BASF, the world’s largest chemical company, is collaborating with quantum processor maker Pasqal to use quantum algorithms to predict weather patterns and solve other computational fluid dynamics problems.

Physics-based weather models are complex as they incorporate data on winds, heat transfer, solar radiation, relative humidity, terrain topology and many other parameters. This means accurate weather forecasting requires solving complex sets of nonlinear differential equations, which is something quantum computers can do more efficiently than classical computers.

“Pasqal’s quantum solutions are ideal for simplifying BASF’s complex computational simulations once quantum hardware matures to a point where we can actually leverage these algorithms,” said John Manobianco, senior weather modeler at BASF’s agricultural solutions division.

“Leveraging Pasqal’s innovation for weather modeling validates quantum computing’s ability to go beyond what can be achieved with classical high-performance computing. Such transformational technology can help us prepare for climate change impacts and drive progress toward a more sustainable future.”

Pasqal chief commercial office Benno Broer told Enter Quantum that Pasqal has experience applying quantum differential equations to other problems, including metal forming simulation as part of BMW’s manufacturing process.

Related:How BMW Uses Quantum to Disrupt Vehicle Manufacturing

“As part of its agribusiness, BASF is helping farmers with local weather prediction to maximize crop yields. They are also seeing it as a test case for these types of differential equations,” Broer said.

“Longer term, they have other use cases in mind, such as process engineering. Many companies we talk to say that they have many problems that are governed by differential equations; that was the case with BMW.”

Broer said that on the software side Pasqal has developed a proprietary algorithm designed to solve complex differential equations on near-term quantum processors. This could be implemented on any gate-based quantum computer hardware, but Pasqal’s hardware also offers an analog computational mode.

“We found out that if we replaced certain parts of the original algorithm with analog blocks, using Pasqal’s quantum analog mode, the algorithm not only becomes more efficient but also much more noise-robust.”

According to Broer, this means Pasqal’s solution could offer quantum advantage for solving engineering fluid dynamics problems in as few as three years, rather than the 10-year timescale most analysts predict.

At the end of the initial two-year collaboration between BASF and Pasqal, the companies will evaluate progress and decide whether to continue the weather forecasting research track or examine another potential use case.