Insider Brief
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 possible scheduling cycles, with QAOA solving smaller optimization subproblems within a larger classical workflow.
The researchers found the approach produced feasible solutions on today’s hardware, improved as larger quantum subproblems could be processed, and completed the full optimization pipeline on an IQM quantum computer.
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.
