Munich-based startup Planqc, together with Saarland University, BMW, and Infineon, is launching the QIAPO research project. The project is being funded with €2.3 million by the German Federal Ministry of Education and Research. For Planqc, the project represents a further step in testing its technology in concrete industrial applications.
The focus is on complex optimization problems, such as those that arise in the production and distribution of cars or semiconductor chips. Such tasks can often only be solved approximately with conventional computers. At the same time, the calculations sometimes require a great deal of time and high computing power.
Planqc is developing a neutral atom quantum computer in Garching, which will be used in the project. For the startup, this is not just about research, but also about exploring whether its hardware can be practically applied to real-world industrial problems.
Hybrid meets classic
QIAPO employs a hybrid approach combining quantum computing and classical computing power. The quantum computer is intended to prepare particularly difficult parts of a problem so that classical computers can subsequently process them more effectively. The goal is therefore not to replace classical methods, but to complement them.
The benefits from the perspective of PlanqcThe startup can demonstrate the potential contribution of quantum computers to industrial processes. It's not just about performance in the lab, but about their potential practical applications.
Peter P. Orth, Professor of Theoretical Physics of Quantum Information at Saarland University, explains:
"Algorithms that are theoretically slower than others can still be faster in practice."
Step by step in the right direction
QIAPO does not aim to solve every industrial problem exactly. Instead, it focuses on finding better approximations. The reason: Many of these tasks are so complex that even a hybrid approach cannot solve them with absolute precision. However, if results can be improved or achieved more quickly, that would already represent practical progress.
Expectations are cautious for now. Over the next three years, the project aims to determine whether the approach is fundamentally suitable for tackling such tasks.
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