IQM Quantum Algorithm to realize its enterprise potential in research collaboration with Deutsche Bahn The IQM Quantum Algorithm generated feasible railway scheduling solutions based on real operational data. The IQM Quantum Algorithm was also run on existing quantum hardware, demonstrating that organizations can start to benefit from hybrid quantum computing technologies today.
IQM Quantum Computers, the world leader in full-stack superconducting quantum computers, announces the results of its research cooperation with Deutsche Bahn – Europe’s largest rail operator. Both organisations looked at the potential of quantum computing to improve railway scheduling by solving complicated operational problems.
The research team used an operational dataset from Deutsche Bahn, consisting of 190 railway trips in five German cities. This dataset was about 98,500 possible scheduling cycles. So the companies developed and tested a hybrid quantum-classical algorithm that solves enterprise scale optimization problems more efficiently.
The published whitepaper describes the research team’s implementation of the Quantum Approximate Optimization Algorithm (QAOA). Instead of solving the entire problem, the quantum processor solved small optimization problems. Meanwhile, a classical computing framework handled the overall scheduling. This allows the architecture to be applied to similar optimization problems in logistics, manufacturing, energy and other industries.
Hybrid Quantum Computing Provides Practical Enterprise Benefits
The research has produced three main findings: For one, the hybrid approach was able to run successfully on the quantum hardware that exists today. That means organizations can start to explore practical quantum computing applications, without waiting for fault tolerant quantum systems.
Second, the researchers saw that larger quantum subproblems produced better scheduling solutions. Therefore in the future the overall performance should be improved without any modifications to the current set-up, by simply improving the quantum processors.
Third, the entire scheduling workflow performed on IQM hardware. The quantum system was able to perform the full process of problem formulation to solution delivery. This provides enterprises with a practical basis to develop future quantum optimization applications.
“This collaboration shows that quantum computing is already capable of tackling the kind of large-scale, real-world optimization problems enterprises face every day,” said Dr. Inés de Vega, Chief Scientist of IQM Quantum Computers. “Working with Deutsche Bahn on a problem of this complexity gives us a clear blueprint for how quantum computing delivers value now, while scaling naturally as hardware improves.”
“Quantum computing is not going away. By tackling a real-world problem in a hybrid HPC and quantum computing environment, we have taken another step toward quantum advantage,” said Manfred Rieck, Head of Quantum Technology at Deutsche Bahn.
Although this project focused on scheduling under stable operating conditions, the researchers believe the same hybrid architecture could eventually support real-time operational decisions. As quantum hardware continues to evolve, enterprises may respond more effectively to unexpected disruptions occurring within minutes instead of hours.
Furthermore, the collaboration highlights IQM’s commitment to accelerating enterprise adoption of quantum computing. The company continues developing systems that customers can own, operate, and expand as quantum technologies mature.
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News Source: Businesswire.com
