promoting quantum computing in the automotive industry

Quantum computing Collaboration BMW, Nvidia and Classiq are working on quantum computing for more efficient electric cars

2024-06-20 Updated on 2024-06-23 Source: Classiq | Translated by AI 2 min Reading Time

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BMW Group, NVIDIA, and Classiq aim to optimize mechatronic systems in a joint cooperation. The common goal is to promote the use of quantum computers in the automotive industry.

BMW, Nvidia, and Classiq are teaming up to improve mechatronic systems using quantum computing, particularly to make electric vehicles more efficient.(Image: Classiq) — BMW, Nvidia, and Classiq are teaming up to improve mechatronic systems using quantum computing, particularly to make electric vehicles more efficient.
(Image: Classiq)

The focus of the collaboration is the question of how the architecture of electrical and mechanical systems can be optimised. The biggest challenge is to identify the optimal combination of various components using complex calculations. In this process, it is also necessary to determine how these can best be connected to each other. The spectrum ranges from electric motors and batteries to cooling elements. This will help to find more efficient and economical configurations, and thus realise more cost-effective electric vehicles, according to a corresponding press release from Classiq.

Collaboration shortens development time

The experts at the BWM Group have developed a quantum program with a multitude of quantum sub-programs. This is one of the most complex and already successfully implemented programs of its kind. "Our collaboration with Classiq and Nvidia has produced an innovative quantum application and shows what becomes possible in the automotive industry as a result. Nvidia's quantum stack was crucial for simulating, testing, and refining this complex algorithm," says Lukas Müller, Team Lead Future Compute at the BMW Group.

The advanced modeling and compilation features of Classiq's software platform enabled this implementation, according to the company. An approach based on the so-called Quantum Approximate Optimization Algorithm—for optimization problems with many possible solution paths—and the Harrow-Hassidim-Lloyd Algorithm—for solving systems of linear equations—which was contributed by Classiq, was also used. In order to simulate the large and complex quantum circuits, Nvidia GPUs and the Nvidia Cuda-Q platform were also used. "This project is a vivid example of what collaborations in the field of quantum computing can achieve. By bringing together expertise in quantum hardware, software, and the automotive industry, we were able to make considerable progress in an exceptionally short period of time," says Nir Minerbi, CEO at Classiq.

The practical application of quantum computing is still in its early stages. Further research is necessary to make the jointly developed solution industrially applicable. Classiq, according to its own statement, is working continuously with other industry leaders to improve quantum design, implementation, and calculation to further advance the link between automotive technology and quantum computing.

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