Quantum computing produces better semiconductor materials faster
Semiconductor materials supplier Showa Denko KK has demonstrated the use of quantum computing to find optimal formulations of materials within seconds.
The company claims that because semiconductor materials contain such a large number of ingredients – such as resins, fillers and additives in various mixing ratios – the number of theoretical combinations can exceed 10^50. Working through these formulations would be effectively an intractable problem taking decades with conventional artificial intelligence models.
Showa Denko made use of Fujitsu’s Digital Annealing quantum computer and applied an Ising analysis model. The Ising model was originally developed to describe the behavior of spins in magnetic materials but has been shown to have broader applicability, particularly to combinatorial optimization problems.
By simulating the Ising model on Digital Annealer, Showa Denko was able to reduce the required exploration time to tens of seconds, or about 1/72,000 of the time required by conventional AI models. As well as reducing the search time the method produced a formula that achieves 30 percent higher performance as a semiconductor material.
The research group said it will apply this approach to various materials and accelerate its development activities,
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