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This collaboration demonstrates a practical hybrid quantum-classical workflow using real-world data to solve complex railway scheduling optimization problems on current superconducting hardware. The results validate that enterprise-scale applications in logistics and supply chain management are viable today, without waiting for future fault-tolerant systems.
IQM And Deutsche Bahn Demonstrate Quantum Algorithm For Railway Scheduling on Real Operational Data
Insider Brief PRESS RELEASE — IQM Quantum Computers (Nasdaq: IQMX), a global leader in full-stack superconducting quantum computers, today published the results of a research collaboration with Deutsche Bahn, Europe’s largest rail operator, exploring how quantum computing can improve railway scheduling. Using a real operational dataset from Deutsche Bahn, a schedule of 190 trips across […]
IQM and Deutsche Bahn demonstrated a hybrid quantum-classical approach that used real railway scheduling data to solve a large-scale optimization problem on current quantum hardware, providing a framework that could be applied across industries. The project used a real Deutsche Bahn dataset covering 190 trips across five German cities and about 98,500…
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