Quanscient and Haiqu Develop Algorithm for Scalable Fluid Simulations on Quantum Computers
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Quanscient and Haiqu jointly announced a new algorithm designed to accelerate computationally intensive engineering simulations by using quantum computing.
The teams successfully conducted a 15-step nonlinear fluid benchmark, the most physically complex publicly documented demonstration of its kind using a Quantum Lattice Boltzmann Method (QLBM), on IBM’s Heron R3 quantum computer. This advancement addresses a critical limitation of applying quantum computing to computational fluid dynamics (CFD), significantly reducing the number of qubits required for complex simulations of fluid behavior around objects like aircraft wings. “This is an interesting and timely contribution to quantum CFD,” said Oleksandr Kyriienko, Chair in Quantum Technologies at the University of Sheffield. “We need more work like this to achieve industrially relevant quantum solutions.” Step QLBM Benchmark Achieves Complex Fluid Simulation on IBM Heron R3 Researchers from Quanscient and Haiqu collaborated to achieve this milestone, focusing on reducing the substantial resource demands historically associated with quantum simulations. This latest demonstration moves beyond simpler linear models, tackling the complexities of fluid flow around solid obstacles, a scenario crucial for real-world engineering applications.
The teams developed a novel One-Step Simplified LBM (OSSLBM) algorithm, a generalization of classical CFD techniques, and leveraged Haiqu’s algorithmic runtime layer to minimize circuit depth and enhance error reduction. This allowed the quantum system to execute a multi-step workflow previously unattainable with current hardware capabilities; the approach represents a new algorithmic framework that streamlines fluid simulations for quantum computers. Mykola Maksymenko, CTO of Haiqu, noted that “This is one of the most realistic CFD simulations ever executed on a quantum computer,” emphasizing the practical implications of simulating fluid interactions with complex shapes on quantum hardware. One-Step Simplified LBM Algorithm Reduces Qubit Count for Quantum CFD The pursuit of quantum computational fluid dynamics (CFD) has long been hampered by the sheer number of qubits required to model even moderately complex scenarios. A new algorithmic approach developed by Quanscient and Haiqu promises to significantly lower that barrier. Haiqu’s contribution was pivotal, with their algorithmic and runtime layer reducing circuit depth and incorporating targeted error-reduction techniques, allowing the quantum system to handle a multi-step workflow. “It is an important signal that quantum CFD research is moving toward simulating how fluids interact with real-world shapes and obstacles on quantum hardware.” The OSSLBM framework represents a shift in how fluid simulations are approached on quantum computers, streamlining calculations into a more efficient process tailored for quantum hardware. This is an interesting and timely contribution to quantum CFD. Oleksandr Kyriienko, Chair in Quantum Technologies, University of Sheffield Haiqu’s Runtime Layer Enables Multi-Step Quantum Workflows Haiqu, a developer of quantum middleware, played a pivotal role in enabling a complex, multi-step quantum workflow recently demonstrated by a collaboration with Quanscient. This achievement was not solely about qubit count; it hinged on Haiqu’s runtime layer, which significantly streamlined the process. The runtime layer proved critical in reducing circuit depth, a key factor in mitigating quantum decoherence, and in developing new algorithmic subroutines. Valtteri Lahtinen, Chief Scientist of Quanscient, explained the broader implications, noting that “CFD is one of the most computationally difficult branches of simulation with some of the largest impact on the world’s biggest sectors,” and that quantum computers offer a future path to simulations exceeding the limits of classical systems. This hybrid quantum-classical approach, according to the teams, outlines a practical path toward realistic engineering applications as quantum systems mature, and “This is the direction that any industrially meaningful workflow would have to take to reach commercial viability.” This is one of the most realistic CFD simulations ever executed on a quantum computer. Mykola Maksymenko, CTO of Haiqu Quanscient & Haiqu Advance Industrially Viable Quantum Fluid Dynamics The pursuit of commercially relevant quantum computing applications took a significant step forward with a new algorithm developed by Quanscient and Haiqu, promising to accelerate complex fluid dynamics simulations crucial to several industries. Beyond academic demonstrations, this work focuses on practical application, addressing the substantial computational demands of modeling airflow around aircraft or optimizing energy systems, tasks often exceeding the capabilities of even the most powerful conventional supercomputers. This advancement centers on reducing the resource requirements for quantum computational fluid dynamics (CFD); the algorithm minimizes the number of qubits and computational operations needed for these simulations. It proposes a more flexible quantum LBM framework while keeping the core algorithm efficient, and it strengthens the case with applications ranging from linear acoustics to IBM-QPU-assisted nonlinear flow simulations. We need more works like this to achieve industrially relevant quantum solutions. Oleksandr Kyriienko, Professor and Chair in Quantum Technologies at the University of Sheffield Source: https://world.einnews.com/pr_news/903218681/quanscient-and-haiqu-announce-breakthrough-algorithm-for-scalable-computational-fluid-simulations-on-quantum-computers Tags: