simulation runs on real hardware to date.
The two companies ran a 15-step nonlinear fluid simulation around a solid obstacle, a fluid flowing around a shape, a type of problem on IBM’s Heron R3 quantum computer.
Computational fluid dynamics, or CFD, is one of the most resource-intensive areas of engineering simulation. Modeling how fluids behave around complex shapes requires a great deal of classical computing power, and the demands increase non-linearly as simulations become more detailed.
Quantum computation has long been theorized as a potential route to simulations that transcend the classical limit, but realizing this potential is limited by the large number of qubits and circuit depth, the length of quantum computing, and the computation required to run even moderately complex scenarios without being overwhelmed by errors.
The OSSLBM algorithm addresses this directly. A new framework based on the quantum Lattice Boltzmann Method (QLBM), an established approach for coupling classical fluid equations with quantum computations, reduces the computational burden of each step and allows longer multistep simulations to remain within what current quantum hardware can reliably perform.
Haigu‘s middleware layer was at the heart of this: it reduced circuit depth, developed new algorithmic subroutines, and implemented targeted error mitigation techniques that allowed the system to complete workflows that are inaccessible to today’s devices.
The significance of the result lies in the barrier. Previous quantum CFD demonstrations have mainly focused on simpler linear scenarios, fluid behavior without the complications of interaction with a solid boundary.
Modeling how a fluid moves around an object is a prerequisite for any industrially meaningful application. Professor Oleksandr Kyriienko, head of the Department of Quantum Technologies at the University of Sheffield, described the work as follows. “an interesting and timely contribution to quantum CFD” He added that more such research is needed to arrive at industrially relevant quantum solutions.
Quanscient and Haiqu have been collaborating on quantum CFD since at least 2024, when they were finalists in the Airbus and BMW Quantum Mobility Challenge, and have previously demonstrated work on IonQ hardware through Amazon Bracket. Industrial applications are years away; the current work is a research phase that establishes that the approach is feasible on existing hardware at this level of complexity.
