IQM Quantum Computers (Nasdaq: IQMX) and Deutsche Bahn published results of a hybrid quantum-classical algorithm applied to real operational data, 190 trips across five German cities, roughly 98,500 possible scheduling cycles, using the Quantum Approximate Optimization Algorithm (QAOA) to solve smaller subproblems within a classical framework, executed end-to-end on IQM hardware.

This is IQM (now publicly traded on Nasdaq) demonstrating a named enterprise customer running its own real data on IQM's own hardware, not a synthetic benchmark. That's a meaningfully higher bar than most optimization-use-case press releases clear.

The result is "produced feasible solutions," not "beat classical methods." No performance comparison against Deutsche Bahn's existing classical scheduling tools was disclosed. Useful proof of integration, not yet proof of advantage.

"IQM and Deutsche Bahn Demonstrate Quantum Algorithm for Railway Scheduling on Real Operational Data," Business Wire, July 19-20, 2026